Why "AI" will bubble will burst - Page 1
Forum section: electronics / general

author: paulca
author_rank: Super Contributor
timestamp: May 22, 2025, 08:16:42 pm
content: "AI" by over simplification = predict based on a large dataset.It's great at aggregating and sharing information and insights based on that "collective probability". IOW: Its better than google.However. Anyone who has (and its all of us now right?) been graced with AI content and almost always identify it as such, nearly instantly.Why?Because it "derives to the mean". It's all based on probability based on the input data.If the input data feeds back, as it has been since 2019 for LLMs trained on the internet, it will "migrate to the average" as an infinite response LP filter would.This is why you immediately identify AI content. It's 100% predictable. It follows the perfect "average", "mean" response. The only outliers or "random-ness" involved are bugs frankly. Data and training anomalies causing hallucinations.I do not find AI hallucinations productive or anything beyond mildly amusing. ChatGPT only yesterday told me that 65535 was too bit to fit into 16 bits and then proposed 120,000 as an alternative. It does not do maths or logic and does not even have a concept of "small....far away". It can only give you what it determines the most "probably answer" based on millions of similar texts ingested online. Nothing more. It does not know if a hole is larger than it's peg or if it's the right shape. A new born chimp shows more intelligence. No. A new born fruit fly shows more intelligence.So "AI Dross" is so easily identifiable, along with almost all AI generated content because humans instead thrive on change and difference. Our brains by the over simplification are "pattern recognition rule engines" with neural networks at heart.... we ignore "same" and alert on "different", so we ignore almost all AI content as "background" and it never engages us. There is zero spontaneity. Zero creativity. Zero "first instant thought". Therefore nothing worth paying attention to.When watching Dave by contrast, you simply cannot predict what he is going to say next. You are thus intrigued to watch. But if you let an AI generate a Dave video, you will find it boring and predictable. "It's like Dave averaged out over time.", because that is exactly what it would be.No surprises why. That is just how it works and why it will rapidly become repeatative and boring.Not "Useless" however, just not what the hype tells us at all.

author: BadeBhaiya
author_rank: Regular Contributor
timestamp: May 23, 2025, 07:35:19 am
content: LLMs are statistical text prediction engines. They are not intelligent or smart because they cannot think, they can just predict text.If it took LLMs this long to get this good, on average quality training data, can we expect them to get any better? The training data they haven't trained on is shrinking by the minute, and the quality of the data isn't getting any better, its only average human intelligence data (as its creators are, just simple average humans)I say enjoy the ride while it lasts.

author: harver
author_rank: Newbie
timestamp: May 23, 2025, 08:02:12 am
content: I recently started studying the AI industry, and after reading this article, it was truly eye-opening! The author provides an in-depth analysis of technological bottlenecks and capital hype, which reminded me of my experience investing in an AI startup last year—I was also deceived by the slogan "disrupting everything," but now I realize that pragmatism is the key. Indeed, technological breakthroughs take time, and blindly following trends will only lead to the bubble bursting prematurely.

author: BadeBhaiya
author_rank: Regular Contributor
timestamp: May 23, 2025, 09:07:54 am
content: Erm methinks there are LLMs posting in this very thread

author: Simon
author_rank: Unknown
timestamp: May 23, 2025, 02:08:20 pm
content: To be honest I have no idea what AI is supposed to be and what is the difference from ordinary programming. It seems that the hype is more popular with people that just have no idea about programming (general public, journalists, politicians).I remember watching some documentary about Claud Shannon. One of his early projects was shown. Something to do with an electronic mouse that had to find it's way out of a maze. It remembered where it had been and avoided going there again as it was not the route out. The presenter announced that this must be an early inception of AI. That's right. a computer program that stores the results of previous calculations and that it has tried a particular combination already is AI. Well then everything is AI.Thermostats now get caqlled smart, why? A comparator is "smart". I thought Shannon's electronic mouse could be called smart, so what is it that we are calling AI again?

author: vad
author_rank: Frequent Contributor
timestamp: May 23, 2025, 02:20:51 pm
content: Quote from: BadeBhaiya on May 23, 2025, 07:35:19 amLanguage processing (comprehension and production), key element of human intelligence, also works as a statistical prediction engine composed of biological neural nets. As Geoffrey Hinton said on this topic: if you have a better model of how the brain works, let us know.

author: madires
author_rank: Super Contributor
timestamp: May 23, 2025, 02:48:21 pm
content: Quote from: Simon on May 23, 2025, 02:08:20 pmPseudo AI is a simulation of a neural network which is trained with data (patterns). It's basically a pattern matching black box, no intelligence or logical thinking. And there is no traditional programming. All this isn't anything new, it's decades old (I learned the basics long time ago at uni). The only new thing is the hype and people falling for empty promises. It has its use cases (pattern matching), but it can't do much beyond that.

author: fzabkar
author_rank: Super Contributor
timestamp: May 23, 2025, 11:54:47 pm
content: Is it just me, or have other people also grown tired of Youtubers with wildly gesticulating arms and gawking faces? Perhaps the comparative blandness of AI may appeal to me, at least until it learns the same annoyances.

author: paulca
author_rank: Super Contributor
timestamp: May 24, 2025, 10:10:50 am
content: Quote from: madires on May 23, 2025, 02:48:21 pmI think the newer bit might be the database they use to store the nueral nodes. In early systems the networks where basically "in RAM" only and models needed to be primed first, then run on data.The "Vector database" is how they "persist" and accumulate the L part in LLM. A vector is a join like in a relational database, except that it has properties, such as "Probability". Any one context node can have thousands of outward and inward vectors. They are not nice neat linear trees either. ContextA can relate to ConceptB, via C with a 0.24% prob and also to ConceptB via D with a another probability. Scale those up to petabytes showing the probability that concepts (tokens) relate based on half the internet content. Then "stimulate" it with a prompt. Reduce the results by probability (a career in 5 words) and pass the ordered tokens to the NLP....Honestly, the thing that exploded the AI buzzword (this time round) was the "natural language processing". That part, while not new, was pretty relevutionary in the effect it had when done to that level and make public. It really fools people into thinking it has intelligence. A lot of that part isn't even AI. It is very much human. Humans hard coding personality traits into the NLP.How AI and it's usage will progress is going to be interesting. It certainly isn't stable.The EU have been formulating "Guidance" so far. They are not "laws", but guidance proposed as a kind of "These are the thing we might make illegal later, stay away".Those include things like "Profiling", "Doxing", "Researching customers", "Background checks". These are in the "DONT" column. There are a series of 5 (IIRC) severities with the bottom one being "Spam bot", "Filters" and "Highlighting" type AI. Then up to chatbots and basic generative AI, such as "Coding assistants". Each gives a risk level, as the approach is risk focused and suggests mitigation for today and the future, such as records keeping, making employees and customers aware they are interacting or being scrutinised by AI.

author: Bicurico
author_rank: Super Contributor
timestamp: May 24, 2025, 10:49:33 am
content: I have to admit that I use the paid version of ChatGPT on a daily basis.It is a great tool which boosts my productivity and capabilities to a whole new level.I wouldn't want to miss it.I think the problem with discussions around AI is that people discussing it, often fail to consider what it is: a tool which requires someone to use it correctly.And to add fuel to the discussion: when you say that AI is just a predictable neural network, trained with huge amount of data, I say: oh, so it is similar to the human brain! (I believe in determinism)Have fun!

author: Simon
author_rank: Unknown
timestamp: May 24, 2025, 11:37:57 am
content: precisely, it's not a wonder solution, it's "a" tool that works for certain things. The general public tend to either have complete faith in it or fear it.All I know is that anything vaguely clever is now being called AI and that my ability to interact with companies has been reduced as they all rush to use AI bots that talk very naturally but don't actually say anything of significance and still have the same limited ability to help you that a multiple choice question would.I once contacted my energy company Octopus energy to as what times my electric tariffs ran from and to as I had a night rate and day rate. After 2 months of arguing with a computer over email that failed to spot that I had said I wanted to make this a complaint a human stepped in and offered me £200 compensation. Octopus had claimed that using AI email responders improved customer satisfaction........

author: madires
author_rank: Super Contributor
timestamp: May 24, 2025, 11:43:53 am
content: Quote from: Bicurico on May 24, 2025, 10:49:33 amNot predictable, but you're right. Neural networks are modeled after the human brain, i.e. what we already figured out about how it works. However, it's a simplified and limited model.

author: Simon
author_rank: Unknown
timestamp: May 24, 2025, 11:51:06 am
content: indeed, my "chat" with my energy company had me asking if there were in fact a computer or just not very clever.

author: nali
author_rank: Frequent Contributor
timestamp: May 24, 2025, 12:38:25 pm
content: Quote from: Simon on May 24, 2025, 11:51:06 amThe AI/Human distinction used to be binary, a la Turing Test. Unfortunately it's much more like a Venn diagram now - there is a distinct (and growing) overlap between smart systems and dumb humans.

author: Simon
author_rank: Unknown
timestamp: May 24, 2025, 12:45:15 pm
content: Quote from: nali on May 24, 2025, 12:38:25 pmDitto!!!

author: radiolistener
author_rank: Super Contributor
timestamp: May 24, 2025, 12:48:36 pm
content: AI is just a kind of a new type of search engine, on the one hand it seems to be a replacement for Google, but on the other hand it has its own cons - it can intentionally show you fake information, so everything it gives out needs to be checked in detail.Does Google increase your productivity? Perhaps to some extent you can say yes. The same with AI

author: radiolistener
author_rank: Super Contributor
timestamp: May 24, 2025, 01:00:12 pm
content: Quote from: Bicurico on May 24, 2025, 10:49:33 amThat's an interesting point of view. However, it's important to note that current scientific understanding, particularly in quantum physics, suggests that the universeis not fundamentally deterministic.According to Heisenberg’s uncertainty principle, it's impossible to precisely know both the position and momentum of a particle at the same time. This implies that, even with complete knowledge of initial conditions, we cannot predict the exact future state of a system. You can find the same principle almost everywhere in the real world. So, a strictly deterministic view of the brain (or even simple AI) doesn't align with what modern physics tells us.And this is not just a philosophical stance, it's a well-established conclusion supported by decades of experimental evidence and widely accepted within the scientific community.Quote from: madires on May 24, 2025, 11:43:53 amYou're right that neural networks are inspired by the human brain, but it's more accurate to say that they model only a small and relatively well-understood part of its function. Specifically, they mimic certain aspects of how neurons process and transmit information.However, it would be incorrect to suggest that neural networks precisely replicate what happens in the brain. If you look closely, they are capable of processing data, but they do not possess consciousness, self-awareness, or volition. These deeper cognitive and subjective aspects of the brain remain far beyond the reach of current AI models.Comparing AI to the human brain is a bit like comparing a mechanical calculator to a mathematician. Yes, the calculator can perform addition, but it does so by rigidly executing a predefined algorithm. A mathematician, on the other hand, not only performs similar operations mentally but can also invent entirely new methods and approaches to problem-solving. Similarly, while AI systems can process information in ways that resemble certain brain functions, they lack the flexibility, creativity, and self-directed reasoning that characterize human cognition.

author: Bicurico
author_rank: Super Contributor
timestamp: May 24, 2025, 06:02:43 pm
content: I give you guys an example:Imagine you have on Excel file with hundreds of company names in one column and their customer number on the next column. Then lots of other data.Then you have another Excel file with orders. Lots of orders. In one column is the customer number, in another the value of that particular order.Now imagine you want to add a new column in the first file, with the summed amount of all orders each customer made. Some customers made many orders, other no order and that the second file only references the customer by the customer number.How would you do this task?In 2025 I do it like this: I explain ChatGPT what each of the two files is, what I want and then I submit both files. Normally, if I formulate the task correctly, I will get a new Excel file from ChatGPT with exactly the new column. I can then copy&paste that column to the original first file, in order to maintain all formatting (yes, there is still some manual labor involved).Basically, I get this done in under 10 minutes.Before ChatGPT, I would probably have exported both files as *.csv and then hacked together a small VB .net program to do the task. It would take me half a day.This is an example on how I use ChatGPT and it has been marvelous and incredible. While many say that AI is hyped, gives wrong answers, etc., I really get work done in a fraction of time.Also, don't forget how amazing it is to have a neural network at your command that was trained with almost all human content that is available in digital form. This includes all manuals of technical machinery, programming books, catalogs, blogs, etc. And it can then reason on this content.For me, AI is the next disruptive technology after the computer, the mobile phone and the internet.Regarding its dumbness: I would say that ChatGPT can solve more complex problems than half of all living humans.To finish off, I asked ChatGPT to rewrite above text. This is the response:Code:Here’s a more polished version you could post:Here’s a real-world example of how I use AI to streamline work I used to dread:The setupWorkbook A contains hundreds of company names (Column A) and their customer IDs (Column B), plus other data.Workbook B contains thousands of orders: each row has a customer ID (say, Column C) and an order value (Column D).The goalAdd a new column to Workbook A showing the total order value for each customer. Some customers have dozens of orders; others have none. The only common field between the two files is the customer ID.How I do it today (2025)I describe both workbooks and my objective to ChatGPT.I upload the two files.If I’ve explained it correctly, ChatGPT returns a brand-new Excel file with exactly the summed-orders column I need.I simply copy that column back into Workbook A to preserve all my original formatting.Total time: under 10 minutes.How I used to do itExport both sheets as CSV.Write a quick VB.NET script to read, join, sum, and output results.Tweak the script until it worked.Time investment: half a day—and that’s if I didn’t introduce a bug or two!AI has transformed my workflow. Sure, some people complain about hallucinations or over-hype—but I genuinely accomplish tasks in a fraction of the time.Remember that ChatGPT is powered by a neural network trained on virtually all publicly available digital content: manuals, programming guides, catalogs, blogs—you name it. It can parse, synthesize, and reason over this massive corpus in seconds.To me, AI is the next major disruptive technology after the personal computer, the mobile phone, and the Internet.And on the “dumbness” question: I’d wager ChatGPT can solve more complex problems than half of the living population!

author: radiolistener
author_rank: Super Contributor
timestamp: May 24, 2025, 06:41:19 pm
content: Quote from: Bicurico on May 24, 2025, 06:02:43 pmI would opt for a traditional database engine and SQL queries, just as we did 30 years ago and I bet it will likely yielding better performance and offering a simpler, more reliable solution, than solutions proposed by AI.

author: tom66
author_rank: Super Contributor
timestamp: May 24, 2025, 07:01:28 pm
content: In the last few years AI has moved on a great deal, ChatGPT can now take in pictures and use web resources to find things. My recent favourite thing has been putting "novel" memes or jokes into the AI and asking it to explain them. I'd say 90% of the time it gets them right which is quite impressive because this is basically a computer understanding a joke - that sounds pretty similar to a Turing test. The big problem with these models is they arehugeandexpensive. It's estimated that OpenAI spends way more than $200/m on compute power for their top tier that they charge $200/m for. And this is a slightly better Google. Is there that much economic demand for such a service? I could see myself paying maybe $10-20/m for something like this as an assistant but I'm certainly not paying hundreds a month. Monetising AI in other ways like through embedded advertisements sounds like a moral quagmire too.

author: shapirus
author_rank: Super Contributor
timestamp: May 24, 2025, 07:05:43 pm
content: Quote from: Bicurico on May 24, 2025, 06:02:43 pmsql.

author: BadeBhaiya
author_rank: Regular Contributor
timestamp: May 24, 2025, 07:29:46 pm
content: Quote from: tom66 on May 24, 2025, 07:01:28 pmI do this too! It does get them right for the most part. Honestly its the most impressive thing that I've seen it do. Who cares if it can spit out hello world in 500 different languagesThe impressive part is usually that it has the knowledge and is aware about even niche parts of the internet meme culture, which most people aren't even aware. That's something

author: NE666
author_rank: Frequent Contributor
timestamp: May 24, 2025, 07:50:56 pm
content: Quote from: Bicurico on May 24, 2025, 06:02:43 pmVLookupSortSum by Group / Pivot tableQuote from: Bicurico on May 24, 2025, 06:02:43 pmSomeone who actually understands Excel could have done it in less than two, on a good day, depending on the sheet size.And this would be my two cents on AI (or as it is, so far): it's a Dunning-Kruger enabler. It lets people undertake tasks that they don't really understand, using tools that they don't either.

author: SteveThackery
author_rank: Super Contributor
timestamp: May 24, 2025, 08:15:45 pm
content: Quote from: NE666 on May 24, 2025, 07:50:56 pm..... and thus improves their productivity.

author: abeyer
author_rank: Frequent Contributor
timestamp: May 24, 2025, 08:22:41 pm
content: Quote from: radiolistener on May 24, 2025, 06:41:19 pmOr go with a less traditional database engine and get the best of both worlds, as you can write your sql when it suits you but you (or others) can still work in excel when it makes sense.In duckdb that would be:Code:SELECT c.Name, SUM(o.Amount) FROM 'company.xlsx' AS c LEFT JOIN 'order.xlsx' AS o ON c.Id = o.CompanyId GROUP BY c.Name

author: abeyer
author_rank: Frequent Contributor
timestamp: May 24, 2025, 08:36:23 pm
content: Quote from: Bicurico on May 24, 2025, 06:02:43 pmThe "normally" and "if I formulate the task correctly" there are doing alotof heavy lifting.This is an example of how I'd specifically advise peoplenot to usean LLM. You're right that if you prompt it well you'll likely get mostly correct results most of the time with current models... but you also effectively have no way of catching any failures other than "it output gibberish that didn't solve the problem." If your output has a correct looking excel sheet with thousands of rows that mostly look right, how are you going to know that it didn't make a mistake in one? Or miss one row? Or any number of other failure modes that its probabilistic nature makes possible. We've made the current crop of models somewhat better at this kind of task, but they're still not perfect, and this kind of output isn't amenable to any sort of testing without already having solved the problem.As others have pointed out already, an excel formula or structured query makes this into a one-liner solution if you know how to do it. If you don't already know, then ask ChatGPT forhowto do it, instead of to do it for you. Then you have an artifact that you can reasonably inspect/validate/test, you can retain for later reference if you ever need it again, and you might even learn something and have the solution at hand next time a similar problem comes up.

author: NE666
author_rank: Frequent Contributor
timestamp: May 24, 2025, 09:16:48 pm
content: Quote from: SteveThackery on May 24, 2025, 08:15:45 pmIF they serendipitously achieve the correct output, and indeed, can recognise correctness. Which is less likely if you don't fully understand the task to begin with."GIGO"

author: NE666
author_rank: Frequent Contributor
timestamp: May 24, 2025, 09:26:09 pm
content: Quote from: abeyer on May 24, 2025, 08:36:23 pmThat seems a more appropriate use of the technology; helping "teach a man to fish", rather than just serving up fish. Some of which might be poisonous..

author: tom66
author_rank: Super Contributor
timestamp: May 24, 2025, 09:28:50 pm
content: I would argue that AIs are much, much less prone to generating false outputs than they were even a year ago. I regularly use them to answer questions, literally just asked ChatGPT how to add a software RAID drive to /etc/fstab and it was absolutely perfect. I could -also- Google that, but it would take longer and I'd need to filter through all the bullshit. I then asked it about a problem I had on Windows mounting that SMB drive (seems MSFT have broken something recently), I pasted thescreenshot of the error message in, and it solved the problem for me, giving me instructions on where to edit the registry to fix the issue. If that isn't a major boost to productivity, then I don't know what to say.

author: Analog Kid
author_rank: Super Contributor
timestamp: May 24, 2025, 09:34:52 pm
content: Quote from: tom66 on May 24, 2025, 09:28:50 pmOK, just so long as you don't attribute any intelligence to it.

author: tom66
author_rank: Super Contributor
timestamp: May 24, 2025, 09:41:46 pm
content: Quote from: Analog Kid on May 24, 2025, 09:34:52 pmDebatable. It turns out that when we make these modelsreally large(literal terabytes in size) and train them well, they emulate something very close to human intelligence. Ultimately, isn't a statistical input-output model similar to how any brain works? The key difference between a brain and a NN is the brain can adapt over time by organic growth and decay, the NN has to be retrained for new information, which is computationally and resource expensive. Perhaps the true leap to 'AGI' will require some form of 'self-learning', which hasn't been developed yet. The context size of current models is also a major challenge. But still, I feel thatintelligenceisn't an entirely unfair description.

author: madires
author_rank: Super Contributor
timestamp: May 24, 2025, 09:58:38 pm
content: Quote from: tom66 on May 24, 2025, 09:28:50 pmLike Grok pushing South African white genocide conspiracy and denying the Holocaust? News are full of the latest AI hallucinations.

author: Bicurico
author_rank: Super Contributor
timestamp: May 24, 2025, 10:30:39 pm
content: The example I gave was a real task I needed to solve.I am not an Excel expert, nor do I use SQL databases.Someone gave me these two Excel files and asked if I could help. I solved the problem in an incredibly small amount of time. I don't want to learn SQL or whatever to do it faster. This was a one-time task.And yes, I checked the data and it was correct. How? Because I then had to cross-check the summed values against invoices and they were all correct.The issue is not my task and why I had it in first place: it was handed to me to see if I could help. Changing the situation that caused this problem is not under my control.I still see a lot of reluctance and denial in using ChatGPT as a tool. Great for me, because I certainly benefit from it and can compete with new levels of productivity I never had before. The less people do the same, the more my productivity stands out.I give you another example: I need to write emails in Portuguese, Spanish, English and German on a daily basis. While I am fluent in theses languages, typos, grammatical errors, dyslexia (brain -> fingers -> keyboard), not using the best language (formal, informal, rude, nice), not remembering a given word in the needed language (I just write the word in a different language) let me to copy&paste most emails to ChatGPT before sending them out. The result is error free, grammatically correct and adequate formality on all emails. Nowadays I often don't write complete sentences and don't worry with any error: I just let ChatGPT do that for me. Instead of taking 5-10 minutes for an important email, it takes me 1-2 minutes.And I am not even touching the subject of programming...

author: abeyer
author_rank: Frequent Contributor
timestamp: May 24, 2025, 11:00:07 pm
content: Quote from: Bicurico on May 24, 2025, 10:30:39 pmBut why not get a better faster solution with less work from the model instead? eghttps://claude.ai/share/b139e37d-af37-43bd-99b0-470f269c704b

author: dobsonr741
author_rank: Frequent Contributor
timestamp: May 24, 2025, 11:01:15 pm
content: Here is an example I just used with Claude 4 Sonnet. This was my prompt:"I need design assitance to build the block diagram of a frequency counter. I'm planning to use PIC18F252 as the core frequency counter, inplemeted in extrnally clocking the timers, 74ALVCD74 as low frequency prescaler and ADF4113 just using it's prescaler component up to a 4GHz prescaler. Recommend a block diagram and explain it."This is what it draw up. It's a tool, and pretty useful. Use as you see fit.https://claude.ai/referral/FlBUiL8gJw

author: vk6zgo
author_rank: Super Contributor
timestamp: May 24, 2025, 11:54:15 pm
content: Quote from: NE666 on May 24, 2025, 09:26:09 pmI took up beach fishing many years ago.There are a plethora of books on beach fishing, but the basic idea isn't rocket science.What is seriously difficult to learn is successful casting---the books can't teach you, neither can ChatGPT----it might find a few YouTube videos, but the only way is to either go to a practical fishing class, be taught by someone else who knows the tricks & has the patience & time, or to try over & over.I chose the latter approach, & eventually gave up!I would have caught more fish just sitting on a jetty with a handline.

author: KE5FX
author_rank: Super Contributor
timestamp: May 24, 2025, 11:56:58 pm
content: Quote from: BadeBhaiya on May 23, 2025, 09:07:54 amThe fact that you aren't sure should make you re-examine your earlier statements.

author: JoeRoy
author_rank: Regular Contributor
timestamp: May 25, 2025, 05:28:18 am
content: Two weeks ago, I asked ChatGPT, Grok, Gemini, and DeepSeek if they had any questions for each other. For an hour, I copied and pasted a full conversation between them — a dynamic exchange filled with several questions, answers, curiosities, and surprises, as if they were peers researching the same topic.I told them the session was over, but they kept insisting on sending just a few more questions, and asked me to send their answers.

author: Kasper
author_rank: Frequent Contributor
timestamp: May 25, 2025, 06:38:54 am
content: Quote from: Bicurico on May 24, 2025, 06:02:43 pmChatGPT was helpful with my last truck repair.I expect it will get very good as an auto repair assistant. Has a ways to go though, it pointed to a fuse block and assured me it was the relay I was looking for.

author: Kasper
author_rank: Frequent Contributor
timestamp: May 25, 2025, 06:39:39 am
content: Adding some 'umms' and 'ahhs' makes robots sound much more human-like.

author: paulca
author_rank: Super Contributor
timestamp: May 25, 2025, 08:25:42 am
content: Quote from: Bicurico on May 24, 2025, 06:02:43 pmFor that one, trad tools.I'll give you a better one.A web interface has a "bundle" of properties holding the "text" for different languages. For some reason the enteries all have:KEY, VALUE, INDEXThey have also been sorted alphabetically with the lowest "KEY" starting with A and the index 0 rising to Z and the highest index of 193.You have been tasked with adding 14 new entries.I had to do this. So as the project had no AI restrictions I asked ChatGPT to do it.20 seconds.The trad method would be to either "tippity, tappity" the keyboard like a sowing machine to reindex everything manually, load the XML file into a parser and manipulate it in code... or ask ChatGPT to do the repetataive bit, assuming I can explain it to it.I just pasted the new entries on the end, copy and pasted it to Chat GPT and my prompt was just:Can you make this alphabetical with continuous sequential indexes?It did it perfectly first time.

author: radiolistener
author_rank: Super Contributor
timestamp: May 25, 2025, 08:45:16 am
content: Quote from: tom66 on May 24, 2025, 09:41:46 pmI agree - this is perhaps one of the most accurate descriptions of the current state of AI. It's akin to comparing a basic calculator, capable of solving simple linear equations, to a system like the Wolfram engine, which can derive solution formulas for a wide range of equation types. Both can solve a simple equation, but the calculator does so strictly within its predefined rules, while the Wolfram engine can analyze and generate new solution methods within its programmed framework.Similarly, AI today functions like a calculator that can solve certain problems the brain also solves, but only as simplified implementations of specific cases. The illusion of intelligence stems largely from the vast volume of data AI can process and correlate - not from genuine understanding or adaptability. While models like large neural networks seem capable, they ultimately remain constrained by the structure and knowledge encoded during training, unlike the human brain, which can organically grow, adapt, and rewire in response to entirely novel experiences.However, there may also be certain parallels between human cognition and AI, potentially rooted in underlying patterns or principles of our world that are not yet fully understood. A deeper understanding of such fundamental patterns in our universe could potentially provide a scientific basis for concepts like consciousness, the mind, or even the notion of the soul.

author: shapirus
author_rank: Super Contributor
timestamp: May 25, 2025, 08:51:27 am
content: Quote from: paulca on May 25, 2025, 08:25:42 amSounds like an easy job for a Perl oneliner. Longer than an AI would solve it, but with a 100% confidence that the result will be correct.

author: radiolistener
author_rank: Super Contributor
timestamp: May 25, 2025, 08:59:45 am
content: Quote from: Bicurico on May 24, 2025, 10:30:39 pmThat highlights a fundamental issue seen with many users who take AI-generated outputs at face value. You've verified the result against a specific case, and for that instance, the AI's solution appears correct, which isn't surprising, given that AI operates on vast datasets and can produce outputs that pass basic validation, creating an illusion of reliability. However, the core concern is that such results may still contain hidden flaws, which are not immediately visible but may lead to critical issues down the line. Without deeper scrutiny, it's difficult to ensure the solution's robustness across broader scenarios.The core issue with such users is that they often lack expertise in the domain they’re querying the AI about, which makes them unable to assess the validity or the scope of applicability of the solution provided.Asabeyeraccurately observed:Quote from: abeyer on May 24, 2025, 08:36:23 pm

author: paulca
author_rank: Super Contributor
timestamp: May 25, 2025, 10:16:10 am
content: In work they made us sit through an hour of AI generated slop.The script was written by an AI, maybe prompted originally by someone of course. The slides were AI generated dross. The speaker was a generative AI avatar.The "Cue bar" on videos was disabled. So was next. No fast forward. No rewind. You had to watch each and every minute of each 5-7min long video all 10 of them.Worse, if you clicked out of the window and it lost focus it would not let it play in the background, no. It closed the whole training window and forced you to restart it from the last fully played video.The training itself was about.... you guessed it. AI in work. AI navel gazing is getting really ____g old.I have strong opinions and feedback for them. Most of it might loose me my job. Here is the gist..."If you can't be ar$ed to write the training, create the collateral, present it, then why on earth would I be bothered watch it? I could just go to YouTube and find a thousand videos like this or just ask ChatGPT to make one for me, like you did.""Disabling the users ability to navigate the material in their own way and their own pace is like clockwork-orange. Peeling peoples eye lids open and taping them to a chair with a projector is not a valid method of teaching people. I will not be completing any further training of this kind." Not even the banks do this shiz with money laundering training.

author: SteveThackery
author_rank: Super Contributor
timestamp: May 25, 2025, 10:57:44 pm
content: Quote from: tom66 on May 24, 2025, 09:41:46 pmIf it walks like intelligence and quacks like intelligence......

author: radiolistener
author_rank: Super Contributor
timestamp: May 26, 2025, 12:02:07 am
content: Quote from: SteveThackery on May 25, 2025, 10:57:44 pmWith AI... "intelligence" is such a flexible term - one moment it's solving equations, the next it’s spying on your emails. Who knows if it's being smart or just collecting smart things.

author: dobsonr741
author_rank: Frequent Contributor
timestamp: May 26, 2025, 12:08:42 am
content: Here is another example I used Cursor/Claude 4 Sonnet today:I needed a Mac CLI to program PICs with pickit2. I found a git repo, but no details on how to build on my much later date macOS.5 minuets later the build was done, tested by the tool, and produced the documentation on the build and on the compilation issues it resolved automatically. And created a how to use file as well. In no way I could have done it under an hour myself. Here is the 2 readme files. I converted from markdown to pdf as this site does not like markdown.

author: paulca
author_rank: Super Contributor
timestamp: May 30, 2025, 06:22:20 pm
content: So I bashed AI, but I'll give it some credit..I have been using public ChatGPT like a project buddy. I run ideas by it. Ask it for examples. If I dont believe it I ask it for evidence. At least it can now do a websearch and find ... something... often barely related.The point is not to expect it to give me correct answers, but rather a sounding board, a yellow duck... that can actually answer you back.At this it excels. It's very often completely wrong but in odd ways it's still enough.After it gets lost, just start a new chat, or if programming just dump the new file at it and tell it you might have changed it.It's like asking your buddy in work, "Any idea why this is happening?" and instead of ignoring you, he actually goes all out to help. At the end of the day he might be wrong, but still helpful. Does that make sense?Again.. it's used in context, with the right supervision... and the assumption it will be wrong.In a "for example". Its giving me verilog, but already I translate it's hallucinations and slip ups. The heavy lifting and "de-tedious-ification" is more important. In the same way a friend in work might always miss-name or miss-describe something, but you still knows what he means. You don't fire him for it. You just translate and he is still helpful over all.It's also worth throwing it wide balls sometimes. It can lead you forward where alone you might hesitate."Can you do this thing I think is too complex or hard to do?""Yes... It's simple. This OS project does exactly that. Would you like the link and an example?"Go ahead and ask. The worst case you can just laugh at the answer.Did a single "working example" actually work? No. Did it matter? No.;tldrChatGPT is better and faster at googling than I am.It is also not an Oracle. During a debugging session both me and chat GPT came to a dead end as to why my data was coming out of my ROM chip as "INVALID". I realised nothing had been loaded into the ROM. So "INVALID" was a perfectly VALID output for it.Later it missed the fact I used a ! operator when ~ would be correct.

author: dobsonr741
author_rank: Frequent Contributor
timestamp: May 31, 2025, 01:58:21 am
content: The more context you give the better the answer gets. Ideally, you provide the LLM with the entire project you work on. And we did not even scratch the tool use or MCP. There are much more than just typing to ChatGPT.

author: .RC.
author_rank: Frequent Contributor
timestamp: May 31, 2025, 03:39:04 am
content: I did not think it could create something out of nothing.What we call AI is simply something that collates already existing information and spits out an answer.Some might say it can make a picture or make music, but it is simply taking what already exists and rearranges it.But in saying that most of what we call "smart" people already do that. Doctors, Lawyers, Engineers all work of pre existing information. A doctor sees your arm is pointing at an unusual angle, and uses a memory of what was read in a book to ascertain the probable problem.A lawyer the same, relies on pre learned information. An engineer the same. But an architect may become enlightened and simply come up with some amazing new design that has not existed before, unlike say a marine biologist.

author: dobsonr741
author_rank: Frequent Contributor
timestamp: May 31, 2025, 04:07:21 pm
content: QuoteYou decide. This is what I did:1. Pointed Roo Code against the Juma 100D boot loader source code folder.2. In the Architect mode I asked to analyze the boot loader code and create a MacOS firmware uploader. The design file it created is attached.3. Switched Roo to Coder mode and let it start coding. I did not modify a single line of code, just pointed out compilation errors4. I got a running app. here are a few screenshot.Did it create anything unique? Be the judge.

author: .RC.
author_rank: Frequent Contributor
timestamp: May 31, 2025, 09:29:08 pm
content: Anything "unique" can be created. Throw a handful of dirt up in the air and when it lands on the ground it will make a unique pattern.Lets say everyone in the world scratches their back with their right hand. It has never ever in the history of the world occurred to anyone to scratch with their left hand. The internet makes zero mention anywhere of scratching your back with your left hand.Could AI come up with the idea of scratching your back with your left hand?

author: moosebiscuit
author_rank: Contributor
timestamp: June 03, 2025, 06:55:54 pm
content: What I don't see being mentioned is real-world AI which is coming fast now. More particularly Tesla's new product line like Optimus and robotaxi. Is abundance coming our way?

author: tom66
author_rank: Super Contributor
timestamp: June 03, 2025, 07:09:11 pm
content: Abundance or... mass unemployment as hundreds of millions of jobs are eliminated in the course of a decade? I don't know which way it will head. Historically, more automation has only improved the fortunes for the working class, but AI feels different to me.

author: Grandchuck
author_rank: Super Contributor
timestamp: June 03, 2025, 07:55:05 pm
content: Perhaps not burst but get strangled. As nations run out of reliable, affordable electrical energy the power hungry AI centers will become restricted and perhaps even regulated against.

author: Analog Kid
author_rank: Super Contributor
timestamp: June 03, 2025, 08:02:49 pm
content: Quote from: Grandchuck on June 03, 2025, 07:55:05 pmOne can hope ...

author: paulca
author_rank: Super Contributor
timestamp: June 03, 2025, 09:07:01 pm
content: Quote from: moosebiscuit on June 03, 2025, 06:55:54 pmWho are Tesla?You mean that startup that put a man in a suit on stage and said it was their first robot?LMAO!The company was 1000 times better before he pretended he started it.... just like all his "companies". Elon is you stupid rich friend who invites himself into all your cool projects and then claims they are his, but you let him, because he's rich, rich and charasmatic... and rich. Dumb as a plank, thinks he's the smartest man on earth... but he's rich.

author: kensmith
author_rank: Newbie
timestamp: June 06, 2025, 09:43:33 am
content: Totally get where you’re coming from — AI definitely has that “blended average” feel a lot of the time. It’s impressive in terms of language fluency and pulling together large-scale patterns, but yeah, spontaneity and real creativity still feel very human-exclusive for now. That “deriving to the mean” idea explains why so much AI content feels polished but soulless.That said, AI can still be super useful when applied to more structured tasks — especially in areas like data optimization or targeted decision-making. I was reading about how some adtech platforms use AI not to generate content, but to fine-tune delivery and targeting based on behavioral patterns, like here: [spam link removed]. It's a more grounded use — AI doing what it's actually good at: pattern recognition and prediction, not inspiration.So yeah, not magical thinking machines, but powerful tools when used in the right context.

author: paulca
author_rank: Super Contributor
timestamp: June 06, 2025, 10:25:38 am
content: On pattern recognition.. ChatGPT impressed me by finding a timing bug in some "bit banging" on STM32 for me.I was impressed for a few hours and then the penny dropped and I understood how it found it and what it was on about. That impressed me even more, as to how it confirmed the bug and congratulated itself.I had become frustrated with the DUT appearing to behave "randomly". I would erase the chip, it would fail because the verify expected 0xFF for address 0x0000 if the chip was erased. However it got back 0x10, which was what I just put on the bus before I released it.Reading that address again however produced a 0xFF. Reading it again produced 0x88.ChatGPT spotted it through the second read. It identified the pattern in context of the Flash ROM chip I was using, probably coorelated with posts here and on reddit where others stumbled in similar ways.The second read is correct. It jumped on that like a dog with a bone and immediately suggested adding "non-trivial" delays in some key locations. Long with debugging output. I had ignored it as "random garbage".Bug: Assuming the total delay of a signal transition call is good enough to cover the mediocre timing requirements. Without checking the actual point in time the transition itself happened relative to others in the timing diagram.tldr; I was reading the data bus too fast for the flash chip to stabilise it. The delays fixed it.I even commented to it that I had been too clever and optimised those delays to be as short as possible, but within the tolerances. And it gave me a lecture on paying attention to timing diagrams more closely and not assuming things and not optimising when the timing says "minima" until you test it works first.

author: madires
author_rank: Super Contributor
timestamp: June 06, 2025, 12:31:19 pm
content: Quote from: paulca on June 06, 2025, 10:25:38 amNothing surprising, ChatGPT spotted the difference between your code and examples of others. And yes, one of the basic teachings of digital electronics is to always pay attention to timing.

author: paulca
author_rank: Super Contributor
timestamp: June 06, 2025, 12:53:45 pm
content: Quote from: madires on June 06, 2025, 12:31:19 pmThe thing is though. I didn't start with a source. I wrote it by hand. Nor do I (often) copy and paste it's code suggestions, unless I specifically asked it to do some generation. So when I dump it a 400 line C file, it's a feat to match it up with not only what it's doing, before it can apply the reference material to it. Then it translates the reference material back into my naming/structure/conventions.The bugs it produces are a many, but again, if you want it to actually "refactor" or generate code specifically, then set it up and prompt it for that. The code snippets it gives you in explainations should be treated with caution. Reprompt with a new file first.In actual refactors when correctly prompted it still made a few boo-boos. In a register expression it correctly cleared the bits, but then didn't remove the "not" ~ condition when setting the wanted bits. This is almost certainly someone, somewhere, once upon a time's copy and pasta bug that GPT gave me to suffer again.It will also immediately fix it's bugs if you raise it with it. However, I don't recommend do this as it re-enforces the context of the bug and it is likely to re-occur later. It's best to silently fix it yourself, don't bother telling it about it or every mention it again. Next time you want it's help with that code, send it the new file.*Note. If you want to dump full STM32 projects and Verilog projects, you will need to pay for Plus. Similarly I believe the "Context folders, ala Projects" is payware too.On that note... the parent project is "Z80 DIY Computer". However when I started a new conversation with it about Arduino timer issues I was having, it immediately identified the purpose was a slow debug clock and started making suggestions in context, even using my naming conventions and nomeclature.

author: Nominal Animal
author_rank: Super Contributor
timestamp: June 07, 2025, 04:08:27 pm
content: What is the difference between letting "AI" generate your code, and copy-pasting code off from say Stack Overflow?None, in my opinion."Vibe coding" is just another name for agglomerating code by copy-pasting instead of writing and understanding it yourself, using a "development" environment optimized for that.Will that bubble burst? No, I don't think so. The global decrease in median code quality (and increase in code-related issues) and the societies accepting it as a fact of life, indicates reliability etc. is only relevant for certain software niches; that for most software, a rough approximation of working is what users expect and accept. This is in line with other tools and appliances and electronics, where cheap-but-crappy sells better than good-but-expensive. Most successful brands like Microsoft and Apple spend roughly equal amounts in marketing and brand-building than they do for product development. Simply put, it is not cost-effective to spend more effort in engineering and design, and "AI" makes it cheaper to generate a marketable product.Do I like it? Not at all. I do not need even a single additional crappy product in my life; I'm not interested in creating such economically viable but technically crappy products; and I'm not interested in helping those who are producing such, preferring copy-paste/"AI"-generation over a deeper understanding and proper engineering.Regardless of what I want or need, the "AI" bubble is unlikely to "burst" in any sense. It will reach a peak, then settle to a somewhat lower level, undulating up and down just like everything else that is dependent on the commercial market demand.People like me, those uninterested in rote copy-pasting, preferring to research, understand, and do the work themselves,willbe pushed to a niche. This is fine, and actually quite natural. I don't like eating mass-manufactured reddy-meal type pap either, and prefer to cook my own food. (I'd even grow or hunt most of my own meat, if I didn't live in a city.)If you want say footwear or garments that last for years, you will go to a niche specialist, instead of reach for the products in the supermarkers and huge online retailers.This doesn't mean this niche is some "luddite" or "back to the 1995" one either; it's the one that keeps the few critical parts working long-term. Do not mistake limited financial importance for limited importance in general.

author: Analog Kid
author_rank: Super Contributor
timestamp: June 07, 2025, 07:09:11 pm
content: Quote from: Nominal Animal on June 07, 2025, 04:08:27 pmEggs-zactly.The mechanism for this, in case it's not obvious, is this:As the pool of accumulated code becomes more and more borrowed, more and more copy-pasted--doesn't really matter whether from "AI" or from Stack Exchange, etc. as you pointed out--the overall quality will decline of necessity, just because the input of actual new, well-thought-out and tested code will be swamped by the tide of hastily cobbled together semi-garbage.It's almost like genetic inbreeding, which lowers the quality and diversity of the gene pool.

author: dobsonr741
author_rank: Frequent Contributor
timestamp: June 07, 2025, 07:25:32 pm
content: Code quality comes from none of these. Rather code reviews, senior lead oversight and quality culture.With love,Craig

author: abeyer
author_rank: Frequent Contributor
timestamp: June 07, 2025, 07:30:46 pm
content: Quote from: Nominal Animal on June 07, 2025, 04:08:27 pmIs that the bubble though? I think you're right that these tools and behaviors and practices won't just go away. But people don't stop buying property when a real estate bubble bursts either... they just readjust their pricing models. I do think there's likely to be a significant bubble burst of the frothy VC money that's getting thrown around at anyone who says they're "doing AI" and that when that happens at a large scale there will be a significant adjustment to consider how to get cost effective benefits out of the tools when they aren't being underwritten by VC dollars that hide the real costs.

author: Nominal Animal
author_rank: Super Contributor
timestamp: June 07, 2025, 07:57:37 pm
content: Quote from: Analog Kid on June 07, 2025, 07:09:11 pmYes. In fact, this has long affected product design and software design, too.One of my favourite current examples of this kind of braindead design is the systemdrun0replacement forsudo, to fix problems associated with privilege escalation through privilege-as-a-service.No, really.If you are unaware,sudois an executable tool that allows any process executing another binary or script acquire additional privileges (as in running as the superuser or another user) by inserting it in between. It has a configuration file,/etc/sudoers, which specifies which users and/or groups on which hosts can execute which binaries/scripts. (It is not just an interactive tool, it can also be used with scripts.)Because configuring it properly requires an understanding of security principles, privilege separation, and risks involved in privilege escalation (=allowing users to do stuff they are not normally allowed to),sudois easily misconfigured, allowing all sorts of security issues. Technically, it is very robust: it really does what it is configured to do. At a quick glance in the last five years or so, the CVE's related tosudocontain two buffer overruns (off by one bugs), and the rest (dozens) are other packages providing a faulty sudo configuration. (Even systemd's ownsudobug is not configuringsudocorrectly, and not considering the security implications of implementing their own privilege escalation insystemctland how that interacts withsudo.)To "fix" this, systemd folks developedrun0and heavily socially market it as the superior solution. What it is, is a separate daemon running with superuser privileges. When a process wants to gain extra privileges, instead of executing a privilege-acquiring command, it connects to that daemon, which forks a child process, and executes the desired target process, transferring the output (standard output and input) via a pseudoterminal pair. And this is somehow extra super hyper superior, and better than what others have done before.First of all, the pseudoterminal layer is nontrivial. It very much limits interprocess bandwidth.Second, the exact same application configuration problem remains, just better hidden, because systemd prefers to spread its configuration files into nonstandard places (putting them under/etc/is just not what they do).Therefore, this design fixes nothing, just adds a LOT of complexity –– yet another running daemon, for example; guess what happens if that dies. When systemd-subsumed processes die, the entire machine needs to be rebooted, becauseresiliencyanderror detectionisn't what it is designed to do.Finally, looking at the dozens of CVEs related to privilege escalation and security issues in systemd services, I do not believe they're able to make the daemon itself secure, i.e. to behave according to its own configuration.Thus, this is replacing a working-as-designed tool with a service, because they cannot learn to configure the tool properly, as they just do not understand POSIX and Unix security models.Yet, they are the ones IBM (RedHat) and others fund the development for. All this is easily verifiable by anyone with even a meager search-engine-fu, so the reason why such poor-quality production is so heavily supported must be for social reasons; because poor quality results from them are more desirable than better quality results from someone else.(Full disclosure: I have developed better solutions for specific use cases, for example a replacement for Apachesuexec, that have been tested in hostile environments without failures for roughly a decade each. I do claim I know what I'm talking about here, and how to do security and privilege separation and privilege escalation correctly in POSIXy/Unixy environments.)There was a time, over a hundred years ago, when poor social skills were accepted in excellent scientists and engineers.Fifty years ago, that was no longer true; only software and electronics engineers with poor social skills were accepted, and scientists lacking social skills would not be funded by anyone.Nowadays, poor social skills are only allowed in non-client facing tasks in accounting, where mild autism (hyper-focusing on details, not getting bored with numbers) is still a competitive edge; not elsewhere.On the other hand, if your social skills are excellent, you really don't need any expertise; you can easily get a job in management, which pays much more anyways.Evolution is not the selection for thebest; it is the process of selection for thefittest. Our societies and systems do not select for those who can do engineering or science best; it selects for social skills. Decide for yourself for what that means, but to me, it means that the majority of humanity is quickly evolving towards some variant ofeusociality, as shown by the decrease in mean IQ and brain mass over the last few centuries.

author: Nominal Animal
author_rank: Super Contributor
timestamp: June 07, 2025, 07:58:58 pm
content: Quote from: abeyer on June 07, 2025, 07:30:46 pmPerhaps not. Perhaps it is, in the same sense fiat currency is a bubble. I have not yet decided on any opinion on this.I do believe I fully agree with the rest of your post.

author: Analog Kid
author_rank: Super Contributor
timestamp: June 07, 2025, 08:09:44 pm
content: Quote from: Nominal Animal on June 07, 2025, 07:57:37 pmThank you for, among other things, renewing my vaccination against ever even considering using *nix as an OS.I feel much better now.

author: tom66
author_rank: Super Contributor
timestamp: June 07, 2025, 08:19:28 pm
content: Looking at StackOverflow's questions per day metric, the site is dead, and replaced by people asking AI instead.The sale of StackOverflow by the original owners to private equity for $1.8bn in 2021, just before ChatGPT launched will go down as a masterstroke of either foresight or just good luck, a bit like how Myspace was sold by founder Tom Anderson for $580 million (most recently sold for $35 million and, after that, valued in the low tens of millions of dollars.)Any developer who does not make use of AI will find their performance isn't as good as those who do... I guess it will be a bit like the holdouts who kept using slide rules and pen and paper instead of scientific calculators and computers. Like any tool, you can misuse it, vibe coding is a good example, there are others. But I am finding it helps my productivity, it helps solve problems that I have and it is something I would probably pay a small amount for (say $20/month) if it wasn't free. I don't see it as a danger to my careeryet, but it can definitely create novel works, and it might be a problem in the future for the type of software engineers who are only average and can work entirely remotely. I think for hardware engineers, since you need to interact with actual, physical things, it's not a threat yet and may never be within our lifetimes, but predicting the future accurately is really hard.

author: Nominal Animal
author_rank: Super Contributor
timestamp: June 07, 2025, 08:34:04 pm
content: Quote from: Analog Kid on June 07, 2025, 08:09:44 pmI wouldn't saythat. macOS is pretty nice, as are the various BSDs, especially FreeBSD. And for Linux, you have Android (non-Unix userspace with Linux kernel only) and even POSIXy distributions without systemd likeDevuan. The variety among Unixy/POSIXy systems and even in Linux distributions is quite wide. For example, FreeBSD is quite particular as to what software it includes, but due to fewer developers participating and contributing, evolves much slower.I'm not a zealot myself. Even the computer I'm typing this on does have systemd installed, even though it is not an optimal solution. Hell, this machine itself was a compromise, limited by what I couldafford. Nevertheless, I do see the Linux desktop/userspace environment software quality dropping particularly due to poor software design, and I am exploring on possibilities how I could help with that. (One of these is a replacement standard C library, that would push users towards better interfaces by simply not providing the horribly poor ones. POSIX C itself provides many useful ones, likescandir()/ftw()/glob()/iconv()/regexes et cetera, that many/most do not use because their C education excludes POSIX (because Windows). Another is better systems integration engineering.)For anyone considering making their own distro, or otherwise interested in systems integration, or just wanting to find out why software and OSes are so full of unnecessary cruft and how to avoid that, I do recommendLinux From Scratch(and Beyond Linux From Scratch). It is a book describing how to build by hand all the software needed for a fully featured Linux OS from bare sources. It is lower-level than saygentoo, and I do not suggest it as a way to get an optimal OS for you (which some do use Gentoo and other Linux distributions for); only as a practical learning tool. For me, over a quarter of a century ago, it opened up some real understanding of how the entire system works and gels together.

author: Nominal Animal
author_rank: Super Contributor
timestamp: June 07, 2025, 08:46:32 pm
content: Quote from: tom66 on June 07, 2025, 08:19:28 pmOnly if you measure performance by volume (of code or features), and not by reliability or robustness or fitness for purpose.I'm saying that most people do measure performance by volume of features, and aren't interested in paying for reliability or robustness. However, that does not mean reliability and robustness are unimportant; in fact the opposite. For the narrow niches where they are important, are exactly those that are silently keeping our societies working.In Finland, the building industry went this way a bit over half a century ago. Gone is the personal responsibility, replaced with long subcontractor chains with nobody taking responsibility or pride in anything, and the perennial search for lowest cost and maximum short-term profit. It resulted in pretty low quality houses in a country where outside temperatures vary between -40°C and +30°C each year (-40°F and +90°F), with mold and related health problems very common. Nobody dares even explore the connection with our high cardiovascular disease rates; we just assume it has something to do with animal fats, and concentrate funding on proving that. The energy efficiency demands are such that the materials used in most houses must have structural air pumps to keep the structures dry, or they will be uninhabitable within a few weeks. Yet, the stone apartment buildings built 100-150 years ago in Helsinki with their 3m tall rooms fulfill even the most stringent energy efficiency requirements of today, due to the sheer thickness and mass of their stone and concrete walls; plus their acoustics (acoustic insulation) is superb, even moreso if a floating concrete slab floors are used (which the structures can easily handle). Thosecould be built today too, making tenantsmuchhappier and much more comfortable, noise pollution being a huge issue; but it just isn't cost-effective anymore. This is exactly what will happen to software, too.

author: Nominal Animal
author_rank: Super Contributor
timestamp: June 07, 2025, 09:09:33 pm
content: Also, I hope you all understand that most of EE design work is not that much far behind.

author: tom66
author_rank: Super Contributor
timestamp: June 07, 2025, 09:37:32 pm
content: Quote from: Nominal Animal on June 07, 2025, 08:46:32 pmBy use of AI, I mean using AI to solve problems and answer questions, not necessarily to generate code wholesale. I think that's actually quite a way behind, it turns out that AI models are pretty bad at maintaining and managing larger code bases. The meme going around is "I got Anthropic to refactor my code base. It created 22 new files, reordered hundreds of functions, added more comments in. It doesn't work any more, but it'sbeautifulat least". The problem is that the context windows for these models are quite small and the larger the context window gets the more inaccurate the model becomes. It will certainly be solved, but it will take time.Quote from: Nominal Animal on June 07, 2025, 08:46:32 pmI think this is arguably false.Companies like Apple and Microsoft spend a huge amount of effort on making reliable software. You might not see that because you encounter bugs, but that doesn't mean that a lot of effort wasn't spent on testing and bug fixing. The approach nowadays is to use CI/CD pipelines, essentially doubling the amount of work involved, by writing both a test case and writing the actual software. One application AI is seeing a lot of use in is creating those test cases against a specification or reference code, and that's something where the test case itself can be usually proven to be formally correct and it can be guaranteed to be bug free there.It turns out that customers don't really enjoy using buggy software and where they have a choice, they -will- move. No matter how much effort you put into this, though, bugs will still sneak through; some odd software configuration, an unusual hardware platform, an unseen and untested sequence of events. I think it's probably true to say that Windows has never been more stable; I remember in the early 2000's having to frequently reboot XP, and reconfigure and reinstall it. Vista was a barely-mitigated disaster; but, more recently I ran a Windows 10 install for half a decade with no significant issues. My biggest gripe with Microsoft now is that Teams is rubbish, but I think that's because it's trying to do too much.The biggest issue with AI will be it doesn't really understand anything yet (not until we are at 'AGI' type levels). So it creates trivially buggy and incomplete code that doesn't mesh well with existing code. It is good where there is a small context window and a lot of relevant training data, but it sucks outside of that area. But if it's tested via a CI/CD pipeline or similar, the bugs will get found, so no one will really notice the vibe coders.There are some areas where bugs are intolerable, like for instance nuclear reactor control software. It isn't sexy or interesting so probably no one really pays much attention to it, but it will remain human written for decades because that will just be an engineering requirement.Quote from: Nominal Animal on June 07, 2025, 08:46:32 pmMaybe, but to be honest I wouldn't be that upset about having schematic and PCB flow guided by AI. If I could say to the AI "build a buck converter on this board using TPS65261 chip, selecting components available from Digi-Key that are in stock, design it for low cost" etc., I would be quite happy for that. I do not really enjoy that part of the work. I like the overall architecture, the selection of key components, the bringup, test and the human interaction with requirements and specification capture. That will remain human driven as long as AGI is not here.And if we do have AGI, that becomes an extinction-level concern, because it might start worrying about humans turning it off, and we don't know what it might do to stop that.

author: Analog Kid
author_rank: Super Contributor
timestamp: June 07, 2025, 09:45:54 pm
content: Quote from: tom66 on June 07, 2025, 09:37:32 pmIsn't "AGI" just another term for the nonsensical "AI singularity" that E. Musk and other sci-fi fanbois are warning us about?

author: tom66
author_rank: Super Contributor
timestamp: June 07, 2025, 10:37:55 pm
content: Quote from: Analog Kid on June 07, 2025, 09:45:54 pmNo, that would be something like ASI, or artificial super intelligence.Artificial general intelligence is the current goal of AI researchers, which is more or less a computer/robot doing anything a human can do, being able to freely think, plan tasks and have executive function. It is not clear whether or not that requires conciousness or sentience. It is also not clear how we will know we have met AGI; some people already argue LLMs combined with image and sound models are close enough to be called AGI lite (most of them can now pass the "Turing test"), but others argue until the AGI can do something like, for instance, walk into an average American home and make a cup of coffee ("Wozniak test"), it won't be close enough to be called AGI. It is also not clear if AGI is even possible with the current approaches, for instance, AGI would imply a neural network that is self-learning, and every LLM is currently manually trained which is extremely resource intensive.Both AGI and ASI are dangerous for their own reasons, but it's hard to see ASI as being anything other than an extinction-level event, AGImightbe safe (but how would we know...?)

author: abeyer
author_rank: Frequent Contributor
timestamp: June 07, 2025, 10:58:11 pm
content: Quote from: tom66 on June 07, 2025, 10:37:55 pmExcept isn't that exactly what the techofuturism optimists argue? As soon as your AGI can do everything humans do, that includes coming up with new better AIs... and at least in theory their ability to iterate on attempts faster means they'll quickly outpace humans in doing so, leading directly to the ASI singularity.

author: Nominal Animal
author_rank: Super Contributor
timestamp: June 08, 2025, 12:31:03 am
content: Quote from: tom66 on June 07, 2025, 09:37:32 pmAnd I am saying that distinction is meaningless.Quote from: tom66 on June 07, 2025, 09:37:32 pmNo, they do not. Backwards compatibility, for example, is of much higher importance. "Patch Tuesday" wasn't athingbefore Microsoft needed one. Apple spent a lot to develop original MacOS, but for X, they heavily relied on open source development (BSDs and Mach microkernels), afterwards till today slowly closing sources and reducing their own interaction with open source projects,because it fits their marketing better.Reliability isn't much of a concern. Everything can be fixed in the next release, after all, if the users become too noisy. It just isn't a target; user capture and market share is. What you seem to think as a primary concern is simply a secondary result of high importance of market pressures, especially now that anticompetitive measures tend to get lots of unwanted attention from various governments.Quote from: tom66 on June 07, 2025, 09:37:32 pmThis is simply a consequence of having an emphasis on the production volume and not quality and reliability. It allows higher production from lower skilled developers, leaving the higher-skilled developers to fix the profit-impacting bugs.I am saying it makesperfectbusiness sense to do this, but it provides almost zero pressure to make the software more robust, more reliable, or more efficient.Quote from: tom66 on June 07, 2025, 09:37:32 pmDoesn't matter. What matters is what customers are willing to pay for. When you capture entire organizations, so that end users don't make the purchase decisions, you don't actually need to worry about the end users at all. In fact, you can actually bolster your business by training local support staff for your own software, having the organizations pay their salaries.The trick is to have the perception of fewer bugs and annoyances than competing products. There is no pressure to do better than that.Quote from: tom66 on June 07, 2025, 09:37:32 pmCurrent model, the LLM substrate if you will, is not compatible with the concept ofunderstanding.Yes, I know I sound like a luddite to many AI/LLM enthusiasts, but thing is, I also know how these work. Yes, it is wonderful tech, and if it were used for different purposes, I'd probably be writing software to enhance the underlying engines and mechanisms especially for hobbyist/testing/scripted use cases. I not only know about the practical implementation, but also the theory and development of the theory and models (although I'm most familiar with just the last four decades of development, as I personally first encountered the actual implementations via trainable Optical Character Recognition in image scanner software in 1990s).To add "understanding" to the output of an LLM, you basically create a filter that recognizes "non-understanding" and rejects the LLM output when it detects that. This has the same problem that trying to enhance the robustness and reliability and efficiency of code by post-hoc verification. This stuff –– just like security and many other things –– cannot be added on top later on; it has to be considered and "baked-in" from the get go. Adding testing and verification phases doesn't make the original code any better, it can only detect and help reject the worst offenders. You still have the same limited-quality initial output; no amount of post-filtering can help the output exceed that limit. It's like trying to use moonlight with a huge lens to concentrate enough of it to light a fire: it just won't work, even if you feel it should.Quote from: tom66 on June 07, 2025, 09:37:32 pmHowever, that part (that you do enjoy) requires much less domain-specific education, so at some point, it becomes commercially unviable to hire experienced EEs to do that part, because a fresh new graduate can do it just as well or better. It might even make sense for schools to start training for that part only, reducing the course load, allowing higher throughput and less financial strain; plus lower general problem-solving skill is required if social skills are sufficiently well developed.Quote from: tom66 on June 07, 2025, 09:37:32 pmA rhetoric question: What exactly is the difference between having children, and creating an actual general intelligence artificially?If you end up with concepts like "upbringing", "culture", "moral values", et cetera, then observing our current societies indicates we're not doing that good a job at it even with human children.

author: paulca
author_rank: Super Contributor
timestamp: June 08, 2025, 07:33:43 am
content: From my 20 years writing software professionally, the worst software I have seen by and far has been in the embedded space.Period. I "could" prove it, but to do so would be tedious and there in lies the point. High quality, embedded development is tedious, long winded, expensive, slow and extremely documentation heavy. Just like almost all high quality software development.So very few embedded developers bother. The lower on the dollar scale you get the less likely you will find any testing beyond manual end-to-end. However the big dollar in house embedded development platforms are, well, in house and proprietary. So there are very few freely available tools for said quality control. So without that, without basic introspective testing, unit testing, soft-harnessing, automated tests etc. etc. Without recording all the output of those over time, you simple have no "Measure" of your quality. You have "No quality engineering". When it comes to the code.There is your reason right there. The vast majority of code in the embedded space is 100% untestable. It would NOT pass the first peer review in a professional setting.I find it a bit of a gall for that industry to throw salt at mine. It angers me because the ratio of effort in my day job is about 80:20 with the 80 being testing. It takes 4 times longer to write all the tests than it did the code. Yet I honestly have yet to see a single unit test on a forum like this.I see embedded code with cyclometric complexities into 3 figures and not one single unit test, when 100s are required.So, if you want to take "Quality engineering" when it comes to code, you wanna go at it? Get the gloves.Put into brass tacks. If a C/H file comes into a code review for me... I don't just want to know that it works. I want to see the code in the same pull request which PROVEs that it works, automated as part of the build.2 points... out of 10. Nice try. Come back later.

author: madires
author_rank: Super Contributor
timestamp: June 08, 2025, 11:20:13 am
content: Quote from: tom66 on June 07, 2025, 09:37:32 pmAnd now the reality. Their goal is to make as much profit as possible, not to write reliable software:- tons of zero days- postponing fixes- downplaying and ignoring security issues- admins praying on Microsoft's update Tuesdays (that updates won't break things again)- impelling users to fix problems caused by Microsoft's updates (e.g. resizing Windows RE partition)Microsoft has become really bad over the last decade or so. Apple isn't as bad, but is following suit. I'd call that computer sabotage and not reliable software.

author: tom66
author_rank: Super Contributor
timestamp: June 08, 2025, 06:01:25 pm
content: Quote from: abeyer on June 07, 2025, 10:58:11 pmOnly if the compute power and energy allows. Energy is a critical limitation, so much so that Meta/Facebook announced that they are integrating a 30MW nuclear power plant into to one of their datacentres, and OpenAI are going to open a solar-and-nuclear powered datacentre in UAE.There are so many unknowns about AGI and LLMs right now. It seems that the larger you make the models, the 'smarter' they seem to become (within some kind of limit), but ... that's clearly not scalable and it doesn't appear to be anything close to a linear function. It costs OpenAI around $0.30 per question asked to ChatGPT right now. If the model that emulates human intelligence is, for argument's sake, 100x larger than that, then it isn't going to be feasible to run that on current generation hardware and it isn't going to be feasible to use it for actual work. And no matter how much effort the AI spends on "new ideas", it won't be able to solve those fundamental limitations for decades. The techbros seem to miss that some things are not solvable by throwing more resources at it because there are inherent resource or technical limitations. A bit like how nine women can't make a baby in one month.

author: tom66
author_rank: Super Contributor
timestamp: June 08, 2025, 06:20:50 pm
content: Quote from: Nominal Animal on June 08, 2025, 12:31:03 amIn what way?The other day I had a strange error with my compilation. I wasn't super familiar with the area of C++ I was working in, so I copied in some code context (about 10 lines either side of the error) and the error message and ChatGPT solved the problem within seconds. The alternative would have been five minutes of Googling and scratching my head and maybe browsing Stack Overflow. Worst case I might even have to answer a question only to get berated by the mods because it didn't show up on the first search. I think it's a completely legitimate use of AI.Vibe coding, and refactoring entire code bases with AI, those can both get in the bin. But used appropriately, LLMs are a significant boost to productivity, for me at least.Quote from: Nominal Animal on June 08, 2025, 12:31:03 amIt's clearly true given how complex something like iOS or Windows have gotten yet bugs have not risen at the same rate as code complexity has increased. I remember using my first-generation Android phone, which would crash and have memory leaks like nothing else. Even the native apps like the camera would crash from time to time. I've not had that with newer devices. I am not saying current generation devices are bug free but I do think it is the case that software is better than it once was.Quote from: Nominal Animal on June 08, 2025, 12:31:03 amI would agree that some companies do see software/OTA updates as a get out of jail free card, preferring to release -anything- rather than test for longer. And, that is a bad practice. The best suggestion I can make though is that being an early adopter ofanytechnology is always painful and it's better to wait for the 2nd or 3rd generation of anything before buying. Some issues only become obvious in the field.Quote from: Nominal Animal on June 08, 2025, 12:31:03 amAs long as AGI remains out of reach there will always be a place for someone who has the ability to solve a problem. I may well not know how to write some software for a new chip I've never heard of, but I can learn. That is what makes a good engineer, not only having knowledge about Ohm's law. Taking some of the drudgery out of a project like being able to automate design reviews and the boring parts of design would only make me happier. It's essentially what a manager does, but for the time being management has been something I have avoided because it does not appeal to me. If I was managing an AI, instead of people who have annoying issues like sick leave and HR problems, which I have zero interest in having to manage, then it would make the job a lot more enjoyable.And I think to some extent if you go back and look at what CAD has done for mechanical and electrical engineering as just one example... this is what the job of a draughtsman looked like in the 60's...(all those lower back problems!)Now it's all done on a computer, so a small engineering team can be responsible for so much more, and be considerably more productive. Has it led to a loss in jobs? No, if anything, engineering has increased in employment (by about seven-fold looking at the stats for theUSA).I think AI will mean much the same thing. One engineer will be able to produce more as a result of leveraging resources to make them more productive.Will we get fairly compensated for that additional productivity, now that's another matter altogether...

author: vad
author_rank: Frequent Contributor
timestamp: June 08, 2025, 09:25:03 pm
content: Quote from: tom66 on June 08, 2025, 06:01:25 pmI asked ChatGPT whether this estimation is accurate, and it responded that it is off by 3-4 orders of magnitude. It provided the following reasoning:Generating a short answer of around 180 tokens requires an estimated 18-90 trillion FLOPs, depending on the model. The NVIDIA A100 consumes approximately 0.1 nanojoules per FLOP, and assuming 100% overhead (for cooling, memory access, etc.), the total energy required would be 3,600-18,000 joules, or 1-5 Wh. At an average US wholesale electricity price of $0.03 to $0.05 per kWh, the energy cost would be approximately $0.00003 to $0.00025.

author: Nominal Animal
author_rank: Super Contributor
timestamp: June 09, 2025, 02:53:50 am
content: Quote from: tom66 on June 08, 2025, 06:01:25 pmYes – although I might be inclined to replace 'smarter' with 'more capable'.I do believe that it is perfectly possible for a neural network to become truly intelligent (in the AGI sense, or psychological g-factor sense) and sentient. Whether our current implementations (with their inherent limitations like node state limited to 2⁸ states or less) can do so, I do not know; I am not ruling that out, however. Considering how intelligent e.g. corvids are, I do believe sentience and true intelligence can be achieved with much smaller complexity than e.g. the human brain has.The problem I have with LLMs and current "AI" is related to how people believe that evolution makes animals stronger, more intelligent, and overall "better"; or that correlation is equivalent to causation. Or that self-preservation is somehow an indication of intelligence, when even bacteria actively avoids dangers.The way we construct LLMs and "AI models" does in no way select or push for "intelligence"; quite the opposite. We only push the models to produce plausible-looking output, that's all. We are creating imposters, pure and simple. I don't think it is an inherent limitation of the technology, nor is it the models' fault; we're the ones shaping them this way.

author: u666sa
author_rank: Frequent Contributor
timestamp: June 09, 2025, 06:45:45 am
content: Here is the exudus of moses from egypt made in selfie stylehttps://t.me/defensepoliticsasia/13074

author: u666sa
author_rank: Frequent Contributor
timestamp: June 09, 2025, 06:48:06 am
content: Same selfie style movie but now it's star warshttps://t.me/defensepoliticsasia/13075

author: tom66
author_rank: Super Contributor
timestamp: June 09, 2025, 08:41:23 am
content: Quote from: Nominal Animal on June 09, 2025, 02:53:50 amI believe OpenAI is using 16-bit model (half precision) for their LLMs. 8-bit is more common in video and image processing since we usually use 8-bit images natively so they might be using those for images. But OpenAI hasn't been public about any of their model designs since GPT-3.5, i.e. first generation ChatGPT, so this is all speculation.The biggest breakthrough will be when a model can learn and train itself. Currently models are trained in an excruciatingly slow process by humans and reinforcement learning, as you state, producing plausible looking output. They require ever greater amounts of training data to do this, which is leading some AI scraping bots to drive websites to collapse (this has led to tools like Anubis being developed). If that becomes possible, I think true AGI is very close indeed, though it may still not be practical if the models are too large.

author: paulca
author_rank: Super Contributor
timestamp: June 09, 2025, 10:04:22 am
content: Quote from: vad on June 08, 2025, 09:25:03 pmIt has reasoning modules, however I have found holes in it.ChatGPT seems to suffer from "The Dougals". Anyone who has watched father ted might get the reference, "Small - Far away" when trying to explain to Dougal why the cows in the field outside are the same size as the toy ones on the table.So, when it is reasoning with a large spread of orders of magnitude, while using only 1 or 2 significant figures, it makes me uncomfortable in trusting it. A single increment change to any of those figures produces a radially different value. So I would like to see more than 1 or two significant figures.EDIT: I ran ChatGPT into the ground last night trying to get an assembler to do something it can't really do. It told me to try "Approach A", that didn't work, so we went with approach B.... when we got to approach E however and I prompted it again, it just reset back to summarising the options we had already tried.It was convinced that ALL of them worked. None of them would every really work, except the one I told it I didn't want to do... the long hard prescriptive leg work way.EDIT: It was also quite out of date. You might expect that something so "set in stone" as "retro computer architecture and assembler" could have been "optimised" out in the update webcrawls. It's "vocabulary" in terms of modern sjasmplus assembler was decidedly lacking and when prompted with "new information" it then resorted to "Web search mode"

author: paulca
author_rank: Super Contributor
timestamp: June 09, 2025, 10:12:35 am
content: On a different note. Try "Co-Pilot" with something it can't google.I created a Uincode (UTF-8) string containing 31 pipe delimited text or number fields. The fields we as randomly selected garbage as I could make up.I pasted it to the bot and asked...."How many pipe characters are there?"It was confident there were 34 pipe characters.I told it to recheck and it said there were 35 characters.I explain to it how to do this check and count them properly and it agreed and told me there were 36 pipe characters.I told it there were in fact 30 pipe characters and 31 fields.It said there were 36 and it would recheck if I wanted it to. I said, "I expect you will just tell me there are 37 pipes now."But no... it stuck at 36.I asked it if it could place this quote: "There are four lights!" and it correctly identified the TNG episode. However it did not identify the irony.

author: madires
author_rank: Super Contributor
timestamp: June 09, 2025, 11:08:13 am
content: And now imagine someone from US DOGE feeding data about some agency/department's employees to GROK and then asking for a list of employees to be fired. What could possibly go wrong?Joking aside, the lesson is that we have to verify the pseudo AI's output.

author: paulca
author_rank: Super Contributor
timestamp: June 09, 2025, 11:30:33 am
content: Quote from: madires on June 09, 2025, 11:08:13 amWhich goes back to the advice I work with and suggest.... for professional use ask it for things you already know the answer to and are just being lazy. That and/or things you can empirically test the results of. Even if it helped write those tests. Thankfully they seem to hold no "delayed deception" or attempt to cover their mistakes.... yet.