Is AI making embedded software developers more productive? - Page 1
Forum section: electronics / beginners

author: jkushuee
author_rank: Newbie
timestamp: June 16, 2025, 09:18:27 am
content: I feel like the ai code generation companies such as cursor and Windsurf have completely ignored the world of embedded software development. Is there anybody in this ecosystem who has been able to successfully utilize AI tools to to develop embedded software.If yes I would like to see specific examples of how it has been useful as well as what tools were they using please. TIA.PS: Feel free to mention any AI tools that are helping in hardware development overall

author: brucehoult
author_rank: Super Contributor
timestamp: June 16, 2025, 10:17:26 am
content: I don't have any evidence except my personal tests of it, but I strongly suspect that1) adding AI (or interns/juniors) to a project lets you tell management that the code is "finished" in a shorter time that they love2) you then spend more extra time debugging than you saved in coding, whether before deployment or after.

author: tggzzz
author_rank: Super Contributor
timestamp: June 16, 2025, 10:52:25 am
content: Quote from: jkushuee on June 16, 2025, 09:18:27 amThe definition of "success" is critical.1) "marked as complete" and handed over to someone else.2) "customer has accepted it as working correctly".3) "can be maintained and enhanced for the next version of the product".The first is easy - but only of interest to beancounters and managers.The second is important to all concerned. If problems emerge during integration and acceptance, they can beveryembarrassing andveryexpensive to fix.The third is important if you want the product and/or company to have a good reputation and grow.So, what's your definition of "successfully utilised"?

author: tggzzz
author_rank: Super Contributor
timestamp: June 16, 2025, 10:57:15 am
content: There's another thread on the topic:https://www.eevblog.com/forum/chatgptai/ai-in-low-level-embedded-systems/msg5919218/#msg5919218You would be well advised tounderstandthe points made there.

author: tggzzz
author_rank: Super Contributor
timestamp: June 16, 2025, 11:01:30 am
content: Quote from: jkushuee on June 16, 2025, 09:18:27 amThere could be several reasons for that...They realise that (unlike application/server level code) correcting embedded mistakes can be very difficult and expensive.The quality of the training examples issuboptimalcrap, and don't want to be exposed to lawsuits about GIGO.

author: golden_labels
author_rank: Super Contributor
timestamp: June 16, 2025, 11:16:59 am
content: Let me add a few more definitions tothe three already offered by tggzzz:4) Makes the product better to a user.5) Makes the product better to an experienced user. It’s a group very different than the entire users set.6) Increases company’s profits over costs, regardless of other factors.7) Increases CEO’s premium.8) Rises company’s stock price.9) Benefits developers long-term.10) Improves situation for the society.Aother person coming to this thread is going to add a few more into the bin.Can you see, where this is going? Note: we didn’t even touch the simple fact, that “best” is poorly modeled by a one-dimensional axis or calculating the net outcome.

author: ahsrabrifat
author_rank: Regular Contributor
timestamp: June 16, 2025, 02:07:37 pm
content: Quote from: jkushuee on June 16, 2025, 09:18:27 amCheck e Edge AI Studio by Texas instruments.

author: tggzzz
author_rank: Super Contributor
timestamp: June 16, 2025, 02:58:55 pm
content: Quote from: ahsrabrifat on June 16, 2025, 02:07:37 pmWhat does that sales literature claim? (I'm not going to spend 35minutes of my life on sales literature!)Can anyone (other than those paid by the company) confirm they have used that product successfully?

author: aaronhance
author_rank: Regular Contributor
timestamp: June 16, 2025, 06:09:46 pm
content: Chat GPT does quite well with a range of development tasks. I'm a software developer and I use it most days, the only embedded stuff I do at work is Arduino and ESP-IDF. I find if you know what you are doing it works well and speeds up your development, but if you don't know what you are doing it paralyses you.

author: tggzzz
author_rank: Super Contributor
timestamp: June 16, 2025, 07:31:55 pm
content: Quote from: aaronhance on June 16, 2025, 06:09:46 pmThat is a common experience: in order to be able to recognise a hallucination, you must know/understand more than the LLM. It isn't a difficult concept! Unfortunately beginners will use LLMs.Serious professional evaluation:https://www.science.org/content/blog-post/evaluation-deep-research-performancedifferent topic allows us to see wood for trees. N.B. he notes what LLMs do well, but...As with all LLM output, all of these things are presented in the same fluid,confident-sounding style: you have to know the material already to realizewhen your foot has gone through what was earlier solid flooring. That,to me, is one of their most pernicious features. I know that these thingswere not designed per se to glide over or hide their weak points and theirmistakes, but they do a terrific job of it, and that's not really what you want.Widely quoted, but now discredited hype:https://www.science.org/content/blog-post/whoa-now-cautionary-tales-materials-scienceand againEntertaining rant:https://deplet.ing/the-copilot-delusion/about programmingSo. Props where props are due. Copilot is like a thoughtless yet high-functioning, practically poor intern:Great with syntax memory.Surprisingly quick at listing out your blind spots.Good at building scaffolding if you feed it the exact right words.Horrible at nuance.Useless without supervision.Will absolutely kill you in production if left alone for 30 seconds.

author: Manul
author_rank: Super Contributor
timestamp: June 16, 2025, 10:18:59 pm
content: At the moment LLM is like an extension to web search engine, cause you can't trust it for any serious job. Personally I tried one time and it just irritates me. I better write code myself which I trust and it also brings an extra benefit - I know what I wrote, I remember it well and if next day I need to modify it, it's easy. Also writing yourself helps to see how all things fit together, what dependencies there might be and so on.The only truely useful thing will be some hybrid AI, which I'm sure will come. Chess engines illustrates it very well. There are classical engines like Stockfish or Komodo. They use brute force search + heuristics which reduce search tree (very strong tactically). And there are neural engines like Alpha zero and Leela, which are trained neural networks, which don't really "search", but evaluate based on training data (very strong in positional chess). And now appears engines which use best of both. When humans play, they also tend to choose a few candidate moves which feel interesting/best and calculate them in depth to confirm. So we humans are hybrid. We have both a gut feeling and can calculate stuff accurately when needed (but it's slow for us).One day AI will be able to use it's neural network to come up with ideas but be able run an actual emulation for testing and debugging. And read a real datasheet. In essence it must have interface to real computational tools and access to real data. So basically a neural network together with petabytes of real books, datasheets and classical software tools, like compilers, emulators and libraries. Then we will be talking. For the moment - nah.

author: tggzzz
author_rank: Super Contributor
timestamp: June 16, 2025, 10:41:32 pm
content: The problem of training data is trivial: justcontinueto use LLMs togenerateit. GIGO? Model collapse? What are they?As for the problem being solved by a "more advanced hybrid AI".... That is suggesting taking something so complex that the output cannot be predicted, and making it bigger. As Tony Hoare famously put it “There are two ways of constructing a piece of software: One is to make it so simple that there are obviously no errors, and the other is to make it so complicated that there are no obvious errors.”Many people claim that more advanced AI will "understand" the subject. To attempt to distance such things from LLMs, they are termed Large Reasoning Models (LRMs). Here's a reasonable newspaper articlehttps://www.theguardian.com/technology/2025/jun/09/apple-artificial-intelligence-ai-study-collapseabout what researchers are discovering about LRM capabilities and limitations. The source is an Apple reporthttps://ml-site.cdn-apple.com/papers/the-illusion-of-thinking.pdf

author: radiolistener
author_rank: Super Contributor
timestamp: June 16, 2025, 11:05:33 pm
content: It depends. If you're newbie and want to develop "blinking LED firmware", then it can reduce time.For real tasks I don't see any improvement, you still need to write code yourself, all what is changed is that you can use AI as a more smart google.The main issue of AI is that while it is good at small and easy tasks, it completely unable to solve complicated tasks. When I talking "completely", I mean that AI is even worse than junior developer for such kind of tasks.In other words, while AI can match or even exceed a developer’s efficiency on simple tasks, its performance drops off sharply to zero as task complexity increases - even on problems that a junior developer could typically handle with spending some time.Here is curve that explain it:

author: Manul
author_rank: Super Contributor
timestamp: June 16, 2025, 11:23:27 pm
content: I'm not gone act like LLM and present here some hallucinatory confidence of when it will happen, but sooner or later it will.Basically there should be iterations between prediction and real world verification. That is not "reasoning" btw.Predict code. Try to compile (with real compiler). Let's say, does not compile. Predict why it does not compile. Retry. Ok, compiles. Run under extensive emulation with all the emulated peripherals and such. Crashes. Predict why. Does not crash, but does not do what it should do. Predict why. And so on. Iterate thousands of times if needed. And also if needed, use real factual data, not predictions. If such system would be able to successfully converge (most of the time), it would already be orders of magnitude improvement over toys like LLM and could be called useful.

author: radiolistener
author_rank: Super Contributor
timestamp: June 16, 2025, 11:47:20 pm
content: it's important to recognize that not all progress scales linearly - and AI may face hard limitations similar to those we’ve seen in other technological domains.For example, in the early 2000s, it seemed like CPU clock speeds would continue to rise indefinitely. But in practice, we hit a wall around 4 GHz due to thermal and physical constraints. Pushing beyond that became exponentially more difficult and costly, so the industry shifted toward parallelism instead of raw frequency gains.I believe AI is facing a comparable kind of ceiling. There's a point beyond which further gains in general reasoning and adaptability may become economically or physically impractical using current architectures. Instead, we'll likely see hybrid systems emerge, combining LLMs with formal reasoning engines, symbolic systems like Wolfram, program analyzers, and structured knowledge sources - to overcome AI’s current limitations.The future may not be about AI replacing developers wholesale, but about augmenting them through carefully engineered combinations of specialized tools.In this context, asking whether AI is making embedded software developers more productive is akin to asking whether a calculator makes a programmer more productive. It doesn’t replace them, but it can streamline certain tasks - particularly those involving routine calculations, boilerplate generation, or pattern recognition - thereby assisting rather than replacing the developer.

author: jkushuee
author_rank: Newbie
timestamp: June 17, 2025, 08:05:42 am
content: hi folks,I hear you.This group is 10x more useful than the reddit thread I had started. (https://www.reddit.com/r/embedded/comments/1lcohtg/is_ai_making_embedded_software_developers_more/)can totally relate to the skeptics who don't trust AI yet. Is it a training data set problem? Perhaps yes. Is it a reliability problem at layers closer to hardware - definitely yes.Having spent a decade and half in the industry, I can definitely say that the industry hasn't really evolved. The world still depends on hardware innovation to drive software forward but the way we're building hardware/firmware still is obscenely old school. how many of you use VIM/Eclipse/VSCode - I'll say majority.A fraction of you do claim to use LLM daily - my firm belief is that, that number is bound to change. Cursor is the fastest growing SaaS company ever. and that will have ripple effects in the softdev ecosystem.I am working on a creating a tool like cursor for embedded software - what would be the top features you'd want? Seeding a few thoughts:1. Code generation and editing (of course)2. Board bring-up software dev3. Schematic validation by looking at Datasheet and Application notesfeature++thoughts?

author: radiolistener
author_rank: Super Contributor
timestamp: June 17, 2025, 08:17:26 am
content: Quote from: jkushuee on June 17, 2025, 08:05:42 amWhile code generation and automated editing are often highlighted as key AI features, I personally don’t find them particularly useful. The output is typically highly variable and requires careful line-by-line review, which often offsets any time saved during generation, especially when dealing with low-level, hardware-specific code.Where I do see real potential is in AI-assisted code analysis. For example:1) Identifying common patterns of bugs or anti-patterns.2) Highlighting potentially problematic constructs or edge cases.3) Generating simplified structural overviews of large codebases - particularly useful when trying to quickly grasp unfamiliar or legacy code.In these areas, AI can significantly boost productivity by serving as an intelligent assistant, rather than an autonomous author.

author: tggzzz
author_rank: Super Contributor
timestamp: June 17, 2025, 08:21:39 am
content: Quote from: Manul on June 16, 2025, 11:23:27 pmSo you deprecatedesigninga system and think thattestingis sufficient. Complete nonsense: the most testing can achieve is to determine you haven't found the next error.That is very, lethally,evidentin fully automated car control systems, despite the proponents denying it.Old engineering saying: you can't test quality into a product, it has to be designed.Simple examples: please use your development technique to create (from scratch) a distributed software system that has ACID properties or a hardware system with metastable immune properties.A named CEO of one of the world's leading AI labs has made a useful and correct statement - which should give pause for thought.Anthropic CEO Dario Amodei just said the quiet part out loud: thatnobody really knows how AI works.Fuller summary plus link to the original athttps://catless.ncl.ac.uk/Risks/34/62/#subj46.1 people paying attention to decent sources and understanding how LLM technologyworksoperates won't be surprised.

author: tggzzz
author_rank: Super Contributor
timestamp: June 17, 2025, 08:29:05 am
content: Quote from: jkushuee on June 17, 2025, 08:05:42 amThat is a standard resultRuddit and stackexchange are - by design - useful for questions like "which button do I press to frobnnitz the spoogle".QuoteThe LLM training set problem became apparent40 years ago, i.e.early-mid 1980s. Igor Aleksander's WISARD also demonstrated other key unsolved problems: understandingwhyit generated a result, andpredictingwhat it would/wouldn't do with atriviallydifferent input.If you want another high quality source and discussion of risks, see the low-volume-high-SNR comp.risks Risks Digest and its archivehttps://catless.ncl.ac.uk/Risks/

author: jkushuee
author_rank: Newbie
timestamp: June 17, 2025, 09:09:07 am
content: 100% true

author: jkushuee
author_rank: Newbie
timestamp: June 17, 2025, 09:21:12 am
content: Quote from: radiolistener on June 17, 2025, 08:17:26 amcurious how much will you pay for the IDE per month if these features became part of the IDE such as Cursor (or another VSCode fork)?

author: brucehoult
author_rank: Super Contributor
timestamp: June 17, 2025, 09:21:25 am
content: Quote from: tggzzz on June 17, 2025, 08:29:05 amI think that depends on the particular sub, the moderators, the membership, the culture. Different subs are completely independent entities, just as stores on Amazon or Aliexpress are.

author: tggzzz
author_rank: Super Contributor
timestamp: June 17, 2025, 12:56:02 pm
content: Quote from: brucehoult on June 17, 2025, 09:21:25 amI'm happy to accept your judgement for ruddit. I believe there has recently been objections/defections as a result of attempts to monetise the platform, but I haven't followed any details.I'll won't change my assessment of stackexchange. It is designed to be "how do I change the colour" Q&A, which is fine but boring.

author: brucehoult
author_rank: Super Contributor
timestamp: June 17, 2025, 01:29:10 pm
content: Quote from: tggzzz on June 17, 2025, 12:56:02 pmI'm biased. In late 2019 I was invited to essentially take over moderation of a Reddit sub that was just hitting 2500 members, when the person who created it it 4 1/2 years earlier no longer had time. A few days ago it passed 26,000 members. I think that place works fairly well. And a week ago I was invited to help mod another sub created in early 2015 which currently has 11.5k members, up 3.5k over the last year.Those are relatively small and very technical subs. A very different thing to the subs dedicated to controversial topics and with millions of members!Just like on X you have both the possibility and the responsibility to choose who and what you read.

author: tggzzz
author_rank: Super Contributor
timestamp: June 17, 2025, 01:41:28 pm
content: Sounds goodTo some extent it is a matter of, unlike our youth, having the luxury of having so much material available that it is necessary to decide what to largely ignore.

author: golden_labels
author_rank: Super Contributor
timestamp: June 17, 2025, 03:33:43 pm
content: Quote from: jkushuee on June 17, 2025, 08:05:42 amIt is not a matter of trust, there is no “yet,” and certainly there is nothing skeptical about that.It is understanding what a tool is, how it works, what it is capable of and what it can’t do. A hammer does not drive screws, even if a less observant or outright ignorant person may get confused, seeing only some outcomes.And not being able to answer your question is even less of “skeptic,” or “trust,” or “yet.” It’s about the question being ill-defined. It feels like posts telling this just flew by you, without making any impression.Quote from: jkushuee on June 17, 2025, 08:05:42 amHonestly? So far you didn’t convince me you know how ML operates and, at the same time, your messages match those of a typical person lacking that basic understanding. Accordingly, let me be blunt: taking basic courses in probabilistics, statistics, linear algebra, and logics. And then at least trying to comprehend the mathematics you’re trying to apply.

author: radiolistener
author_rank: Super Contributor
timestamp: June 17, 2025, 07:23:38 pm
content: Quote from: jkushuee on June 17, 2025, 09:21:12 amPersonally, I don’t pay out of pocket for such tools - that’s typically a decision made at the company level. For organizations to justify paying for an enhanced IDE or tools, they generally need to see a clear and measurable return on investment - improved productivity or process, faster development cycles, or reduced defect rates.That said, engineers do influence these decisions - especially when a tool significantly improves developer experience or workflow efficiency. Even if the utility doesn't directly translate into measurable profit, companies are sometimes willing to invest in tools that make their developers lives easier. A more comfortable and streamlined environment can contribute to better team morale, lower turnover, and higher overall satisfaction, which indirectly benefits the organization.I would caution against tightly coupling your solution to a specific IDE. Even if a company sees value in your product and is willing to pay for it, they may ultimately pass if it requires switching from their existing development environment. Many teams have deeply integrated workflows, toolchains, and automation tied to their current IDE, and are unlikely to rework those just to adopt a new platform.A more strategic approach would be to design your product as a set of standalone utilities or services. IDE integration could then be offered as an optional layer, making adoption easier and more flexible across a broader range of development environments.

author: Manul
author_rank: Super Contributor
timestamp: June 17, 2025, 08:54:19 pm
content: Quote from: tggzzz on June 17, 2025, 08:21:39 amIf you call it nonsense, you either misunderstood the thread or what I said. We are are talking here about increased productivity. I understand that as assisting human designer in some useful way. In embedded world it may mean initialization code snippets, more specific tasks like "use timer to generate SPWM output", these sort of things. System design is a whole different field. But a trustful code snippet writing AI would certainly be useful and increase productivity. Modern hardware gets more complex. Setting up state of the art ARM MCU is much more involved than some old 8 bit AVR. Assistance would save time.Again, the main problem of trained AI models is that all the training data is crunched into coefficients and there is no concrete data saved. So it crunched a million datasheets, but it can't cite a single specific datasheet, cause it does not exit in the model as such. Unavoidably, the response will be poisoned by data bleed from hundreds of other similar datasheets which were used for training. So if you ask it to configure MCU peripheral, it might, for instance, start setting bits which don't even exist on that particular MCU. Which is a trivial error to check, yet impossible for such AI to avoid.And the second biggest issue is that it can't validate it's output in some automated way (like running a code it just generated), a human must do it manually. To be fair, what it generates is much better than monkeys typing on a keyboard. After telling it many times that it does not work as expected, sometimes it stumbles upon something which is correct. So if you hide all that under the hood of automated verification, the end user will get much higher quality results. That requires it to be able to do classical computation - in this case code emulation as a supplement to neural network output.

author: radiolistener
author_rank: Super Contributor
timestamp: June 17, 2025, 09:57:09 pm
content: Quote from: Manul on June 17, 2025, 08:54:19 pmRelying on AI-generated code for production use, especially in embedded systems, is a risky and naive approach. While AI can indeed produce plausible-looking code snippets, there's no guarantee that the code is correct, safe, or even meaningful. It may appear to work in simple cases while hiding subtle issues that only surface under specific conditions.From my practice, AI-generated code usually requires more time for review and debugging than writing clean, well-understood code manually. This is particularly true when dealing with low-level hardware setup, where incorrect register configurations can lead to hard-to-diagnose behavior or even hardware damage.If you're already familiar with the MCU architecture and peripheral configuration, AI might help by suggesting examples or reminding you of register names. But for those who aren’t deeply familiar with the platform, blindly using AI-generated initialization code is dangerous and stupid. You risk deploying something you don't fully understand - and when a bug inevitably appears, no one on the team may be able to explain or fix it, especially if the original logic came from AI and not a developer.In short, AI can be a helpful assistant for exploration or prototyping, but it shouldn't be trusted as a substitute for expertise in production-critical embedded code.The fundamental issue with AI-generated content is the lack of trustworthiness. You cannot assume that the output is correct, safe, or aligned with best practices. As a result, using AI to insert ready-made code blocks directly into real-world projects is a highly risky and potentially dangerous practice.There is a significant risk inherent in granting an AI generator the ability to directly modify your project’s codebase. With such access, the AI could unintentionally introduce subtle regressions or break functionality, and these changes might go unnoticed until much later in the development or deployment process. This lack of transparency and control makes automated code modification a serious concern in production environments.Moreover, there have been growing concerns, backed by recent reports, that malicious actors are beginning to exploit AI code generators to distribute harmful or backdoored code. The most concerning aspect is that developers who blindly rely on such tools often don’t fully understand what the AI has produced. This lack of scrutiny can inadvertently turn them into vectors for propagating insecure or malicious code, without their knowledge or intent.Consider a common cyberattack scenario - a malicious actor shares a seemingly helpful utility online, perhaps a tool to automate a tedious task or interface with some hardware. On the surface, it works exactly as advertised, gaining the trust of the user. However, embedded within the tool is hidden functionality - it silently opens a backdoor, transmits sensitive data, or uses the victim’s machine to spread malware further.The danger lies not in the visible functionality, but in the unseen behavior and in the user's lack of ability to verify what the tool is truly doing.This scenario closely mirrors the risks associated with blindly using AI-generated code. A user with limited understanding may prompt an AI to generate a solution, copy it directly into their project, and move on unaware that the code contains unsafe operations, hardcoded credentials, insecure configurations, or even subtle logic flaws.The situation becomes even more concerning when such a generator is tightly integrated into the IDE and allowed to automatically insert or modify project code. In this case, the user may not be fully aware of the changes being made, or may overlook subtle but critical alterations. This lack of visibility and oversight significantly increases the risk of introducing bugs, security vulnerabilities, or unintended behaviors - all without the developer realizing what the AI has actually done to the codebase.Without the knowledge to audit the generated code, the user becomes vulnerable to unintended consequences - ranging from serious bugs to security breaches. Worse yet, they might unintentionally propagate flawed or even malicious code further, especially in collaborative environments.In both cases, the core issue is the same - trust is placed in something not fully understood, and the consequences can be severe.

author: tggzzz
author_rank: Super Contributor
timestamp: June 17, 2025, 10:25:06 pm
content: Radiolistener's assessment is spot onI would like to highlight one paragraph...Without the knowledge to audit the generated code,the user becomes vulnerable to unintended consequences - ranging from serious bugs to security breaches. Worse yet, they might unintentionally propagate flawed or even malicious code further, especially in collaborative environments.Beginners - and managers - won't have that knowledge, and will be very susceptible to salesmen's claims.

author: Manul
author_rank: Super Contributor
timestamp: June 18, 2025, 12:08:04 am
content: Absolutely, very good post by radiolistener. He correctly pointed out how big of a rabbit hole the subject is.I did write in reply #10 that I also consider current state AI as a no go. And I will reiterate that I'm not a proponent of AI use in coding, in case some people did not follow my posts.Touching the psychological side of the matter, I realize that it's easy for me and some other people to just write code old school way, cause we are old school. My experience started with assembly programming back in the early 90s. So what shaped me is very different from what shapes young kids of gen Z. For current day young players, AI is such a candy to grab, that they often can't resist and they have no ability (or willingness) to judge the implications. I know young people write their homework and even master thesis with AI on a massive scale. So what we are even talking here. Of course they also try to write code with AI if they can get away with it. That's a very different mindset and a shift in paradigm.

author: xrunner
author_rank: Super Contributor
timestamp: June 18, 2025, 12:30:26 am
content: I haven't tried using "AI" for coding yet for my own projects. But I was wondering if it added comments for the code it produces. Can you tell it to add comments and can you tell it how detailed you want the code explained, be it lines or functions or whatever you want.

author: JustMeHere
author_rank: Frequent Contributor
timestamp: June 18, 2025, 12:52:48 am
content: I make money on debunking AI. It's one of my new favorite things.Client: AI said we should do this....Me: The very first answer in regular Google give the correct and different answer.I bill 2 hour minimums.

author: radiolistener
author_rank: Super Contributor
timestamp: June 18, 2025, 04:32:10 am
content: Quote from: xrunner on June 18, 2025, 12:30:26 amYes, it adds comments, but the problem is that it uses the same language in which you ask it to write code.The most effective way to enforce English comments is to ask it to write comments using only ASCII characters.Unfortunately, it doesn't remember this setting, even if you add the requirement to memory - so you have to repeat the request every time. This is very annoying.

author: xrunner
author_rank: Super Contributor
timestamp: June 18, 2025, 11:03:33 am
content: Quote from: radiolistener on June 18, 2025, 04:32:10 amUh OK that's interesting.I gotta try that and see what it looks like.

author: tggzzz
author_rank: Super Contributor
timestamp: June 18, 2025, 11:18:17 am
content: Quote from: xrunner on June 18, 2025, 12:30:26 amGiven the "statistical parrot" nature of LLMs, I would expect any such comments to be similar to the comments that provoked the Agile/XP dogma that comments should be removed

author: Psi
author_rank: Super Contributor
timestamp: June 18, 2025, 11:45:23 am
content: I don't think we have yet seen the true benefit of AI/LLM for programmers.We're probably going to see another even higher level language come into existence. Not AI/LLMs tacked on to current IDE's an entire new interface using AI/LLM at its core. The human will be writing/debugging the code, not the AI/LLM.Currently we have AI/LLMs converting English statements into code which is terrible.English is no where near precise enough to write code. The AI/LLM takes over, and predicts, way to much of the process with obviously bad results.The new higher level language/IDE I'm suggesting would allow programmers to tell the AI to write code but in a way that is very well defined and restrained so that the programmer knows exactly what code he will get with each statement he gives the AI/LLM. It simply makes it much faster to express the code you want and with less silly mistakes.I suspect it will be a new "spoken" language for expressing coding concepts, but could still be text based.If you abstracting things down enough speech should be way faster than typing, even with code completion

author: jpanhalt
author_rank: Super Contributor
timestamp: June 18, 2025, 12:24:44 pm
content: Re: English is no where near precise enough to write codeI am not into HLL, but in Assembly, the mnemonics used by Microchip are easily and precisely translated into English, e.g., movlw = move literal in operand to WREG. That situation is similar to what I have seen of other Assembly languages.

author: jkushuee
author_rank: Newbie
timestamp: June 18, 2025, 12:48:05 pm
content: Quote from: radiolistener on June 17, 2025, 07:23:38 pm1. I understand you don't make purchase decisions. What IDE are you currently on (paid like IAR or Keil or free ones such as Eclipse)? Cursor has two pricing tiers pro (usd20/m)and enterprise (usd40/m). They also have close to 40k enterprises using cursor. Generally, developers/EMs recommend these kind of tool adoptions. I'm also thinking of a similar GTM.2. I get your point about the specific IDE. What would be your assessment of IDE distribution in embedded world - something like 50% Eclipse + 30% VScode + 10% vim + 10% others? Cursor is a vscode fork. I am doing similar. Eclipse is just so clunky (albeit with better dev support). IDE gives me better control over user experience hence going with that strategy.

author: paulca
author_rank: Super Contributor
timestamp: June 18, 2025, 01:32:45 pm
content: I don't have professional embedded experience, but speaking generally...Can AI (specifically LLMs like ChatGPT) be used as a tool by developers to make them more productive?Yes.Does that involve getting the AI to generate your project/code/documentation for you?No.Consider it for what it really is.... a brilliant "google search summariser". In the old model you googled, and vent through individual discrete forum posts and stack overflow rejecting them one by one until you find a few short lists to explore. Correctly prompted AI will do that for you today.Putting it against the forum or reddit model. Old model you post a question and 1% of the forum/site respond. A small, though focused snapshot in time. If you search reddit and research manually you will find your question has been asked in a variety of different ways in the past and collectively all the replies together form a kind of "knowledge base". In the old model you had to do all of that "reduction in context and to your level" manually with not just research skills, but also the rock breaking effort of it.In the new model, instead of posting to a forum, you put the same content to an AI. It will effectively "back play" your query through the past of all of the relevant forums, it will reduce it, summarise it, pivot it into your context and pitch it to you "at your calculated level" in a friendly hard to hate kind of way.Taking that for what it is, a reflection from an imperfect knowledge base, it's output is often full of the same mistakes repeatedly posted in the source material. Incorrect associating "problem descriptions" with "solution descriptions" can even cause they to GIVE you common bugs.If you just accepted every "auto complete" and "inteli-sense" suggestion when coding you would write garbage. The same applies to the new tools. The best work will be done by the best combination of the two. The best skilled engineer with the best skills with the tools.

author: paulca
author_rank: Super Contributor
timestamp: June 18, 2025, 02:16:09 pm
content: In hobby space using ChatGPT to aid embedded development I have noticed a bizarre but understandable 'feature'.Those who have spent years on forums like this one, or like Reddit know that from time to time threads pop up which go back and forth, back and forth for more information, try this, try that until the OP has to expand the information and the complexity of the question so far that .... most people give up, it now looks like it's a good job it's "not their problem".These are then ingested by AI LLMs and used to "help" with other developers querying later.The net result is, you will find yourself, guided by AI, around and around the same loops. You quickly spot that after trying A, B, C, and D it still fails, it reverts back to A again. You know you have hit the limits of this prompting track and need to tear down teh context and try and different tact, or accept that it doesn't know or cannot coherently summarise the chaos in the material it was trained on for that topic..

author: JustMeHere
author_rank: Frequent Contributor
timestamp: June 19, 2025, 06:46:25 am
content: Quote from: paulca on June 18, 2025, 01:32:45 pmBut it's wrong almost every time.

author: Psi
author_rank: Super Contributor
timestamp: June 19, 2025, 06:58:34 am
content: Yeah, I think they way it will go is AI/LLM will become like code completion but on steroids.There will of course be advancements in the future as AI/LLMs get better and are able to take over more aspects of coding without causing problems.But it's going to have a human at the center for the foreseeable future.One thing we will probably see though, is really basic coding being done entirely by AI in some settings.Like for example home automation control. Where a normal user, who doesnt know about coding, can ask their AI assistant to do things in English and the AI assistant will convert that into some common command/config format for doing tasks.That format might be a blur between a config file and code. Sort of like ESPHome JSON configs, if you're familiar with them.AI/LLM should be smart enough and reliable enough to have control over configs/code for general home automation tasks.Turning an English explanation from the user for what they want into 'If This Then That' configs, maybe a little code if needed.

author: Psi
author_rank: Super Contributor
timestamp: June 19, 2025, 07:02:14 am
content: Quote from: JustMeHere on June 19, 2025, 06:46:25 amIt's wrong for general search stuff sometimes because it's been trained on inconsistent data. Us humans cannot all agree on the truth of things so it doesnt have a hope of being error free when it's trained on all human text, right and wrong.If you train it on something specific, especially something math related where you can pre-screen training data to make sure its correct then its outputs are really good.

author: jkushuee
author_rank: Newbie
timestamp: June 19, 2025, 07:39:22 am
content: Quote from: Psi on June 19, 2025, 06:58:34 am\This makes sense. A smart engineer would know the difference between using ai and completely depending on ai. Of course the engineer needs to understand where to use it for code completion and what scenarios you could use it for boilerplate definitions and in what scenarios a whole module could be coded just by ai but may be 10X faster.Think of an IDE that supports uploading data sheets application notes, Gerber, Schematics and then is able to generate and edit code just like cursor but with all the hardware context.It's also able to write drivers right application layers network protocols as well as as well as answer basic questions about about the schematics and the data sheets such as features implementation guide or coding from the register map to bare-bone C etcCurious how much will you pay per month for an embedded IDE that support native AI if these features became part of the IDE such as Cursor (or another VSCode fork)?

author: Psi
author_rank: Super Contributor
timestamp: June 19, 2025, 07:57:35 am
content: Quote from: jkushuee on June 19, 2025, 07:39:22 amI wouldn't worry too much about having to pay a monthly fee for the cloud LLM service in your IDE.You can run AI/LLMs locally with good hardware and it doesnt have to break the bank, you don't need an RTX 5090.The primary reason people tend to buy really expensive graphics cards for AI is because they have more RAM and can load bigger models.RAM isn't that expensive. Reasonably priced graphics cards would work fine for a single users AI needs if they had more RAM.NVidia has little motivation to give the cheap cards more RAM as it would reduce sales of expensive cards. We'll have to wait for NVidia to get more competition in the AI accelerator space.But AI acceleration will likely get included in every CPU/GPU in the future. So running local LLMs should be totally fine for programming IDEs

author: paulca
author_rank: Super Contributor
timestamp: June 19, 2025, 08:46:07 am
content: Quote from: Psi on June 19, 2025, 06:58:34 amMy brother is on a waiting list for cataract surgery. He can't see a damn thing right now. He is "IT Literate" but hasn't coded since high school out side of some mickey mouse arduino LED sketches.He used his terminal based AI he pays £15 a month for to create him a grafana dashboard with the three or four "gadgets" he bought.Remember, he can't see, he can barely read and his font size on the monitor is about 3 inches high!Somehow that AI got him to a working and... honestly, not that bad a grafana dashboard.

author: paulca
author_rank: Super Contributor
timestamp: June 19, 2025, 08:53:33 am
content: Quote from: JustMeHere on June 19, 2025, 06:46:25 amShort snappy quirps like that require evidence.I haven't see a single thing from you that suggests you have even used an AI before. Honestly.Give it 10 "everyday" questions and prove to us that it's wrong for all of them. Come on... Lets see your wizardry at confusing the bot.EDIT: To make it easier for you, you can even pick things you can empircally test."EG: ChatGPT Im being lazy. Here is verilog of some 12 different gates, can you reforumulate these into 74HC series quad nand gates?"

author: Siwastaja
author_rank: Super Contributor
timestamp: June 19, 2025, 08:54:17 am
content: Quote from: Manul on June 17, 2025, 08:54:19 pmI can totally see where this is going, and agree that AI is perfect fit hereSo we have initialization, say, turning a pin into output, which means writing a bit into a register, 1 LoC. Because someone thought this is too easy, they added a wrapper which makes it 20 LoC which no one can remember how to write. Worry not - they added a code generator. Then they added a pointy-clicky to drive that code generator. And the job still isn't done. Now we need to add AI to drive that.QuoteNope. I have worked extensively with the flagship ARM MCUs and completely disagree. There is nothing really involved or special, and it works just the same way. Of course, if your application is complex enough to need 20 peripherals instead of 2, then it's 10x the work. Some of the peripherals are more complex - for example CAN peripheral needs more config than SPI peripheral, but that is because you are setting up filters - and that isexactlyall about system design. Once you get the system design right, these "difficult" init things are a few lines of code, each.Unless, of course, you wrap it with layers of unnecessary complications, generated by unnecessary code generators, those then driven by AI.You may think there is a lot of "boilerplate" which can be automated, but that is only because you chose to use this unnecessary boilerplate. I never did, and thus see the matter completely differently. We can keep adding layers of extra work on the top of existing ones, or we can peel off unnecessary crap, our choice.Things like peripheral initialization are a small part of the codebase, but also a part where everything has to go exactly correct, in the way your design needs it, and taking into account all pecularities and silicon bugs of the peripherals. These are things that are completely undocumented, not even in errata, and rarely discussed even on forums. So totally not in any AI training material.But for a project which is fundamentally very simple (say led blinker, hello world) and only made complex by unnecessary boilerplate layers, then sure it will be a breeze for AI to reduce the workload by repeating the boilerplate; and it's more effective than copy-paste as it can "think" how to modify the common example it has learned.

author: paulca
author_rank: Super Contributor
timestamp: June 19, 2025, 09:15:20 am
content: An interesting element of using a "natural language" frontend LLM like a chat bot is that it's NOT a teacher, mentor or even a peer.This has massive advantages, but some of those are massive disadvantages if you are not aware of them.You: Can we use an 74hc595 as a bi-directional latch?Peer/Mentor/Boss: Probably, maybe, but dumb, just dumb.AI: Absolutely, lets jump down that rabbit together, hang on tight.YOU LEAD! IT FOLLOWS!It will not stop you and say, "Maybe, but why on earth would you want to try?", instead it will do it's damnest to find you are coherent answer.I got it similarly confused when I as actually asking it about a bi-directional latch. There isn't a 74 series bidirectional parallel latch. Doesn't exist. There are latches and there are bidirectional transceivers but there are not bidirectional latches.This would tell your "peer" I have left the beaten track and am headed down the wrong road. If he likes you, he will stop you, repoint you and maybe give you some grief.An LLM like ChatGPT will not. It will let you lead and it will follow you down the same rabbit hole 100 times and not get bored, annoyed or chastise you.So, if you want wrong answers, they are very easy to induce. The further you lead it from the main concensus the less and less coherent the material and the less and less coherent the answers.This makes it a great risk when the bot is used by unskilled and untrained hands. In hobby land it just leads to frustration. Ask the wrong question, get the wrong answer. In professional land it usually catches juniors who used an AI for their interview out.

author: radiolistener
author_rank: Super Contributor
timestamp: June 19, 2025, 09:23:24 am
content: What I think about the current state of AI strongly resembles the dot-com bubble era. Back then, inflated expectations and aggressive investments led to unsustainable growth, resulting in a dramatic market collapse when reality caught up. Similarly, today we're witnessing a surge of hype, speculative funding, and exaggerated promises around AI technologies. While AI undoubtedly holds real potential, much of the current enthusiasm seems disconnected from practical constraints and long-term sustainability. And will end the same...

author: Psi
author_rank: Super Contributor
timestamp: June 19, 2025, 09:27:46 am
content: Quote from: paulca on June 19, 2025, 09:15:20 amYeah, but that isnt really an LLM issue, it's a chatGPT issue, they trained it into that state of being super helpful instead of critical.You might get a better result if you add "pretend to be a professional no-nonsense engineer. Don't suggest anything that might work but is stupid"

author: brucehoult
author_rank: Super Contributor
timestamp: June 19, 2025, 09:36:48 am
content: The 74HC595 is a serial-in, parallel-out shift register with an 8-bit storage register, commonly used to expand output ports. However, it is not designed to function as a bidirectional latch, as its primary role is to shift data in one direction (serial input to parallel output) and latch it for output. Here's a breakdown:- Unidirectional Nature: The 74HC595 takes serial data in (DS pin), shifts it through an 8-bit shift register, and latches it to the output pins (QA-QH) when the latch pin (ST_CP) is triggered. It lacks input capability on the output pins, so it cannot inherently read or latch data bidirectionally.- Bidirectional Latch Requirements: A bidirectional latch would need to both output data to its pins and read/input data from those same pins, typically requiring additional circuitry like tristate buffers or a different IC design with bidirectional I/O capabilities.- Workaround for Bidirectional Use:- You could pair the 74HC595 with a complementary input device, like a 74HC165 (parallel-in, serial-out shift register), to handle input operations. The 74HC165 can read parallel inputs and shift them out serially, effectively allowing you to simulate bidirectional functionality with two chips.- Use external tristate buffers or multiplexers to switch the pins between input and output modes, controlled by a microcontroller or additional logic.- Limitations: The 74HC595’s outputs are strictly push-pull (not tristate), so direct bidirectional use on the same pins isn’t possible without additional circuitry. Also, managing input and output states would require careful timing and control signals.Conclusion: The 74HC595 alone cannot function as a bidirectional latch due to its unidirectional design. To achieve bidirectional latching, you’d need additional components like a 74HC165 or tristate buffers, or you could consider a different IC with native bidirectional capabilities, such as a microcontroller with configurable I/O pins or a specialized bidirectional latch IC like the 74HC245 (octal bus transceiver). If you’re set on using the 74HC595, combining it with a 74HC165 is a common and straightforward approach.----That's Grok.Seems not unreasonable to me. Maybe it doesn't discourage the idea in quite strong enough terms, but the first three paragraphs make it pretty clear for those who want to listen.The only thing to really argue with is that the 74HC245 has no latching functionality. And the closing "common and straightforward" which should read "lunatic, if you insist".Well, and that the 595/165 have serial on one side and parallel on the other, which indeed might be want you want sometimes, but is not the first thing that would come to mind from the words "bi-directional latch".The microcontroller is actually a good idea.So, I expect, would be a pair of 74HC373, with careful management of ~LE and OE on each. Depending on what you're trying to do, they *could* both be OE at the same time as they're driving different buses, but you'd need to manage one one wrt whatever else is on each bus, and it would be relatively pointless to LE one of them while the other was the OE device on its bus as that would just be feeding the same value back to the original bus.

author: paulca
author_rank: Super Contributor
timestamp: June 19, 2025, 10:02:11 am
content: Quote from: Siwastaja on June 19, 2025, 08:54:17 amWhat about refactoring STM32 code?What about this, say:"My 16 bit address bus is spanned across the following GPIO pins.<insert table>My signals are on these GPIOs<insert ODEC(sp?) RAM signals and GPIO ids>Can you write me functions to:Acquire signals - untristate for input/controlSet the Address BusRelease signals - tristate relevant signals"It did this. Including all the register shifting to create single register level function to do as above.It then asked me for my databus mapping and if I wanted tristate GPIO drivers for it too.Did the code work perfectly first time? Not quite. There were one or two copy pasta bugs, such as "notting" the first part of a register bit set but also noting the setting part incorrectly. However, overall it did actually work. So did it's databus handler.One slight annoyance was it forgot I mentioned I wanted my bus lines to be "as atomic as possible". So I asked it to rework it. It did. Moving the switching to "output" to after the registers were fully set. So my address bus stabilised in a couple of steps, one per port instead of one or two bits at a time.At that point in the dev cycle, I have a working, two click build, deploy, test with a logic analyser. Anything it gives me I can immediately empirically test.The code was a mess. GPIO and memory IC logic strewn together in a birds nest. I figured it would not work, but I asked it..."Can you refactor that C file into two layers. Layer one shall have no low level MCU dependancies and should be portable. Layer two should contain the rest."It basically answered, "Got it... thinking.... here you go."It even switches to a mini IDE to present multiple files. You can review them. You can back and forth highlight and code review with it. You can do whatever you like and it will respond to it, if you want.I wanted to "hard test" it, so I copy and pasted them directly, after taking a git branch.... "ai_refactor".I'm not lying ... it worked first time. Not even a compilation error.The code it produced was NOT copy and pasted. It still obeyed many of my "odd nomenclatures", it still obeyed my multiple useless steps which it had mentioned aren't really required, but didn't remove them, because I didn't ask it to. So there are no examples of this code and I would doubt an anti-plagerism test would find a significant signal in it. This goes to my other point that it will follow you down the rabbit hole. If I had let it right back at the start it would have given me the most prominent example from the internet or github that is tried and tested, or just pointed me directly to that github. This is where the professional should "get off the ride". The code probably won't work, probably not quite the right MCU or whatever, but it will get the professional what he needs, "a steer, shove, a seed". The hobbiest who wants to go the painful way down the rabbit holes and back up is where that "follow" becomes both useful and dangerous. It can allow professionals to describe very complex problems which are hard to articulate and find the structure in it with the AI, where a peer might get lost.I had "post conditional" function calls in my Read/Write handlers which "ReleaseBus" on both address and databus, ensuring that both were always HighZ when I left the routine. It pointed out they were not required in most cases.The AI left all that in and played along with it. Nobody else on the Internet is going to do that for you, no matter how patient.

author: paulca
author_rank: Super Contributor
timestamp: June 19, 2025, 10:18:27 am
content: Quote from: Psi on June 19, 2025, 09:27:46 amBut I like the rabbit holes and I enjoy the ride.EDIT: Honestly I think if I had started with it, with this Z80 project, the way you suggest it would have asked, "Why bother?"It might then have steered me, given me already having a working verilog/fpga learning environment to "Just soft core it. You'll learn as much, learn verilog and not have to fiddle with 1970s hardware!"

author: paulca
author_rank: Super Contributor
timestamp: June 19, 2025, 10:21:29 am
content: Quote from: brucehoult on June 19, 2025, 09:36:48 amYea its responses, in context of the bidirectional latch morphed into using the 244/245s, which are bidirectional transceivers. I might have them mixed up again. I look at about 5 different sources, one of them being my stock pile and then work from there. The 244/245s don't latch, so wont solve a slow consumer, fast producer bus problem.I don't need it anyway unless I want to push the clock higher, the peripheral has plenty of time. I did that analyse myself in the datasheets, but I could have asked it to.What started it all was I had a lovely neat schematic that was "Write only" to the LCD. It was the bot that then reminded me I need to read the busy flag. Hence, "Can I use a bidirectional 74 series latch?" rabbit hole. Blind leading the blind from that point.And a latch is really just a set of flip flops "clocked" with the enable line, no? I was just trying to avoid having two of them, those or the actual standard latches I use elsewhere for LED displays.On proving what it gives me works, if it's breadboardable and I can be bothered I BB it. Usually however I go to verilog first and bluntly and ignorantly recreate (or borrow) 74HC logic modules. When I want to test timing, I put "torture clocks" inside the components so they don't and can't respond or act immedaitely. Then retest. I can swap chips a lot faster and roll new ideas faster. THen I can give the output to the bot and ask it to convert to discretes.... which given most things are called 74HCxxx anyway it's fairly obvious, but it does pick up the ANDs, OR, NOTs required, and simplify things like "~pin -> pin -> ~pin) and not give me 2 not gates for example.

author: Tation
author_rank: Regular Contributor
timestamp: June 19, 2025, 10:32:54 am
content: Quote from: JustMeHere on June 19, 2025, 06:46:25 amIn my experience, it is wrong sometimes, as happens with colleagues, forum people, etc. But, usually, it is easier to detect it is wrong. Definitely not writing my code, but a useful aid.

author: radiolistener
author_rank: Super Contributor
timestamp: June 19, 2025, 11:20:14 am
content: Quote from: paulca on June 19, 2025, 10:02:11 amYou will likely be disappointed with what AI produces when asked to refactor your STM32 code, not because you don’t want improvements, but because it often introduces subtle bugs and issues that are hard to spot.

author: Psi
author_rank: Super Contributor
timestamp: June 19, 2025, 11:20:37 am
content: Treat it like a person, not a calculator.It's backwards to how we are used to using technology.If a calculator is sometimes wrong it's trash and you throw it in the bin. It's either 100% right or useless.If a person is sometimes wrong you consider what they say and just use your judgement.

author: radiolistener
author_rank: Super Contributor
timestamp: June 19, 2025, 11:28:02 am
content: Quote from: paulca on June 19, 2025, 10:02:11 amFrom my experience, in many cases, the generated code will contain subtle errors that aren't immediately apparent. To catch them, you'll need to review the code line by line and step through it in the debugger. This process often takes as much time, if not more than writing the same code manually from scratch.Sometimes it makes mistakes so illogical and absurd that even a person with minimal understanding would be unlikely to make them.Once, I asked it to implement a well-known DSP algorithm. It produced code that compiled and generated seemingly plausible results, but upon closer inspection, it turned out to be complete nonsense and did not fulfill the actual purpose of the algorithm.

author: paulca
author_rank: Super Contributor
timestamp: June 19, 2025, 11:29:26 am
content: Quote from: radiolistener on June 19, 2025, 11:20:14 amYou know where that comes from don't you, forums like here.In fact, if you push it on things and it gets the impression it is out of date, or if you tell it is out of date and to recheck, it will now web-search.Guess where it searches. Here, embed forum, stm forums, etc.One thing I would like it to do more readily is produce "sources" and "credits". So if it does lift a sizeable chunk of heavily reference code from SiliconWizard or similar it would nice if it gave some credit. I would also include it in any code I published to retain the credit.It doesn't really do that though. If you push it it will produce "a source" or two. But it an't give you an accurate tree of sources for it's output. You might have to drill down on a point by point basis to get "non-reductive sources".EDIT: It did give me a quite specific answer one day and I didn't trust it, so I asked it for a reference.It gave me the line of code in github ... smug bastard.

author: radiolistener
author_rank: Super Contributor
timestamp: June 19, 2025, 11:33:59 am
content: Quote from: Psi on June 19, 2025, 11:20:37 amThat approach often doesn’t work in practice. If it fails to produce a correct result initially, there's a high chance that even after carefully breaking the problem down and explaining every detail, it still won’t be able to generate a reliable, working solution. This is because when it fails to solve a problem, it often indicates that the task exceeds a minimal level of complexity at which point the AI’s effectiveness tends to drop sharply, approaching zero for problems of that difficulty.That doesn't work with AI, even if you provide working code and ask it to fix a minor issue, there's a high risk it will break the rest of the functionality in the process.This is a key difference from a human: a person usually needs only a hint or a brief correction to understand the mistake and adjust accordingly, often producing the correct solution with minimal guidance.

author: radiolistener
author_rank: Super Contributor
timestamp: June 19, 2025, 11:42:27 am
content: Quote from: paulca on June 19, 2025, 11:29:26 amI don't know exactly, but as I asked chat-gpt, it answer that he don't search, it generate:Quote

author: tggzzz
author_rank: Super Contributor
timestamp: June 19, 2025, 12:12:29 pm
content: What happens if you ask an LLM to generate code for something that issubtlyimpractical or impossible? I'll bet it doesn't state that it is impossible/impractical, and does still return something which will have more or less subtle failures.What kind of thing? Perhaps something thatimpliesthe Dining Philosophers or Byzantine Generals problems don't exist or have been solved. Or unit tests to demonstrate a system has ACID properties. Or running .NET code on an 8-bit processor. Or demonstrating that two interacting FSMs are deadlock/livelock free.

author: paulca
author_rank: Super Contributor
timestamp: June 19, 2025, 01:04:42 pm
content: Quote from: tggzzz on June 19, 2025, 12:12:29 pmThe problem is real. They don't know what they don't know. So they will, the ones in my experience, answer and make a complete and utter hash of it. Yet they will be confident. Even when they change their answer repeatedly, they are confident in all of them.An example that they simply can't do is "find signal in noise", not in the "Public Chat bot" form anyway. An example, which I meantion in another thread, might be to give it a randomised bit of text containing pipe characters. Then ask them to count the characters.They cannot "search it" as it's too novel. It's noise. 0 real matches.It will answer and it will be incorrect (in my experience), but it does not know it's incorrect.In my opinion this needs fixed. It needs to be a little more aware and be more willing to "shy" away from things it "knows" or has been "trained" it will get wrong.I named this effect, "The Dougles" after Dougle from Father Ted series. The AI will struggle to identify the concept of "Small" versus "Far away" and given a picture of a cow would be as confused as Dougle was about the same size but different reasoning. Hypothesis: If you ask for pictures of small cows far away, do we expect it to also give us photos of toy cows?

author: tggzzz
author_rank: Super Contributor
timestamp: June 19, 2025, 01:54:30 pm
content: Quote from: paulca on June 19, 2025, 01:04:42 pmYup, and fusion also needs to be fixed so that the reactions last longerIt is in the LLMmanufacturer'strainer's financial interest for LLMs to be (excessively) assertive and (obsequiously) polite when the errors are pointed out.

author: paulca
author_rank: Super Contributor
timestamp: June 19, 2025, 05:00:58 pm
content: An accident led to a bizarre and rather funny discovery. (I found it funny, made me literally LOL).My breadboard Z80 running with no clock connected on the board, aka on a floating clock pin, at 50Hz only when I brought the magnifier lens with it's fluorescent lamp close.I knew the root cause, but I thought I would try and experiment and capture it in a way that won't spam, but allow you to view if you wish.Initially I knew the root cause, so my prompt is leading and vague to see how it does.Then I assert my analysis for it's expansion.Then I expand more on it. For fun, insight, expanding my own scope and learning.... for fun.Is it lying to me?I think I spot a few "Wha?" items, but in context of the vocabulary and "level" of my questions, I think it's pretty spot on.I would highlight that it, at least initially gives "How to verify" summaries, which if you are actually confused might help you solve it. You don't need to trust it.Right or wrong, this is how I use GPT to learn. Used this way it's biggest risk is "Confirmation bias". It is very much (as ChatGPT is trained to be) Mirror, mirror on the wall, is my idea the greatest of them all? ChatGPT: Yes, yes, it is. Lets break it down.(You get to see my recent chat history, it chooses the titles, but sure.)https://www.youtube.com/shorts/zyfLaNVOhnQ

author: JustMeHere
author_rank: Frequent Contributor
timestamp: June 19, 2025, 05:14:17 pm
content: Quote from: Tation on June 19, 2025, 10:32:54 amI got examples where it was egregiously wrong. The first one, the character's name is Philo and he did throw the fight (AI got this right the last time I checked)The next two are me removing the word air handler in the second search.

author: jamesucf
author_rank: Newbie
timestamp: June 20, 2025, 03:39:29 am
content: Interesting question! I’m also curious to see if anyone has successfully used AI for this.From what I understand, AI is quite good at generating code for common tasks—like building websites, handling data input/output, text processing, and similar operations. Why is that? Mainly because these tasks are widely documented, and there’s a vast amount of open-source code available online. AI models are trained on large datasets and rely on having seen similar examples before to make accurate predictions. So, if your task is common, the AI has likely "seen" it before and can generate helpful code. Otherwise, it may hallucinate or produce unreliable results.When it comes to embedded software, the situation is different. These systems are tightly linked to specific hardware, and open-source projects for many embedded platforms are limited. If you're working with new or uncommon hardware, AI might struggle due to the lack of training data.So training data is the key.

author: Nominal Animal
author_rank: Super Contributor
timestamp: June 20, 2025, 08:11:31 am
content: Kosmyna, N et al.Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task(preprint at arxiv.org) investigates the cognitive costs of using AI. Specifically, that when one uses AI to help write an essay, it negatively impacts how much the writer learned/understood of the subject themselves.I do not know how well that maps to software development, but I personally write a lot of code to understand a problem, solution, or algorithm; sometimes just for fun, but always when designing software (to help decide which parts/modules I want to base the software on).If I started using AI/LLM for this, according to the above MIT study preprint, I would understand/learn less.I suspect that this would apply to most other software developers also. I do not like the idea of developers understanding even less of the code they write than they do today.

author: paulca
author_rank: Super Contributor
timestamp: June 20, 2025, 08:17:43 am
content: Quote from: Nominal Animal on June 20, 2025, 08:11:31 amMaybe you could try rather than post without any relevant information.You talk about how much you learn from writing a letter about the topic, but yet you make forum posts about a topic which you can freely experience, yet you haven't.In 1986 you could go to a newsagents and buy a copy of a ZXSpectrum weekly and in it you would find program listings. You typed them in, spent hours doing it. 1000 lines of BASIC with a 2Kb block of HEX to enter for the ASM portion. What did you learn typing in someone elses program?How is this different to asking an AI for example today?New tech, old patterns.Beside. If you expect to simply ask it to write your entire code, correctly in one shot, you are probably in for a shock. To create your perfect code you will need to give it so much information, you might have been better off writing it yourself. Instead you use it for parts, examples, and look for help with complex bits, for a second set of "eyes" on problems, code reviews etc.A tool not a fully automated production system.It exists without entropy and without free forming thought. If you want creativity, YOU bring it.

author: brucehoult
author_rank: Super Contributor
timestamp: June 20, 2025, 11:17:52 am
content: Quote from: paulca on June 20, 2025, 08:17:43 amI was never in Clive's army, but as a high school kid in a remote place in 1980 with possibly no one else who knew anything about it within 100 miles, I learned A LOT from the VERY terse 6502 reference material (nothing tutorial at all) in the back of the Apple ][ manual, and Woz's commented assembly language ROM source code (listing, so the hex codes were there too). In fact I learned EVERYTHING from it that started me on my way to a career programming, and I was able to write some very useful things in machine code (I didn't have an assembler), such as something that printed a text file (preloaded into RAM) to the very slow Seikosha GP-80 printer while you did something else on the computer (as long as it called RDCHAR via the zero page vector from time to time). Such as something to compact BASIC strings and string arrays in linear time (less than a second) instead of the quadratic time (up to a minute or two) of the built in code in ROM.In either case, whether the reader gets something out of reading other people's code depends largely on the reader, and even more on whether they do actually read it.The NEED to read other people's code in order to learn has been observed many times, perhaps most famously for example by Peter Norvig "Teach Yourself Programming in Ten Years", but I think Fred Brookes, Alan Perlis, Eric Raymond and others expressed the idea earlier. Probably Wirth too.You don't have the time (for sure) or the brains (very probably) to invent by yourself everything that the greats have invented over the last 75 years.But, yes, of course just being a copy-typist teaches little.

author: Nominal Animal
author_rank: Super Contributor
timestamp: June 20, 2025, 11:48:53 am
content: Quote from: paulca on June 20, 2025, 08:17:43 amThe preprint is about actual research done at MIT, using EEG to measure brain activity when doing a cognitive-creative task (essay writing) with LLM aid. While it isn't exactly software development, and I did explicitly say that itisarguable how the task of writing an essay on a topic for school compares to software development, I pointed out how I believe it applies to myself.Just because I write "If I started to use LLM for this", does not mean I've never tried using LLMs as a coding aid. It means simply that I do not use LLMs when examining a problem/solution/algorithm, and the preprint gives a good reason why one might not want to.Are you sure you're not just pissed off because research indicates using LLMs for cognitive work may have significant downsides? If so, don't blame me. I didn't make that happen.

author: xrunner
author_rank: Super Contributor
timestamp: June 20, 2025, 12:04:59 pm
content: Quote from: paulca on June 20, 2025, 08:17:43 amI used to have a TRS-80 back in those days which, if some people do not know, had BASIC. That's the language you used to get your computer to do anything.I subscribed to a magazine, I think it was 80 Micro, which had programs you could type in, games and so forth. I used to sit down and type in those programs page by page to get something new to try on the TRS-80.I can tell you without hesitation that almost every program either had bugs or typos which caused the program to not run correctly. Even if they didn't I could see improvements in the programs I wanted to try and I would learn by adding things to them. Debugging those programs taught me so much about coding back them I am glad I had that experience today.

author: Nominal Animal
author_rank: Super Contributor
timestamp: June 20, 2025, 12:15:50 pm
content: Quote from: paulca on June 20, 2025, 08:17:43 amNothing, of course. That is why I've stated before that I consider using LLMs as a coding aid no different to copy-pasting code from StackOverflow.When writing creative text or articles or books, that sort of thing is calledplagiarism.When done to software projects, it can lead to some serious copyright issues. Well, already has, although we only hear from the rare publicly-raised cases.Current code-assisting LLMs have been trained on codebases using various open source licenses, but almost none of it is in Public Domain. According tothis paper from 2024,"even top-performing LLMs produce a non-negligible proportion (0.88% to 2.01%) of code strikingly similar to existing open-source implementations. Notably, most LLMs fail to provide accurate license information, particularly for code under copyleft licenses."For now, the LLM companies are claiming that if they were required to follow copyright laws like everybody else, the entire business model would be ruined. Pity the sports streaming pirates don't get to make the same defense.There is a reason why Microsoft and Alphabet/Google do not use theirownproprietary code bases for training their LLMs.When my next-door friend got a Commodore 64 in the eighties, we did type in some code from a Finnish magazine (MikroBITTI), and definitely didn't learn anything while doing that. Fortunately, the C64 came with proper manuals, and we read those, and quickly started writing our own BASIC programs.I do think I learned some things by dissecting the few BASIC-only programs, although those were much simpler than the ones with significant hex/machine code sections.Quote from: paulca on June 20, 2025, 08:17:43 amSure: it is all about how you use it. My previous post pointed out one negative case, that's all.For example, it would be nice to have code LLMs that were copyright-aware, for example different models for different target licenses. For example, a model that is intended to be used when one writes GPL 3-licensed code, can use GPL-, Apache-, MIT-, and BSD-licensed code. The license subsumption matrix is a bit complex due to the number of license variants, but it is well known and generally accepted as valid.

author: brucehoult
author_rank: Super Contributor
timestamp: June 20, 2025, 01:10:05 pm
content: Quote from: xrunner on June 20, 2025, 12:04:59 pmNah. Even at 17 yers old in 1980 I got bored with BASIC in two days and said "What's this 6502 thing?" and from then on BASIC was only used to load and call machine code.

author: tggzzz
author_rank: Super Contributor
timestamp: June 20, 2025, 01:35:53 pm
content: Quote from: brucehoult on June 20, 2025, 01:10:05 pmBasic? Luxury! I started out with 128bytes of RAM and switches.Actually, that's not strictly true. I started with Algol-60, and still remember the light bulb going on when I realised what the compiler was doing. Subsequently, my first assembler program enabled me to triumphantly re-invent the concept of an FSM.

author: Siwastaja
author_rank: Super Contributor
timestamp: June 20, 2025, 02:08:47 pm
content: Quote from: Nominal Animal on June 20, 2025, 12:15:50 pmAnd there we have it - LLM coding is just the good oldStack Overflow Copypaste Codingon steroids.And itisa very usable pattern, when:* The task is relatively simple (i.e. appears on Stack Overflow / AI training dataset),* But it is not simplefor you, because the task is outside of your usual expertise / comfort zone, and* Your primary intention is not to learn to solve similar problems, but only to get the job done quickly this timeFor example, 15-10 years ago I was much crappier in bash scripting and POSIX C interfaces than I am today, and used Stack Overflow Copypasting to just get the bare minimum to keep my main things going (e.g., microcontoller bare metal C). I have intentionally stopped trying to mindlessly solve these issues and try to exercise my brain a bit more, and as a result, do much better now on those new-to-me subjects.But regular expressions I still struggle with. I'm certain that AI would increase my productivity on those, but I guess I'll pass. I'll try to learn instead and solve the problems myself.

author: paulca
author_rank: Super Contributor
timestamp: June 20, 2025, 02:37:23 pm
content: Here's a rather annoying thing. People on github and other places are rebelling against AI by renaming their repos, closing them entirely and moving to their own forks etc.Literally half the github link gpt gives you are dead - 404.

author: Nominal Animal
author_rank: Super Contributor
timestamp: June 20, 2025, 04:29:52 pm
content: Or maybe they just don't like their work being copied wholesale without any respect to the license?The "Free" in free software does not mean "zero cost". The cost of free software is measured otherwise, by contributions in copyleft licenses, and attribution in BSD- and MIT-style licenses. Copying free software without respecting the license is just as much theft and piracy as illegally downloading games, movies or TV shows is.

author: julian1
author_rank: Frequent Contributor
timestamp: June 20, 2025, 08:59:30 pm
content: Quote from: Nominal Animal on June 20, 2025, 04:29:52 pmOne can imagine Google execs a few years ago - sitting in a round-table discussing it in a kind of Dilbert like scenario -We developed this technology that can summarize, and interpolate between different text sources in a quite sophisticated way.How can we monetarize it without infringing on copyright, or upsetting traditional/social media publishers, who keep getting their governments to intervene on their behalf with protective legislation?I know. We'll call it AI. And attribute the output to some intrinic factor or process of the technology.That way, people will think we're the ones doing the work and sidestep the IP rights issue.For the software side, we already know the majority of programmers will just go along with anything that makes their life easier, so likely no probelm for adoption there.

author: LinuxHata
author_rank: Frequent Contributor
timestamp: June 21, 2025, 05:27:32 am
content: Well, I'm using AI in my embedded code development (Picbasic pro) with some success, however, cases when AI generated code works directly, are close to zero. Main issues are that if often messes up with syntax - can use C++ typical construction instead of Basic syntax. Or even with basic syntax, it might make errors, like use square brackets in one line of code for array, and in next line - use figured brackets. Also, it never does any index out of bounds checks, so these had to be done manually. But anyways, it is still good, because say, when I need to interface with a certain chip, it generates a code, which gives me at least idea, how should I do it.Sometimes, it makes things very funny. Once it created new type of variable - so called "S-Type", which of course, won't compile. When I asked, what was that, it said that "sure, such type of variable does not exist in Picbasic Pro, so I invented it"

author: Nominal Animal
author_rank: Super Contributor
timestamp: June 21, 2025, 05:30:36 am
content: Quote from: julian1 on June 20, 2025, 08:59:30 pmNo, I don't think it happened quite like that. I'm 100% sure that the LLM developers' bosses fully believe that what they do is not just a transformation (even though that is exactly what it is), and therefore they are not engaging in copyright violations.The 1%-2% figure quoted in the research does not sound like much copying, but if you look at large software copyright law cases, millions and billions have depended on less copying. Typical lawyer estimate is that after abstraction-filtration, something like a dozen lines is sufficient to prove copying occurred, if there is no other source for it. (In my opinion, the limit should be higher.)The choice of using only copyleft-licensed and no proprietary source code bases for training coding-assistant AI/LLM models was definitely a deliberate one, probably due to legal advice. The AI/LLM companies know that if proprietary sources started leaking through their models, even at 1% rate, they would have huge lawsuits in their hand. With copyleft licenses, there are tens of thousands of authors, and the only real risk is a class-action lawsuit; and it is exactly this that they are fighting, trying to convince the governments that excepting them from copyright requirements on this is appropriate.I know I sound like an asshole with my copyright ranting, but having been paid to develop software under various proprietary and open source licenses –– really, everything from secret under NDA to GPL to CC0-1.0 ––, and having an actual lawyer explain software licenses and especially GPL for me over two decades ago, and having a mean streak ofpsychological fairness, it isimportantto me. Kinda like following the laws in general, so we can have a comfortable organized society overall.It really aggravates me when Cxx-level officers (and even some software developers) think that by publishing your code, you are implicitly allowing everyone else to copy your code; that the license is just a formality used between companies, or something like that. We have had books for centuries now, and even though their text is published, we do tend to respect their authors' copyrights. Why would software be any different?No, really. Math cannot be copyrighted or patented, that's true, and appropriate in my opinion. No equation is under copyright, and they are filtered out in any copyright abstraction-filtration test. But neither isménage à trois, or teenage growing pains, the folly of being human, and the other standard core subjects in literature.I'm sure we're all aware of how large publishing houses are fighting against misuse of their work by LLM companies, with very large lawsuits looming. "But we couldn't make a decent profit if we had to pay for the stuff we use!" just isn't a valid reason in a society based on equitable business and equal competition, and not state or monopoly control. But, now that governments are mixed in this and expected to issue some legal rulings on this within the next few years, we'll find out.I personally believe we should teach this stuff, the basics of copyright, at high school (if not earlier). It's really not difficult, and it opens up understanding on how you can do business, "sell your own work", in a complex society. Before I understood how copyleft (GPL etc.) and BSD- and MIT-style licenses work, and why they are used by authors, I was used to keeping sources always proprietary business secrets –– having been paid to write code for a few years already at that point ––, and thought they were incompatible with business. I was utterly wrong, of course, which is why I do not stay angry at anyone who does not understand these things yet. (I only stay angry if they are unwilling to learn, and instead stick to the misconceptions.)The various threads here about Qt licensing is similar. Up until a few years ago, Qt's marketing folks really pushed the idea that to do any kind of proprietary software, you needed a business license from Qt. This is not true, because with certain requirements, one can use all the desktop modules and even some of the embedded modules under the LGPL license. It just has to be doneright. Yet, there is always someone who simply claims "No, that's not right, you do need a proprietary license", because that is what they believe and they do not understand the licenses in the first place. "It is the safe thing to do", in their mind. Like buying and wearing the magic woo-woo crystal in your pocket just in case it does ward off evil spirits, I guess.It is also why I explicitly license my example code, algorithm implementations, and electronics designs underCC0-1.0, for example in C using the SPDX-formatted license comment, "// SPDX-License-Identifier: CC0-1.0". It is not an arbitrary choice at all for me; I specificallywantsuch to be able to be used freely for learning and commenting purposes, without any kind of risk of copyright derivativeness issues. If I created a communications format specification, I would more likely useCC-BY-4.0. The selection of the license itself is clear communication of the author/copyright owner intent, and if we respect it for one, we should respect it for all.All this circles back to the topic of AI/LLM use in software development.I consider things like "vibe coding", using AI/LLM assistants, asking AI/LLM for advice, no different to "copy-pasting".This is very new to us humans, and most believe there is a difference, which is why understanding the cognitive effects of such workflows is important. That is, that just because a tool exists, it may not be the best ever and only tool you'll need in the future. Just like a cell phone, for example.Also, we do tend to think about where we copy from, and current AI/LLM are completely obscuring the sources.In essence, comparing to literature, it is a writing coach that when you ask it, it suggests passages and plot twists from other works, but never tells you where it took them from, and lets you happily believe you thought of it yourself, that you didnotcopy it from somewhere else. This is problematic.Genuine apologies for the wall of text, but I really do feel this is important.

author: paulca
author_rank: Super Contributor
timestamp: June 21, 2025, 08:06:16 am
content: If you try and explain basic software licensing and basic copyright to most amateur github types you will find they haven't the fainest clue.License-less repos are very common. Most maintainers of them think that default copyright still protects them after they allow X number of downloads and use to violate that default copyright. Downloading is making a copy and therefore it violates a "license-less repo" copyright. Default copyright comes with no "license" to do anything with the work, other than view it if published.That's only one of many pitfalls. Once you let people violate your copyright and take no action, it is usually more difficult to make a claim later. Possibly public domaining the project and removing any rights the original author actually had over it.There is also very, very little to stop someone forking a "license-less" repo and adding a license to the fork.

author: brucehoult
author_rank: Super Contributor
timestamp: June 21, 2025, 08:51:28 am
content: Quote from: Nominal Animal on June 21, 2025, 05:30:36 amThere is nothing legally to prevent a human reading every book in the library, and then using the knowledge gained in the future.We're just not very good at it.When an LLM takes all of human knowledge, both conventional prose and program source code, and condenses it down to 500GB or 1TB of data then something must be going on. The training data is thousands of TB, right? If it manages to spit out poems or code verbatim later, it must have created some abstract theory or model of it. There simply isn't room to store everything verbatim, or even using conventional compression.

author: Nominal Animal
author_rank: Super Contributor
timestamp: June 21, 2025, 10:04:10 am
content: Quote from: brucehoult on June 21, 2025, 08:51:28 amNo; and we also limit the duration of copyright to ensure knowledge and human output eventually becomes part of the free-use common pool, too.Quote from: brucehoult on June 21, 2025, 08:51:28 amNot necessarily; it could be that the training data does not have that much unique uncompressible information after abstraction to begin with.We do not know.Which is why I think we'd have much better long-term results from using models with more carefully prepared datasets; including datasets limited by compatible licenses as I mentioned before.And if open source code is co-opted without asking their authors and completely disregarding their licenses, why isn't the same done to e.g. Microsoft Windows source code, or various Alphabet projects' sources? What is good for goose is good for gander, isn't it? Or are these AI/LLM companies somehow protected from being treated like they treat others?Do note that I've stated before that I do find the technology extremely interesting and worthwhile. It is just the uses it is put to and how, right now, that I object to.One might consider the fact that to harness the power of atomic fission, we had to develop a bomb out of it first; it was years later that a first fission generator produced useful electricity (December 1951, I believe). We tend to innovate in extremely disruptive ways, and then later on, if at all, find ways to use the innovations in an actually beneficial manner.

author: Siwastaja
author_rank: Super Contributor
timestamp: June 21, 2025, 01:51:51 pm
content: Quote from: brucehoult on June 21, 2025, 08:51:28 amI don't understand what point you are trying to make, because no one ever claimed that LLMs infringe all copyrights of all training material. No, for a single infringement, some hundreds to thousands of bytes is all that is needed, and that easily fits to 0.5 - 1 TB of data.Your comment is similar to saying that a burglar cannot physically enter all the homes around the world at the same time. It is not a sensible comment; burglary is still harmful and illegal, just like is reproducing copyrighted material without author's permission (~ license), and for that to happen, you don't need terabytes of data.

author: golden_labels
author_rank: Super Contributor
timestamp: June 21, 2025, 03:02:20 pm
content: We have no less than three separate cases of potential IP infringement here. Being vague about which one is being discussed doesn’t help. It’s enough that word “use” in the context of IP is so capacious, it may contain anything.We have training data collection and use as the training data.In this case infringement is obvious, as ML authors didn’t obtain permission from the owners. It’s only a matter whether it falls under some exemptions. Existing or retroactively established for this case.We have content of the model.Whether it’s a derived work or not is a subject to a debate. Accepting the former leads to the situation brucehoult described: making learning itself an illegal act. If it’s a human or a machine is hardly relevant: the concept is roughly the same. At most humans could raise the basic rights argument, whereas with an algorithm it doesn’t work directly.We have the output copyright.In this case it’s well established: how the work was created is not important. If a connection to the other work can be shown in court, it of course works strongly in favor of the plaintiff. But it’s not a requirement. So the output from an LLM may infringe copyright, independent of two other points. With LLMs the problem becomes bigger than it has been before, because the probability of this happening is much higher. They’re also convenient, as the connection can be hand-waved in court.

author: Nominal Animal
author_rank: Super Contributor
timestamp: June 21, 2025, 03:07:43 pm
content: Yes; that defense is the "the computer says no" of the next generation.

author: radiolistener
author_rank: Super Contributor
timestamp: June 21, 2025, 11:42:24 pm
content: I would like to warn those who place great hopes on AI. As recent studies shows, the frequent reliance on AI to solve tasks can have detrimental cognitive effects - it may impair memory, weaken neural connections, and reduce independent problem-solving ability. Most participants were unable to recall details of the content they generated with AI, suggesting potentially serious long-term impacts on brain function for those who depend on it, or use it regularly.Regular use of AI has been linked to a gradual decline in neural connectivity and brain activity, weakening memory, engagement, and creativity. It also diminishes critical thinking and reduces the effort individuals put into understanding and verifying information.So the real concern may not be that people will lose their jobs and become obsolete, but rather that we may soon face a significant shortage of individuals capable of thinking and solving problems independently, without relying on AI, making such individuals increasingly rare and highly sought after

author: LinuxHata
author_rank: Frequent Contributor
timestamp: June 22, 2025, 06:11:22 am
content: Yes, I remember similar talks about abilities being reduced, when:1. Forks were introduced2. Firearms were introduced3. Early automation equipment introduced (google for Luddite)4. Cars were introduced5. Radio was introducedXX. Internet was introducedetc.

author: Nominal Animal
author_rank: Super Contributor
timestamp: June 22, 2025, 06:43:50 am
content: Quote from: LinuxHata on June 22, 2025, 06:11:22 amExcept this one is nottalk, it is a scientifically verified observation, per the MIT preprint article I linked to inreply #69.

author: Siwastaja
author_rank: Super Contributor
timestamp: June 22, 2025, 06:47:04 am
content: And, to be fair, cars and firearms have some very real downsides to them.

author: LinuxHata
author_rank: Frequent Contributor
timestamp: June 22, 2025, 06:56:58 am
content: Well, even without any MIT research we can safely conclude that, say, horse-riding skills in 2025, amongst 14-year-old teenagers are critically low, compared to same skill in 14-year-olds around, say, 1625 year. Is this that bad?

author: Nominal Animal
author_rank: Super Contributor
timestamp: June 22, 2025, 07:59:06 am
content: Well, perhaps LinuxHata and othersareright, and embedded software developers nowadays just don't need to understand what they are doing as much as before, and remember even less. After all, if something goes wrong, there's always the AI/LLM assistant to blame for it. Win-win for everyone!

author: MariuszD
author_rank: Regular Contributor
timestamp: June 22, 2025, 08:55:36 am
content: Greater productivity is not always an advantage. I know someone who writes code using AI. He doesn't want to learn programming well, he doesn't want to design a program, he just wants to complete the task.He succeeds because AI improves productivity.In my life, I have never seen worse code. This code breaks all the recommendations for writing high-quality code. All variables are global. Functions do not return values, they only write to some global variable. The code is completely unreadable, function and variable names never reflect their purpose. Related actions are never in a single function; they are scattered throughout the code, "goto" is used hundreds of times, dozens of functions differ by just one line. In some, that distinguishing line is commented out.Even worse, there are several machines working together with shared variables, so we have kind of multithreading. Code handling the first machine is also on the second.The code shows a trial-and-error method. One function performs a task but contains an error, so it doesn't work properly. After it, the next function is called, which has the same task but also contains errors. After calling the third function with errors, the goal is achieved. It's not deterministic, but it works.Finally, I would like to add that the program controls a large industrial machine that can harm a person.Can you imagine hell for programmers? I don't have that kind of imagination, I've seen it with my own eyes. AI help and goal driven approach made it possible. Work must be done, no one cares about the rest.

author: paulca
author_rank: Super Contributor
timestamp: June 22, 2025, 09:11:47 am
content: You could just replace AI with CNC and programming with machining and that would have read perfectly 30 years ago, no?Hint. It's not the tool.... it's the tool.

author: tggzzz
author_rank: Super Contributor
timestamp: June 22, 2025, 09:57:04 am
content: Quote from: radiolistener on June 21, 2025, 11:42:24 pmThere are better arguments against LLMs.Your point is effectively the same as the point made 2400 years ago, by Socrates. Socrates recounted the Egyptian myths about the invention of writing, and declared that writing would weaken the necessity and power of memory, and for allow the pretence of understanding, rather than true understanding.His student, Plato, wrote that downhttps://newlearningonline.com/literacies/chapter-1/socrates-on-the-forgetfulness-that-comes-with-writing

author: tggzzz
author_rank: Super Contributor
timestamp: June 22, 2025, 09:59:29 am
content: Quote from: Nominal Animal on June 22, 2025, 07:59:06 amExcept the Ts&Cs will disclaim responsibility. Who was it who said writing was a bad thing? Oh yes, Socrates.

author: paulca
author_rank: Super Contributor
timestamp: June 22, 2025, 10:15:32 am
content: Popcorn. Universal and Disney file against MidJourney.https://youtu.be/zpcWv1lHU6I

author: Nominal Animal
author_rank: Super Contributor
timestamp: June 22, 2025, 10:43:42 am
content: Humans arecomplicated. Anthropologists and brain researchers seem to agree that when we invented written text, that new facility did actually reduce the acuity of our sense of smell and hearing. That is not at all strange, because we know from practical trauma research that human brain facilities can "shift": that while certain faculties may have a "standard locus", that locus can shift. (I've mentioned before the example of certain cases of aphasia, where the person cannot really speak coherently, but can quote songs and poetry and such; some regaining of ability can be achieved via training and therapy.) These are the tradeoffs, and sometimes they are definitely beneficial and worthwhile – I personally would trade my sense of smell for reading and writing without much hesitation, if I had to choose. Usually it is not one-or-the-other, but a dynamic balance, making the tradeoff itself easier, but also more difficult to evaluate and examine.The generation that has grown up with cellphones has more neck-related problems than previous generations, because of the common pose used with these devices; it is a well known phenomenon called "text neck".A human will not simply "use" a tool; they will always also adapt to the tool, too. When you first start using an axe, you will quickly develop callouses in the places where the skin is most stressed, but also your muscles and motor memory adapt, so that the swinging becomes unconscious, almost autonomic action, mostly handled by your motor cortex, and even in your limbic system. (When you are hurt, your limbic system causes a motor reaction (like "flinching") before you even become aware of it. Conversely, with adrenaline in your system, you may not even notice pain before you become aware of the damage.)To be human is to manipulate and adapt. We adapt whether we want it or not. That is what we are.Considering the tradeoffs of new tools is not the same thing as rejecting those new tools. We do this all the time in science. Consider thalidomide as an example. It was initially used for all sorts of purposes like anxiety and sleeping aid, over the counter. Unfortunately, it turned out to cause birth defects, with thousands of sufferers born between 1957 and 1962 in Europe. A couple of decades later on, we found out that it is actually quite effective in combating certain types of cancers, and is used for that purpose today.Ignoring the historical precedents and repeating the same kind of errors every generation or so is the height of stupidity in my opinion.We can do better, if we simply choose to. Yet, we seem to be governed by immediate gratification and short-term profits and benefits, even though we absolutely know there is no such thing as a free lunch or new tool without any drawbacks.Me, I do not want to stop progress, or even slow it down much. I want to minimize the disruption, so that we have time to observe the effects of the change, and react accordingly –– incremental changes, instead of disruptions or revolutions. (I've discussed this before here, especially wrt. software development. It is why I am not interested in developing my own programming language de jour, but making existing languages, especially C better by replacing its standard library with something much more suited for todays' architectures and tasks.)Take cellphones as an example: there are bothpros and cons in children having cellphones. Or AI/LLMs as an aid in creative writing: I used to be a prolific Sci-Fi reader, always on the lookout for new writers and their short stories, but now find so much repetitive AI slop online that I am apprehensive of considering new writers (simply because of this new downside, being let down by repetitive plots and protagonist-focused writing).Even AI/LLM developers themselves indicate that scraping the net for new training content is becoming less and less useful, because of the amount of AI/LLM generated content, and the issues that causes; and this will only become worse as time progresses and AI/LLMs are more and more utilized.Only an utter idiot disregards all that, just to be "hip" and "at the forefront of technology", a "tech bro".

author: golden_labels
author_rank: Super Contributor
timestamp: June 22, 2025, 03:51:16 pm
content: The references to historical precedents don’t tell us, that this time it will be fine. That problem is left open. They instead show as a fault in the argument itself. That mistake remains there no matter what. It’s a reasoning error pattern repeating over millennia. It doesn’t go away, because we appeal to authority (pointing to “scientific research” and a famous academic institution), because some examples given were inaccurate (Luddites), or there did exist counterexamples.To be specific: the claim is basically nothing other than “<X> being <negative-adjective> to <persons|society>, because it reduces faculty <Y>.” I intentionally used variables. While not absolutely always, in general it doesn’t matter, what we set them to. It’s always the same mistake. A mix, in varying proportions, of:A belief in absolute “better” or universal “preferred.”Conflating own needs, perceptions, and values (all very local temporally, spatially, and culturally) with reality.Ignoring changes to the environment, focusing solely on properties of objects embedded in that environment.Assuming a negative value inherently implies the need to take a preventive action (or opposite for positive values).Oversimplification, misinterpretation, or extreme vagueness regarding terms used. Think of a phrase “it reduces intelligence.” It induces negative feeling, but a moment later a question kicks in: what they mean by “intelligence?”Of course I don’t call for apathy and inaction. A naïve interpretation of points 1 and 2 would lead to accepting any change. But we should really think of what is really nacessary, for what purpose, and if it’s actually used. It should be weighted, if we wish to defend it for ourselves, for the general population, or for ideals. Whether something is worth protecting long-term or is it fine to just smooth out the changes.For example my primary concern is not that a great change comes to society. The society continuously adapts and in 23rd century our beliefs will be as distant and unacceptable as those of 17th century. I just want the cushion to let me and people with similar thinking toconfigure our IRC clients in 2051.And similar means respecting choices of other people, who grown up in different times and hold different values.Also, to clarify: I’m talking about the argument used. Not about what I think about LLMs in this or that use. I think that part I expressed well enough in other posts.

author: Nominal Animal
author_rank: Super Contributor
timestamp: June 22, 2025, 04:17:58 pm
content: Quote from: golden_labels on June 22, 2025, 03:51:16 pmNo, mine is not. I am saying basically that "<X> has been shown to have effect <Y> on these test persons, so we should consider the effects of society-wide use of <X>, and whether we should control or limit it somehow". Compare to e.g. sugar, hallucinogens, opiates, TV, or cellphones.Quote from: golden_labels on June 22, 2025, 03:51:16 pmYes, thank you.I do want to emphasize that I do not want to tell people what to do or not to doat all, just point out things to consider, especially the risks so often ignored (and afterwards claimed as "impossible to know beforehand"). I want them to makeinformeddecisions. Plain <negative-adjective> are useless, because everything is a balance, a tradeoff; not a black and white <positive-adjective> vs. <negative-adjective> at all. I use myself as an example only, to give ideas on options, and fully assume most people will do differently because I'm sorta wonky in multiple ways.If that does not transmit in my postsif one reads them carefully, I need to adjust.

author: LinuxHata
author_rank: Frequent Contributor
timestamp: June 22, 2025, 06:14:19 pm
content: Simply saying, world is moving forward. In a certain direction.You might like it, you might not. You might join, you might not.However, you can't do anything against it (even if you're president and can randomly nuke distant donkey farm somewhere in Iran)That's all.

author: tggzzz
author_rank: Super Contributor
timestamp: June 22, 2025, 07:30:05 pm
content: Quote from: LinuxHata on June 22, 2025, 06:14:19 pmYou can be passive and accept whatever happens, good bad or indifferent.You can be active and try to prevent people making mistakes that will havepredictablebad consequences.You can learn from others and then makenewmistakes. You can re-make mistakes other people made, again and again. Stand on a giant's shoulders, or tread on a dwarf's toes.Your choice.

author: Nominal Animal
author_rank: Super Contributor
timestamp: June 23, 2025, 06:53:42 am
content: Quote from: LinuxHata on June 22, 2025, 06:14:19 pmNo. That is an illusion.If you consider human evolution or technological advancement asflood–– the connotations of unstoppability and uncontrollability ––, the same control mechanisms do apply. It takes surprisingly little to control the direction of a flood, if you plan it beforehand. You can see this in many cities situated near rivers. Some are designed to handle floods, some are not. The physical differences are tiny, mass and cost wise, if done up front.In human technology, and to a lesser degree even cultural development, forward steps, the first tendrils of the flood, are made by very small numbers of people. Very often by key individuals. Usually not politicians, nor even inventors or celebrities, but the salesmen. And bankers, to a degree.It isexactly this phasein the introduction of a new technology that its direction can be affected, the societal effects it may/will have controlled somewhat, like designing the way floodwaters will flow.If you consider technological advancement a train that chugs forward without stopping, it still follows the tracks. The time to plan where the train is directed at is when the tracks are laid. With AI/LLM, we're already well off the station, but those building the tracks are only looking at most at the next quarter profits and not any further. What I am suggesting is not to stop the train, but to plan ahead. Leaving such planning for others is stupid, because most humans are only worried about the short term, and not even able to see the damn tracks, being so focused on the train itself.

author: golden_labels
author_rank: Super Contributor
timestamp: June 24, 2025, 07:55:00 am
content: Quote from: Nominal Animal on June 22, 2025, 04:17:58 pmI had to add subscripts to avoid confusion: both messages use the same names to denote different variables.Your “effect <Y(your)>” is nothing more than “it reduces faculty <Y(my)>.”“We should control or limit <X>” is a reaction, a consequence of assuming “<X> being <negative-objective> to <persons|society>.”And the reason for that assumption is: “it reduces faculty <Y(my)>”.It is the same pattern.Quote from: Nominal Animal on June 22, 2025, 04:17:58 pmBut there are two conditions here: the risk must be real and the reaction must be appropriate.The risk can’t be seen as real, if the argument is built upon little more than: makes things different than what I grown up with. The aforementioned pattern is exactly that. And, where the risk may be real, to weak possibility the response is monitoring. Not painting something as harmful.Quote from: Nominal Animal on June 22, 2025, 04:17:58 pmThat was a variable in a pattern.Quote from: Nominal Animal on June 22, 2025, 04:17:58 pmI wasn’t responding to you in particular. That was a note on the more general observation about the discussion. I wasn’t even considering specific people there, just the kind of argument being made.tggzzz’s post explains it perhaps better than I do.The entire class of argumentation is rejected. Not a specific instance about machine learning or single person’s words.Quote from: LinuxHata on June 22, 2025, 06:14:19 pmThis is the kind of thinking I warned against in“of course I don’t call for apathy and inaction. A naïve interpretation of points 1 and 2 would lead to accepting any change.”No, by no means this should be interpreted as a call to inaction. It is about the need to get the right reasons for acting and knowing the limits of one’s reasons.Where from people derive “you can”t do anything” thinking is beyond me. Cherrypicking historical precedents? Learned helplessness? Upbringing?Also, to be nitpicky: the world is not moving forward. There is simply no forward to move to. It is just moving. Even if there was forward, you still couldn’t tell it beforehand.

author: tggzzz
author_rank: Super Contributor
timestamp: June 24, 2025, 08:18:57 am
content: Quote from: golden_labels on June 24, 2025, 07:55:00 amThat should be remembered, and reiterated frequently lest people forget.I'm not sure which is cause and which is effect (probably both equally), but western tradition is intimately tied up with the concept of "the arrow of time".The older I get the more I appreciate the Hindu (and others?) concept and tradition of "the wheel of time".

author: LinuxHata
author_rank: Frequent Contributor
timestamp: June 25, 2025, 05:47:43 am
content: Another issue is that some people confuse "Forward" with "Good" and "Backwards" with "Bad". This is not correct.Forward means that things do change and there's no way to turn them back. You simply can't turn back time, it can't be reversed.Yes I understand that certain developments or advancements from someone's point might be "going backwards" in terms of abilities, culture, etc. But time, time still goes forward. And things will never be the same again.

author: radiolistener
author_rank: Super Contributor
timestamp: June 25, 2025, 07:04:01 am
content: Maybe now is actually the perfect time to start figuring out how to avoid using AI altogether. At the rate things are going, AI may soon become less of a helpful tool and more of a mandatory feature, baked into everything from your fridge to your toothbrush.I wouldn't be surprised if, in a few years, people start paying premium subscriptions just for “AI-free” experiences, like a digital detox, but for sanity.

author: paulca
author_rank: Super Contributor
timestamp: June 25, 2025, 09:57:44 am
content: Quote from: LinuxHata on June 25, 2025, 05:47:43 amOn the flip side. My Brother preaches much as you do and while "enshitification" is real and not every "advancement" is a benefit to all... the opinion is also a very common bias which calls it out as suspect immediately.The bias is nostalgia. We all suffer it. We all remember with fondness the things from our past. Or at least we think we do. What we actually remember is very little except the good things we have "romanced" in our heads until they are simply not a true reflection of reality.I longed for the Amiga a few months back. So I installed an Amiga emulator. The stark reality of what it was actually like back then was a shock... like it is every time. I tried to do something fairly rudimentary like edit an ASM file in DevPac. There is no mouse highlight, no syntax highlight, the basic keyboard editing functions are extremely rudimentary. Even to highlight, copy, paste is a gymnastics exercise in key binds. The screen is 800x600 4 colour and luckily I can filter out the interlacing artifacts and flicker today. Even entering a blank line into the code and you can visually see the text redraw line by line as it all moves done. IT was really unpleasant. A right good bucket of reality check cold water over my nostalgia bias.I can guarantee you that the past is nothing like you remember it. I can guarantee you for every single pleasant memory you have, you erased a 1000 unpleasant ones.The world was always shit - a book for those who romance the past. ( didn't look up the meme )

author: tggzzz
author_rank: Super Contributor
timestamp: June 25, 2025, 10:12:58 am
content: Quote from: paulca on June 25, 2025, 09:57:44 amNostalgia and rose-tinted spectacles can indeed be a trapfor the unwary. The presumption that "newer=>better" is also a trap not only for the unwary but alsofor novices. One is usually backed by money and advertising, the other may be.As someone that spent most of my career seeking and developing improvements, it is obvious that many claimed improvements are no such thing. Too often they aretrivially different offering no advantage to the user. Advantages to the seller, of course!renamed existing products/concepts, in the hope that novices and the unwary won't notice and will be swayed by advertisingignorant repetitions of known mistakes. "Those who cannot remember the past are condemned to repeat it"worse than existing alternativesdeliberate enshittificationsMost - but not all - examples of using AI/LLMs fall into one or more of the first four categories. Too many inexperienced and/or malign people won't recognise that.

author: paulca
author_rank: Super Contributor
timestamp: June 25, 2025, 10:21:33 am
content: On tails of ChatGPT. I asked it about how to get access to the RISC-V cores on a RP2350.It point blank told me there are no RISC-V cores and it was all just BS made up by AliExpress salesmen.15 minutes later I had a blinkie.elf which was RISC-V and running on my RP2350.It's a bit unfair as it is a very new chip and yes, there are confusions surrounding it. It actually has 4 cores. Only 2 at a time, the bootloader works out which and it's fixed from then until you reset it, AFAIK.So that gives me, TBC, a RISC-V assembler test rig.Normal google won.

author: golden_labels
author_rank: Super Contributor
timestamp: June 25, 2025, 10:57:31 am
content: Quote from: LinuxHata on June 25, 2025, 05:47:43 amSure, we may now switch to the meaning of “forward” that means that time passes. An undeniably true statement.(1)Being a tautology, it’s a useless statement too. So what did you meanin that post?Quote from: tggzzz on June 24, 2025, 08:18:57 amI hope this is unrelated to my earlier comment. Because certainly this isn’t what I meant.I was not referring to the arrow of time, but to the perception that there is a preferred direction for humanity to move in.Regarding the wheel of time, I’d argue it is much more tightly bound to the direction of time than in European philosophies. The need to “loop back” arises from time having direction. Whereas in the latter case we have various forms of determinism: some of which make time’s direction a mere illusion or greatly reduce its importance.(1)Directly from the very concept of time.

author: paulca
author_rank: Super Contributor
timestamp: June 25, 2025, 11:39:30 am
content: Digressing, but my morning thought for this thread is around enshitification and the loss of diversity. It is somewhat on topic for LLMs and the "revert to the mean".Unfortunately a huge amount of the world today is being decided by software developers. We have a strong tendency against "diversity". Diversity means complexity. So when faced with ANY and I mean ANY diversely complex problem we IMMEDIATELY and EXHAUSTIVELY attempt to reduce it.We don't want 150 slightly different diverse things, we want 5 neat classified boxes of things with properties to differentiate them clearly.If you fashion the item with that tool it will always "reduce to generic". Generic means cheap, scales well, etc. etc.1950s: We only produce our kitchen appliances in white.2000s: You can have any colour you want. We make 16 different colours.2020s: You can have grey, like everyone else, you have been told repeatedly through marketing that the only colour you need is grey. Obey.Things may start to pick up though. A lot of flux is underway. Some is being blamed on AI but really it is the industry recovering from the 2019-2022 bubble. We expanded too fast, hired too many "lesser skilled" "coder only" types. Like brick layers, they will code anything you give them. Managing those hordes into creating large working software systems has been the challenge. Enshitification in the form of simplifying, automating and subdividing the work enough to get productivity out of such a work force has had an impact on productivity, innovation, cohesion and levelling of technological capabilities across engineering teams. Ultimately the enshitification of software and thus our modern lives. It's very fractured at the moment from my POV. Vastly different capabilities are sitting beside each other and not even talking because they are so far apart they don't speak the same technical language and both on the same project expected of the same.The big tech are beginning the change, hopefully it goes for the better. Dumping the under-skilled "I taught myself to be a software engineer in a weekend!", instagrammers and returning to requiring an actual qualification in some STEM topic like prior to 2019.Hopefully this will free up some innovation, but it could also make it worse as I expect the work load on those skilled engineers will shift from hand holding and pampering to extremely heavy work loads doing all the stuff the AI can't.In the meantime I get to burn off my bitterness by watching said instagrammers crying on YouTube now. It's certainly better than watching the 21yo's who "taught themselves to be software engineers at the weekend" and landing themselves a $60k salary with free daily fruit in the office.... watching them with their grand 7 months experience try to explain to me why the big tech are firing them all ... that I can't watch. Not without being unkind to them comments. They do not like it pointed out to them that they stand proud on "Mount Stupid" the first time round and haven't even seen the valley of dispair even once yet! Most of us educated types went up and down that landscape of mount stupids, valley of dispair and the slow slog rise of understanding before we even went to university! There we did 4 hard years of dunning kruger hiking. So "Get the fuck off my lawn!"... and take your free fruit, fuzball and bean bags with you!

author: tggzzz
author_rank: Super Contributor
timestamp: June 25, 2025, 01:48:45 pm
content: Quote from: paulca on June 25, 2025, 10:21:33 amAnd that is a key point, and will continue to be true for a long time - because frequently the "specialised" and/or "accurate" result is preferable to the "averaged" result.Exceptions: for people too incompetent to use a search engine and/or ignore irrelevant results, for CEOs that want to replace people when answering trivial enquiries (assumes no written FAQs).

author: SteveThackery
author_rank: Super Contributor
timestamp: June 25, 2025, 06:50:12 pm
content: And yet, and yet.....Over the past couple of days I've been conversing with ChatGPT about the psychology of Chet and people like him. It wrote two essays for me: a 500 word one and a 1000 word one when I asked it for a more detailed analysis.I've got to say that the results are excellent: genuinely useful and thought-provoking. Of course there may be aspects that could be criticised, but that's true of everything I write, too.There's no way Google Search could offer me anything similar without a couple of days solid work. For very little work on my part I've got something which I value highly and find useful.PS: the only small annoyance is that it will not produce a complete, formatted copy of the conversation as a PDF because it would take more credits than I have with my free account.Feel free to make up your own mind:https://chatgpt.com/share/685c4538-b6b0-800a-96dd-b0fea15d73f1Sorry about the stuff near the end - it is my repeated (and failed) attempts to get a formatted PDF of the conversation. Even if you are reflexively an AI/LLM hater, I hope you will judge it with an open mind.

author: tggzzz
author_rank: Super Contributor
timestamp: June 25, 2025, 07:10:17 pm
content: Quote from: SteveThackery on June 25, 2025, 06:50:12 pmHaven't read it in detail, of course.A characteristic that many people have noted is that LLMs can produce beautiful sentences that makesuperficialsense.To spot the subtle flaws you already have to know the subject.Humans who rely on that technique are called deceptive bullshitters, and can be salesmen, politicians, theocrats, propagandists, etc.It does seem that LLMs are passing the Turing test, just as PARRY did half a century ago.An LLM is, in a strict technical sense, a bullshitter—as defined in Harry Frankfurt’s “On Bullshit”:"The bullshitter may not deceive us, or even intend to do so… his intention is neither to reportthe truth nor to conceal it…. He does not care whether the things he says describe realitycorrectly. He just picks them out, or makes them up, to suit his purpose."fromhttps://blog.rootsofprogress.org/can-submarines-swim-demystifying-chatgpt

author: golden_labels
author_rank: Super Contributor
timestamp: June 25, 2025, 08:41:51 pm
content: I doubt the specific answer GPT generated is relevant at all, so I’ll not even try running this app.We may instead focus on what was said by the human here. And the human tells about using ChatGPT as a recall engine. Not as a knowledge retrieval system or as a tutor. Am I wrong? If not: this is a valid use for LLMs. Unlike many stuff they’re advertised for, thisisrooted in their design.What would be invalid is trusting this information. In the same way it would be with “traditional” search results. The same kind of caution is needed in both cases, and the same checks need to be done.

author: tggzzz
author_rank: Super Contributor
timestamp: June 25, 2025, 08:59:38 pm
content: Quote from: golden_labels on June 25, 2025, 08:41:51 pmLLMs assemble sequences of words that they havefrequentlyseen inproximityin their training set. That is not recall; it is averaging and interpolation.Arguably that is worse.

author: SteveThackery
author_rank: Super Contributor
timestamp: June 25, 2025, 09:11:41 pm
content: I think it worth pointing out that caution is required in most queries, whether Google Search, ChatGPT, asking your mate, and so on.ChatGPT seems risky when asking it questions that have a specific, right-or-wrong answer. For example, if I asked "What is the maximum c-e voltage of a 2N3055 transistor", I wouldn't dare trust the answer! Because it might be wrong, with dire consequences.However, if you want an overview of a topic which you might then use to steer further research, then I find it very useful. For example, I asked it to discuss the biggest obstacles to travelling to Alpha Centauri. The result was a very useful outline which covered energy requirements, propulsion technology, survival issues (radiation, damage from space dust, etc), communications, and human factors (life support, psychological and societal issues).What distinguishes this type of query is that there isn't really a right or wrong answer - rather, it's an overview, a discussion, an outline. This, to me, is where the strength of ChatGPT lies.And remember, wherever and however you seek out information, there is always a risk of bad data. Vigilance is always required.

author: SteveThackery
author_rank: Super Contributor
timestamp: June 25, 2025, 09:25:28 pm
content: Quote from: tggzzz on June 25, 2025, 08:59:38 pmOK, but it's the results that matter, and the results can be useful.I've noticed that some people in this thread are more sceptical about the value of ChatGPT than others, and that is absolutely how it should be. The more sceptical point out how LLMs work, using that as a reason not to trust the output. I don't have the technical chops to counter those arguments. All I would ask is that the sceptics just give it a try. Try to stay open-minded, of course! 😄The number of times I've got a useful output greatly exceeds the useless ones. I don't ask it simple right-or-wrong answers like component specs. But questions like "Suggest some low cost alternatives to the 741 op-amp" seem to work OK.

author: golden_labels
author_rank: Super Contributor
timestamp: June 25, 2025, 09:37:39 pm
content: Quote from: tggzzz on June 25, 2025, 08:59:38 pmRecall is putting one in the proximity of the concepts they seek. So you just confirmed, not disproved that LLMs may be used as recall engines.Even if you didn’t, I don’t see how your conclusion follows from the premise. The reasoning you seem to be applying, is that the mere use of a probabilistic model somehow implies uselessness of an arbitrarily chosen purpose.Quote from: SteveThackery on June 25, 2025, 09:25:28 pmIt’s as much “scepticism” and being “open-minded” as it would be, if somebody tried to sell you a perpetum mobile or a wooden cart taking you to other galaxy.It’s called knowledge. There is no need to guess and be deceived by outputs from a black box, when there is basic knowledge that tells what something can or can’t do.If I tell you, that a hammer is a tool for driving screws, will you believe me? C’mon, I can show you many screws that were placed in their holes with a hammer! You will not believe how flush with surface they are! Be open-minded! Why all the skepticism? Of course not, because you do know, how screws work and how a hammer works. And this is exactly the same feeling we get each time somebody tries to argue an algorithm can do, what it can’t. Any algorithm, not only LLMs.Though some go to the other extreme, trying to argue that an algorithm can do nothing, even if it can. Which I find as harmful and disgusting as deceptive advertising many ML companies do nowadays.

author: Tation
author_rank: Regular Contributor
timestamp: June 25, 2025, 10:12:15 pm
content: Not verbatim, but an excerpt:- I'll gave you scans from some [in fact, 150+] invoices. I want you to extract the info from them and generate an Excel file listing, for each invoice: business name, VAT number, date, amount and VAT amount- OK [in fact some enthusiastic phrases and instructions on how to send the scans]- here they are [sending a single PDF file, directly from the scanner, with the invoices]- here it is [in less than a minute]After that, only detected errors in a handful of business names, all numbers seem correct.Saved an afternoon that I spent in a nice live musical show. Not really interested in scientific studies measuring if this is better or worse to my brain than filling the Excel manually, have enough empirical evidence about it.Not to mention the HUGE help it brings when studying a foreign language.No, Google search cannot do that. And holy averaging and interpolation!But, still, it doesn't write my code nor I ask it to write the Critique of Pure Reason v2.0

author: tggzzz
author_rank: Super Contributor
timestamp: June 25, 2025, 11:23:05 pm
content: Sigh. I do wish people wouldn't chop context: it makes conversations difficult to follow and enables people to make strawman arguments.Here's what you wrote:Quote from: golden_labels on June 25, 2025, 08:41:51 pmand I replied:Quote from: golden_labels on June 25, 2025, 09:37:39 pmIn English (this meaning of) "recall" implies memory. LLMs do not remember, whereas search engines and knowledge retrieval systems do remember. LLMs munge sources together. For several reasons, "munge" is a very good word to use in conjunction with LLMs."To transform data in an undefined or unexplained manner, as for example when data wrangling requires nonsystemic or nonsystematic edits."https://en.wiktionary.org/wiki/munge" To imperfectly transform information."https://jargondb.org/glossary/mungeQuoteI'm not implying that - and wouldn't unless the purpose was defined.<unrelated comments from a different sub-thread omitted>

author: tggzzz
author_rank: Super Contributor
timestamp: June 25, 2025, 11:26:54 pm
content: Quote from: SteveThackery on June 25, 2025, 09:11:41 pmJust what you would expect from a human bullshitter: exquisitely formed vague witterings, with zero understanding of the question.BTW, although I've omitted them, I do note the sensible caveats you makeIf only everybody was as sensible

author: tggzzz
author_rank: Super Contributor
timestamp: June 25, 2025, 11:33:12 pm
content: Quote from: Tation on June 25, 2025, 10:12:15 pm...and later you will spend a lot of time and effort tracking down and explaining why your summary information doesn't actually match the actual invoices - and that you are neither careless nor committing fraudSometimes it is better to get things right first time. Ask all the lawyers that have been sanctioned in several jurisdictions, for falsely presenting fictitious case law to judges. Such LLM hallucinations can be pretty career limiting!

author: Fire Doger
author_rank: Regular Contributor
timestamp: June 26, 2025, 12:22:03 am
content: GitHub Copilot has increased my productivity by 2 to 5 times.I definitely don't ask it to write me code like magic.But I search faster without needing to exit code editor.Of course I have in mind that it may be bs but usually points to right direction which most of the time is enough. It has also helped me to find bug reports in forums.If I make a change it usually suggest correct related changes.It auto writes comments and doxygen, And with proper comments it usually suggests code blocks (2-8 lines) that are useful.Plus I do some scripts like .html utilities with vibe coding which help me finish faster some tedious task. (I.e rotate a matrix 90 degrees)** Very Important, I ask it to create code that does the job, not to do the job itself. Code can be tested & reviewed, magic results are luck.

author: Tation
author_rank: Regular Contributor
timestamp: June 26, 2025, 04:25:55 am
content: Quote from: tggzzz on June 25, 2025, 11:33:12 pmNo. Later I will check if the total of invoices matches the difference in the bank account from date A to date B, if the VAT % of all invoices fits the current VATs % in use here, if the VAT calculation for each invoice is correct, and so on.Your position seems based on two non factual assertions:* LLM always hallucinate* people always accept all LLM hallucinations (i. e.: all LLM output) with no checks at allwhere both of them are not true, and the second one doesn't even depend on LLM, but on users.If I delegated this task on an human assistant, I still need some verification of the report.

author: paulca
author_rank: Super Contributor
timestamp: June 26, 2025, 07:58:02 am
content: Quote from: tggzzz on June 25, 2025, 11:23:05 pmI hate to tell ya, but that's how YOUR brain does recall. It does not "remember" the way you "think" it does.It (your brain) is also even more likely to hallucinate. In fact your brain hallucinates constantly. That is what makes us different. We have noise, entropy, free thought. We can grab our hallucinations and manipulate them, learn from them, grow them and they become great things. We call it 'creativity'.Fact recall. The brain is NOT to be trusted here. Everybody knows that you CHECK. You don't just recall the hfe value for that transistor, do you? No. You think you do, you recall a figure, but you know deep down you can't trust your own memory recall, so you look it up.Yes? All of the above has research by the bucket load.So maybe we shouldn't be asking if you trust an LLM more than google, maybe we should ask if you can trust yourself more than ChatGPT with facts.

author: tggzzz
author_rank: Super Contributor
timestamp: June 26, 2025, 09:06:41 am
content: Quote from: paulca on June 26, 2025, 07:58:02 amI am completely trustworthy. Other people, not so much.More to the point, how many times have you run into this attitude, either implied or directly expressed: "... because the computer says so". Too often, I'll bet.(BTW, would you like to buy this bridge I have for sale?)

author: paulca
author_rank: Super Contributor
timestamp: June 26, 2025, 10:47:23 am
content: Quote from: tggzzz on June 26, 2025, 09:06:41 amYou can't stop dumb. No damn is that well built. You can surf the waves of dumb and have fun, but just don't get dragged under.On topic, ChatGPT does exceptionally well with mixing metaphors like that.The bridge.Can you specify it, characterise it and prove to me that it's fit for purpose for now and the future? Then if I'm in the market, yes. Even if you use AI to help generate your collateral.

author: tggzzz
author_rank: Super Contributor
timestamp: June 26, 2025, 12:27:46 pm
content: Quote from: paulca on June 26, 2025, 10:47:23 amYou can find out all the specifications and purpose of my bridge starting here:https://en.wikipedia.org/wiki/Brooklyn_BridgeAs for the future, I will leave you to define that.

author: golden_labels
author_rank: Super Contributor
timestamp: June 26, 2025, 12:39:06 pm
content: Quote from: tggzzz on June 25, 2025, 11:23:05 pmThe recalling party is the user, not the LLM. The user has memories. The LLM is used to invoke them.When it comes to knowledge, this is also most of my search engines or encyclopedias use. I rarely use them to learn something new. I use them to reconstruct what I myself know. LLMs seem to do this equally well on average.As they are expected to. In contrast to things they’re often advertised doing, despite clearly they have no mechanism to offer such features.Quote from: Fire Doger on June 26, 2025, 12:22:03 amAnd this is where the trap hides.I strongly believe LLMs can do great job in analysing the context and narrowing down suggestions. I can’t see any risk involved in that.(1)But generating the suggested code is a different monster. Humans are notoriously bad at proofreading(2)and doing a proper check takes more effort than writing the same code. So it becomes a choice: allowing more errors to be introduced or making it less efficient.Not sure, what kind of comments and documentation it can write though. As far as I know Copilot still can’t read programmer’s mind.Of course this has to be compared to some reference. The level of programmers seems to be falling fast and it appears this is what market wants. So in comparison LLM generated code may indeed be better.(1)Not related to the task of writing code. Ignoring other areas.(2)Ironically: the cause is named by the slang word general public picked up from ML research inrecent years. Halucination.

author: tggzzz
author_rank: Super Contributor
timestamp: June 26, 2025, 01:18:35 pm
content: Quote from: golden_labels on June 26, 2025, 12:39:06 pmYet another strawman argument enabled by choosing to snip the relevant context. That doesn't make you look good.Here is your point yet again...Quote from: golden_labels on June 25, 2025, 08:41:51 pmSentence structure is <subject> <verb> <object>, wheresubject: the humanverb: is usingobject: ChatGPT as a recall engine.If the human was doing the recalling, the sentence would be "the human is recalling using ChatGPT, or similar.

author: Siwastaja
author_rank: Super Contributor
timestamp: June 26, 2025, 01:19:51 pm
content: Quote from: Fire Doger on June 26, 2025, 12:22:03 amWith claims like this, I wonder what kind of projects people do. For my programming patterns, I could see that a very well performing automation of small snippets and boilerplate could maybe increase my productivity by 10-20% tops, assuming it gets it always right and without any overhead of its own. I would estimate maybe half of that would be automation of really unnecessary boilerplate, which would be long-term positive to my brain, and about half could be detrimental to my long-term thinking capabilities (think about getting looping conditions right).With this much productivity gain, surely we should be seeing huge improvement in how software works overall, and availability of better new software? Or huge savings in cost of labor, which surely should reduce the prices of everything around us? This tech has been around us for well over two years now. When will this happen?Microsoft marketing says that Copilot would increase your productivity by 55%, so it's interesting to see you think that for you it worksan order of magnitude betterthan advertised, and usually advertisements are optimistic, not pessimistic.Just wondering.

author: tggzzz
author_rank: Super Contributor
timestamp: June 26, 2025, 01:28:40 pm
content: Quote from: Siwastaja on June 26, 2025, 01:19:51 pmJust so, except for my projects 10% would be a very optimistic improvementAlternative explanation: the "2 to 5 times" is over a small part of the project, and omits the vast majority of the project's time.In my experience only a small part of a project is spent coding, and boilerplate is only a small part of that time. If it took significant time, I would automate it without needing LLMs!

author: Fire Doger
author_rank: Regular Contributor
timestamp: June 26, 2025, 01:49:50 pm
content: 2 to 5 times is for the majority of my workload, it's not the same for everyone.For example I use copilot to translate mandarin (they make much more sense)50% of my code is comments. I spend a lot of time reviewing and fixing other people code.With auto suggestion changes it's 1 tab click to update the comments based on what I changed.Even the git commits have more information now.Writing an example on how to use a library, making markdown files, etc... It takes less than 5 minutes. Otherwise it could take a couple of hours.Generating unit testing is also much much faster.Someone who has different workload, like design pcb or is in more debug oriented developing state then surely it won't see that much of a benefit.

author: tggzzz
author_rank: Super Contributor
timestamp: June 26, 2025, 02:07:11 pm
content: Quote from: Fire Doger on June 26, 2025, 01:49:50 pmTranslation is one plausible area for LLMs, since language is so... imprecise. Nonetheless, there continue to be equivalents to the traditional cockups such a "out of sight, out of mind"->Russian->"invisible idiot" and "the spirit is willing but the flesh is weak"->Russian->"the vodka is strong but the meat is rotten"It would be prudent to use one LLM to translate in one direction, a different LLM to translate back, and then to compare the originalsFailing that, even two LLMs might highlight translation problems.QuoteWas their code produced by LLMs? If not, why does it need so much fixing?If an LLM can update the comment, the comment is probably unenlightening. (Useful comments indicate "why" and "how and when to use" not "what")

author: SteveThackery
author_rank: Super Contributor
timestamp: June 26, 2025, 03:53:49 pm
content: Quote from: tggzzz on June 26, 2025, 02:07:11 pmLD A, (0B1Ah) ; Load accumulator with data from address 0B1ASRA A ; Divide by 2LD (0B1Ah), A ; Store result back in address 0B1A😂😂

author: tggzzz
author_rank: Super Contributor
timestamp: June 26, 2025, 04:43:32 pm
content: Quote from: SteveThackery on June 26, 2025, 03:53:49 pmMost Doxygen comments end up like that.But that is a success, because then the customer's "full comments" requirement can be ticked as "done". Or not?

author: SteveThackery
author_rank: Super Contributor
timestamp: June 26, 2025, 05:21:19 pm
content: Quote from: tggzzz on June 26, 2025, 04:43:32 pmTruth be told, I used to write code like that back when I was a spotty youth. I was very proud of it. 😁

author: Siwastaja
author_rank: Super Contributor
timestamp: June 27, 2025, 02:44:05 pm
content: Quote from: tggzzz on June 26, 2025, 02:07:11 pmI have tried asking LLM to add comments just for the sake of experiment, and the comments are totally useless*. But probably not everyone realizes that; many actual people write similar comments. It becomes a bad habit. The seed of this habit comes from early lectures and tutorials, where commenting every line of what code does just in natural language is an important learning tool because the student still does not understand the programming language.*) except for the purpose of explaining code line-by-line to someone who is total rookie on that language andneedsa "natural language" equivalent side-by-sideBut one should get rid of this habit as soon as possible, and use comments to explain the design, why the code is written like it is and how it would interact with rest of the system.Or save a lot of time by writing harmful comments by LLM instead of doing that youselfThen again, I'm sure a LLM could be programmed to periodically check if these unnecessary comments are still in sync with the code, in which case it would be an improvement over manually writing them, as a very typical problem is the desynchronization of the comments. But best to leave them out, really, and write useful comments. And they are hard to write! If it feels easy to write them, just "tedious", then they likely are useless.

author: SteveThackery
author_rank: Super Contributor
timestamp: June 27, 2025, 07:07:30 pm
content: I prefer to use "virtual comments" (which look exactly like white space) because they update themselves automatically. (I'm not alone.) 😄

author: tggzzz
author_rank: Super Contributor
timestamp: June 27, 2025, 07:23:03 pm
content: Quote from: Siwastaja on June 27, 2025, 02:44:05 pmYes indeed.It is beneficial to remember that COBOL was designed to be readable in that way, hence "ADD A TO B GIVING C". "A=B+C" is regarded as advanced. Caution: that (mis)understanding is based on theonlytime I've looked at COBOL, in a book in my school's library, in 1973. That book compared and contrasted COBOL, FORTRAN, Algol (60 not 68!), and maybe LISP. I stuck with AlgolQuoteYup.QuoteI'm sceptical that will be practical. It feels equivalent tounderstandingwhat the programmerintended.

author: Analog Kid
author_rank: Super Contributor
timestamp: June 27, 2025, 07:45:44 pm
content: Quote from: tggzzz on June 27, 2025, 07:23:03 pmAs a former COBOL programmer (at one point I was actually paid to do that), I can tell you that the language is at least somewhat "self-documenting" because of its verbosity. All those words actually help.Regarding comments, one small point:Many folks suppose that comments are mainly forotherpeople reading someone's code.Not necessarily so: I use comments liberally in my own code for the sake of the future me looking at that same code 6 months, a year or two years hence and trying to make head or tail out of it.Do it for yourself.

author: tggzzz
author_rank: Super Contributor
timestamp: June 27, 2025, 09:10:22 pm
content: Quote from: Analog Kid on June 27, 2025, 07:45:44 pmAnd people complain that Java is too verbose. Sigh.QuoteWrite the comments that you would like to read if you were the other person.

author: Analog Kid
author_rank: Super Contributor
timestamp: June 27, 2025, 09:14:11 pm
content: Quote from: tggzzz on June 27, 2025, 09:10:22 pmNo, I'm saying write themfor yourself; that way they will also be helpful for anyone else reading them (assuming you don't use cryptic language that only you understand).

author: tggzzz
author_rank: Super Contributor
timestamp: June 27, 2025, 09:44:56 pm
content: Quote from: Analog Kid on June 27, 2025, 09:14:11 pmI realise that's what you were saying, but I don't think your technique follows from your objective.You give one example why my strategy is more widely useful.

author: Analog Kid
author_rank: Super Contributor
timestamp: June 27, 2025, 09:58:43 pm
content: Quote from: tggzzz on June 27, 2025, 09:44:56 pmOK.In any case, I think we can agree that extensive, meaningful comments are a Good Thing, yes?

author: adbgg
author_rank: Newbie
timestamp: July 29, 2025, 12:29:08 pm
content: Maybe something you wanna try out:https://marketplace.visualstudio.com/items?itemName=Enduin.enduin&ssr=false#overviewIt doesn't generate code. It helps debugging by running code, setting breakpoints, watching variables & co. It focusses on embedded dev only, so might be something you're looking for