skysight-inc/HackerNews huggingface dataset:
Well, that's why language paradigms are a thing - if you are not familiar with any language in the logic paradigm but are an expert in the OO-paradigm, this could take a little bit to wrap your head around. Triska is an excellent teacher of Prolog, be sure to check out his videos linked.
Looking Back At 2024 AT Protocol Development
Emergent properties are nice. They show CoT now, but who knows if there is a better planning strategy? Second thing is it kind of implies every base model can be increased in capability just with some RL tuning, cheaply. So in theory you can plug in every observable and quantifiable outcome beyond math and coding(stock returns, scientific experiment results?) and let it learn how to plan it to solve it better. Train on Observed effects of various drugs on people, it then creates a customized treatment plan for you? Sft version would be limited by doctors opinion on why certain drugs affected the outcome, whereas RL version can discover unknown relationship.
> Impressive numbers, but have you ever tried to use one of these things to get actual work done? They're terrible at it!

If you mean "have you tried using an LLM like ChatGPT or Claude for doing development work", then you're wrong.

I'm very confident in saying this, both because I personally use AI for programming and get a lot of value from it, and also because almost everyone else I know in real life also uses AI for programming.

But also because there are dozens/hundreds of accounts of very good developers getting a lot of value from AI in their work.

So at this point, insisting AI products are terrible doesn't say much about the AI products, so much as it says something about your ability to get value out of them.
Okay then I guess I must've gotten that one wrong too, since I always imagined Switch is slightly larger than GameBoy Advance or PSP.

(They really need to start adding bananas for scale for to ads for those devices. Or I need to watch more ads; the few photos I saw gave me the mental picture of a PSP-sized handheld.)
Ask HN: What do you use for content moderation of UGC?
My co-founder and I started a static site hosting platform. From our past experience in user-generated content, we knew we needed moderation. So, we wrote a very simple script that checks for common phishing attempts and alerts us.

However, this simple script does not catch some of the more advance phishing sites and it doesn't catch other types of content that we can't support on our platform like porn.

Curious if anyone has tips and tricks for content moderation? We're still going to be manually reviewing sites because we haven't reached a scale that makes that impossible. But automation is nice.
It depends. Sometimes I feel that OAI performs better, and sometimes deepseek does.
Sometimes customers just can't grasp simple concepts, and people are morons who don't understand how really great Google products are. /s

A Pissed Off Tutorial For Google Wave:

https://www.youtube.com/watch?v=4Z4RKRLaSug

In the long term, Google's better off focusing their efforts optimizing the AI and UI behind their "I'm Feeling Lucky" button.
book bans now totally cool, says Dept. of Education.
The Best and Worst Airlines of 2024
Gift link: https://www.wsj.com/lifestyle/travel/best-airlines-2024-delt...
Cool, thank you. It feels like Athena + S3 Tables has the potential to be a very attractive serverless data lakehouse combo.
I think this mischaracterizes the state of the space. Iceberg is the winner of this competition, as of a few months ago. All major vendors who didn't directly invent one of the others now support iceberg or have announced plans to do so.

Building lakehouse products on any table format but iceberg starting now seems to me like it must be a mistake.
I don't lose any editor state, at least nothing I care about.

In my configuration vim will save (among other things):

- Cursor position

- Undo history

- Register state

:term is clunky for me, mainly because my muscle memory is to just :wq

I got it working as seamlessly as I could once just in an attempt to use it but I stopped pretty quickly.
It's a biased viewpoint, but it's not nostalgia. The following all happened to me:

- 486 Packard Bell that I upgraded ram from 4MB -> 12MB as a kid? Win 3.1 went from being slow period to Windows 95 being fast any time I didn't touch disk or CD-ROM.

- ZSNES on Pentium MMX? Zero lag gameplay with time-travel debugging and full memory view.

- DOS running on a Pentium 4 to support legacy software? Nearly instant everything, especially power on -> usable machine.

You'll notice a common thread. It was possible to outrun the demons of sluggishness back then.
For that there is ra-multiplex (to which I contributed sockets support).

I don't use any other LSPs which have a long warmup time, but if I did then they can also be used behind ra-multiplex.
Most accurately, lab leak and spillover event are not mutually exclusive theories.
For home use hard drives seem to be about the same price, but much more convenient and take less space.
It is no myth. Go try a Windows 2000 system and compare it to today. Windows 2000 will respond a lot faster (often instant), even on complex applications.
Halliday AR(Not?)/AI Glasses
No, the debugger does not get involved in preprocessing. When you write "a = __LINE__;", it expands to "a = 10;" (or whatever number) and is compiled, and the debugger has no knowledge of it. Debugging information, including the mapping of positions in the code to positions in the source, is generated by the compiler and embedded directly into the generated binary or an external file, from which the debugger reads it.

The __LINE__ macro is passed to the debugger only if the program itself outputs its value, and the "debugger" is a human reading that output :)
Re: losing focus: Maybe this a problem with tap to click on a touchpad? This happens to me and drives me crazy and it's invariably me inadvertently clicking with my palms. Disabling tap to click helps a lot.
Part of the skill in using these tools is recognizing when it spins off the rails and backtracking immediately. Most of the time something can be gleaned from that wrong approach which can then guide further attempts.
Best RTS for me, by far.

10x more playable than SC2.
Where is the $10 purchase link?
It was still big up until the 70's at least - I remember the huge Miner's Galas in Durhan, attended by people like Harold Wilson, Tony Benn and Arthur Scargill. There are still lot's of former miner villages in the area that don't look like they've changed much. Maybe my comments on steel & ship building are equally dated(?), but I think it was coal driving these related industries that got the north entrenched as a poorer working class part of the country. Of course there is also the fishing industry and sheep farming due to poor quality land, again all low paying jobs.

One of the best predictors of individual financial success is the wealth of your parents, and I wonder how many generations this effect lasts for ...
> But after that, it was an endless loop of the LLM adding logging code to find some bug and failing to fix it, only to add more logging code and ineffectual changes and so on. The problem is that even after it's lost at sea, it's still answering in a completely confident and self assured tone, so when you decide to take matters in your hands you might be too far gone from sanity and have an unfixable mess in your hands.

I wonder how much better or worse things would get, if we took the human factor out of the loop. Give the LLM the ability to run tests and see the results, then iterate on its own output and branch off with different approaches, gradually increase the temperature etc.

Maybe it’d turn out that you need 10 LLMs running in parallel for an hour to fix something, or perhaps even a 100 would never stumble upon a solution for a particular type of problem. And even then I wonder, whether it’d get better if you fed it your entire codebase or the codebases of the entire libraries or frameworks that you use (though at that point you’re either training it yourself or are selectively finding and feeding the correct bits not to exceed the context).
I tried to find some technical details, but there is nothing on the tutorials page. The press page links to a few articles in French, but all I found was that there is that there is no 4G, and "Circuit artisinal fonctionnel" on a diagram.

It would be great to know how it compares with other DIY phone projects like ZeroPhone.
This reminds me of something Dijkstra wrote almost 50 years ago in On the foolishness of "natural language programming [1]:

> When all is said and told, the "naturalness" with which we use our native tongues boils down to the ease with which we can use them for making statements the nonsense of which is not obvious.

Although this is obviously not about LLMs, its astonishing how many parallels can be drawn to today's usage of AI systems.

1: https://www.cs.utexas.edu/~EWD/transcriptions/EWD06xx/EWD667...
Elon Musk, Video Game King? Well, Maybe Not
Agreed: Worked on a tough problem in philosophy last night with DeepSeek on which I have previously worked with Claude. DeepSeek was at least as good and I found the output format better. I also did not need to provide a “pre-prompt” as I do with Claude.

And free use and FOSS.

Yep, game changer that opens the floodgates.
Back in early 2023 I tried to write a tool to do my taxes based on my broker CVS files. Since I wasn't familiar with how the data was structured, I let the LLM lead me while building this in incremental steps. The result was not just buggy, it simply failed to detect the relationships in the data (multiple somewhat implicitly embedded tables that needed to be joined). Even after I pointed this out, it failed to handle it, getting stuck in the same kind of loop you described.

To this day, no LLM that I tried passed this task of leading the development while detecting the underlying structure of the data.
I mean, in this case we're talking about emoji, so I'm having a hard time picturing the criminal use, but in general anonymous file uploads or text uploads absolutely get used by criminals as soon as they're discovered. Anyone who's run a service for long enough will have stories of the fight against spam and CSAM (I do!).
High-perf brain–comp interface:finger decode/quadcopter control—paralyzed person
There is the story that von Neumann flew off the handle the first time he saw an assembler.

That was in the 1940s when labour was very cheap and compute was insanely expensive. We’re talking hundreds to thousands of programmers’ salaries for the cost of one computer.
I'm a college prof in the US and know that term.
I don't use tabs, sometimes I use split windows (usually only when vim-diffing), mostly I use multiple terminal windows in a tiling WM. I do use multiple buffers but I usually don't care about editing more than one or two at a time and it's easy to re-open these whenever I need to.
Anyone who has ever worked with VCs or shareholders before knows that, if you tell them the reality and limitations of something, they will either fire you or ignore what you say. They have been desperate to remove the leverage programmers have due to their skill and replace us with AI that they don't have to pay salaries to. All we can do at this point is just take VC money promising them exactly what they want to hear, that they will be able to replace us with a NLP model. Sometimes you just can't save people but you can profit from their voluntary fall from the cliff?
Not everyone is the same, but I have a different view of programming that what you describe. Most tasks involve thinking about the domain and what implementation techniques to use while trying to reduce the technical debt in the project. For the domain, I talk to people, rely on past experience (mine or others), or do research. For implementation techniques I look at other people’s code, read books, or ask someone more experienced. Both are heavily influenced by the context, aka what already exists in the project and the constraints that I have to deal with. I heavily distrust LLM because it cannot assimilate the context like an experienced person and provide me direction based on experience. Why experience? Because the problem and the constraints always exist in the real world.
>Men in general don't like being given advice, rarely seek it and when they do, they are explicit a put seeking it.

What? Certainly not my experience, in either direction.
The way to get better is to do it a lot. Every time you dig through a problem to solve it, you're not just learning about that problem - you're learning about every problem near it in the problem space, including the meta-problems about how to get information, solve problems, and test solutions.

In a sense you're slowly building the LLM in your head, but it's more valuable there because of the much-better idea evaluation, and lack of network/GPU overhead.
Is it? Python requires twenty times more computing time to solve the same problem. You could argue that there are much more browser JS users than python users. I don't have the numbers, but I guess with all the deep learning number crunching, the Python share is quite significant. Or what is your assumption based on?
The way it looks reminds me of the Handspring Visor[1] for some reason (with less buttons).

1: https://en.m.wikipedia.org/wiki/Handspring,_Inc.
The hype in some areas is around replacing coders, which is a fantasy without orders of magnitude better systems.
Am I the only who finds this article to be inaccessible due to color choices and implementation?

I'm really interested in Prolog, but my eyes feel the strain after a few sentences. The reason is that the contrast ratio of some parts is very low, of others excessively high. The constant alternations between these extremes intensifies the effect.

The page looks shredded in Safaris reader mode, so that's no help either.
In the USA since 2010, there have been standards that prohibit ads being louder than the program material:

https://en.wikipedia.org/wiki/Commercial_Advertisement_Loudn...
This is my experience with Aider. When I first started using it, I turned off the auto git commits, but I’ve since turned them back on because they serve as perfect rollback points. My personal style is only commit once I have a feature fully working but with Aider it's best to have it commit after each exchange.

I've gone 2-6 steps down a path before realizing this isn't going to work or the LLM is stuck in a loop. I just hard reset back to the first commit in that chain and either approach the task differently or skip it if it wasn't really that important.
OpenAI is bust and will go bankrupt. The red flags have been there the whole time. Now it is just glaringly obvious. The AI bubble has burst!!!
Gerrymandering can simply be looked up in a dictionary or on wikipedia. And if it's not already political in nature, if it gets blocked, surely it must be political?
Number changes with every refresh though.
My experience has been the opposite, I found cursor to be an improvement over comparable tools such as aider.

I was able to write a plugin for ComfyUI (a 60k loc python/js codebase) in 2 hours thanks to semantic search. It's not an exercise I'm versed in.

It wasn't that different from the kind of internal monologue I'd have held in my head had I done it on my own, including misguided confidence that gets crushed 5 minutes later as you read other parts of the code that show you had the wrong understanding of how it actually works.

In this context, LLMs can be very useful because a ground truth already exists to compare their replies against.
That's obviously wrong, as demonstrated by the engineers invested in building tools to enable that.
While I agree its real competition are we so certain that R1 is indeed better? The times I have used it, its impressive but I would not throw it a title of the best model.
I don’t remember how we debugged it at the time, but I’ve run into very similar symptoms that were caused by clock skew between client & servers. Increasing the validity window to both past & future by a longer period helped resolve it.
Or PR happy talk.
I don't think it is an illusion. It can remove a lot of barriers to entry for some people, and this is probably what you're seeing in the anecdata.

For example, my brother. He is what I'd refer to as 'tech-aligned' - he can and has written code before, but does not do it for a living and only ever wrote basic Python scripts every now and then to help with his actual work.

LLM's have enabled him to build out web apps in perhaps 1/5 of the time it would have taken him if he tried to learn and build them out from scratch. I don't think he would have even attempted it without an LLM.

Now it doesn't 'code everything' - he still has to massage the output to get what he wants, and there is still a learning curve to climb. But the spring-board that LLM's can give people, particularly those who don't have much experience in software development, should not be underestimated.
It didn't when I set it up, but I haven't removed the keybindings to test if this has changed recently.
Hey Guys, I just created a webapp + chrome extensio n for easily accessing dynamic and AI generated Snippets across different websites. I am looking for some feedback on how to grow the user base and what features to implement
>Frontier AI systems have surpassed the self-replicating red line

https://arxiv.org/abs/2412.12140
What a sweet position to be in. All the upside of the potential stock valuation windfall while none of the downside of putting your career and income on the line.
It delivers debugging hell if you don't know what you do which is usually the case for inexperienced developers. It assists experienced developers very well who can sort through which parts of output are useful from the AI and which not so.
No judgement – I like them both. What is it about RA2 that you prefer to others? Also, YR or original?
It's funny that this is MIT licensed, expecting credit for uncopyrightable work.
There have been studies (in the 80s or 90s, I never wrote down references, unfortunately, but they probably involved lexical priming) that support that idea. They suggest that English keywords get a meaning of their own for non-native speakers.
This is indeed a massive exaggeration, I'm pretty sure the $30 experiment is this one: https://threadreaderapp.com/thread/1882839370505621655.html (github: https://github.com/Jiayi-Pan/TinyZero).

And while this is true that this experiment shows that you can reproduce the concept of direct reinforcement learning of an existing LLM, in a way that makes it develop reasoning in the same fashion Deepseek-R1 did, this is very far from a re-creation of R1!
He didn’t claim YC does this where others don’t, his gripe is with the narrative YC pushes and how they seem incongruent to how they currently operate.
Is there a Mac version yet?
I loved the domain name, once I figured out it was a reference to "watersheds".
How much did the hardware to train gpt4 cost?
that seems a bit harsh dont you think? besides youre the one making the assertion, you kinda need to do the proving ;)
There is no urban future, despite those who dream smart cities. The reason why it that dense urban areas can't evolve and consume MUCH MORE in the modern world than sparse areas even if most deny it and do not even try to compute the raw materials and energy an urban vs sparse area consume.

The future could be or a mass genocide to lower quickly earth population or an "urbanized" world of single family homes and sheds. That's why all who knows push "urban air mobility" which can't be in dense areas and can't be "collective" as well, because it's a way to reduce the need of infrastructure again and again.

We need a cluster world, not a mainframe one.
They just got 500 billion and they'll probably make that back in military contracts so this is unlikely (unfortunately)
I'm sure it's not better in every possible way but after using it extensively over the weekend it seems a bit better than o1-pro, which was my previous pick for the top spot. The best part is that it catches itself going down an erroneous path and self-corrects.
Agreed, Friston's Bona Fides are impressive. (Aside: His fame in neuroscience comes from him having written important FMRI software that everybody cites.)

That's also why I worked with his team and read a lot of his papers for a while.
His principal idea was originally that neurons perform free energy minimisation. This idea makes a lot of sense, once you understand what free energy means. But, to the best of my knowledge, it has not at all been empirically verified for neurons (I'd be delighted to be proven wrong in this belief). So he went the route of generalising the free energy principle: "the free energy principle asserts that any “thing” that attains a nonequilibrium steady state can be construed as performing an elemental sort of Bayesian inference".
Terms
"can be construed"
and "elemental sort of Bayesian inference" do a lot of work here. Updating and generalising one's research hypothesis is legitimate (albeit one could be more explicit about this), but it weakens the claim being made. Anyway, under a charitable interpretation of those terms, I agree that this is
true, but, at the same time doesn't say much. Indeed, under the
charitable interpretation it basically equates doing free energy
minimisation with existence. Friston has lately said that the FEP is
not falsifiable.
Take it from the horse's mouth (i.e. a Verses employee): "the free energy principle just applies to stones, it applies to birds, it applies to any kinds of animals" on Machine Learning Street Talk [1].

Here is my current position: from a mathematical principle this general one cannot derive scalable ML algorithms!

> he seems to have joined only in 2022, they were 4 years old at the time.

The company founders have a cryptocurrency and (later) metaverse background.

[1] https://www.youtube.com/watch?v=qxEfcrmTWO4
That's a different part of the implementation details. If you were to break the system into mocroservices, the model is a binary blob with a mocroservices wrapper and accessing web search is another microservice entirely. You really don't want the entire web to be constantly compressed and re-released as a new model iteration, it's super inefficient.
What I find interesting is that the project claims MIT license, but if it is "almost entirely" AI generated, I am not sure it even is copyrightable. So either the licensing terms deserve some large disclaimers, or it is not "almost entirely" made with AI. Based on the name I assume it is your project, could you shed some light on which of those two options is correct?
I guess you can go tell the military they are wrong, along with all the homeowners that have been arrested for shooting drones down with shotguns. You might want to do some actual research before just spouting off whatever you think when the facts don't support it. They even make shot shells designed to take down drones.

Yes shooting down a drone is an offense in the US, unless you're in law enforcement or the military in specific situations.

https://www.armyrecognition.com/news/army-news/2024/analysis...
> For example, I wouldn't manually rewrite localhost, I'd tell the AI "Why is localhost everywhere? Will this worker if I deploy to a droplet?" and it will fix it for you.

The solution is multi occur (emacs), quickfix list (vim), or any editors that have whole project find and replace.
That's still highly contentious, hence the "low confidence" the CIA assigned to their conclusion. There's apparently a lot of evidence for the zoonotic original, though I personally don't understand said evidence.
Politics and culture represent people's world view. That makes unemotional discussion very difficult.
Shitibank US account hasn't charged me in 25 years. Now they do. $15 a month.

May they go to hell.
It's also worth checking out the project that the creator uses it in: https://github.com/IQEngine/IQEngine