skysight-inc/HackerNews huggingface dataset:
> You can't hill climb tokens, but you can climb manifolds.

Could you explain this a bit please?
I don't understand. If you are trying to express something about the Atlantic, then just say it.
Two ideas you might like:

Debezium + Arrow Flight: Use Debezium as a library to grab PostgreSQL CDC events and stream them into Arrow for super-fast, columnar processing. Works great with Polars or DuckDB.

RisingWave: This is a lightweight stream processor that connects directly to Postgres CDC, lets you write SQL for transformations, and keeps everything updated in real-time. No Kafka or heavy setups required.
If this was a random blog post I wouldn't nitpick, but this is the Wall Street Journal.
Where did you pick up “toque”? I always thought that was a distinctly Canadian usage.
Should the Uvalde police sue the school for putting them through that trauma?
Yes, a lawyer could refuse your case after consulting them and their time considering the case.
But the energy density of nuclear fuels is so fantastic that it remains compact.

See

https://www.explainxkcd.com/wiki/index.php/1162:_Log_Scale
Why engineers don't test code
Thanks for sharing. Do you have an estimation of LoC? I know it's a BS indicator but just curious. I'd imagine it's something difficult but not too large.
Pac-Man for the Commodore Amiga: Writing an Operating System Friendly Game [video]
> In that example the constructor parameters were just moved

Not really. In the "Original" example there's no constructor in sight, as that's just a standalone procedural-style method, not a class.

The second one turns the method into a class.

> is there some cost

As GP mentions, this incurs mental costs: "In more complex classes, it’s often hard to even identify that this has happened. Is this permanent object state, or just an internal temporary variable that made it easier to leap around methods?"

In terms of performance, this depends on the language/runtime/type, but in general you'll get heap allocation instead of a stack, and it will use the GC.

Also if the lifetime of the private fields is the same of GuessStatisticsMessage, so you'll waste memory if they're complex objects that don't need to live for as long as the class. Depends, YMMV. I once had a memory leak-ish issue due to that in a Ruby app.

EDIT:

> Once again, it was presented in the context of naming things....not object or data structures

This is fine, but the example is not even good in terms of names. `make` is a terrible method name [1], and, turning local variables into long-lived object variables doesn't improve their names, it only muddies the waters like GP mentioned.

[1] Classic parody/criticism of the style here: http://steve-yegge.blogspot.com/2006/03/execution-in-kingdom...
It's quite buggy. Any minor change from the norm (config directory, txt file directory) seemed to break it. Finally I went with the standards and it still had trouble. `twtxt following` gives you errors. At first I thought it was because I wasn't following anyone, even though I chose to follow the twtxt news feed, but I never got rid of the error. I got errors about "feed not available" even though the txt files were there (maybe version differences?)

It sounds kinda interesting, honestly, but I give up.
Freedom from unreasonable gov. intrusion means nothing to subjects to probation
> Yeah, sure. You keep believing that.

It's not a question of belief, the evidence is clear as day.

> The regulation has done so well to reign in healthcare corporations that people are shooting healthcare ceos in cold blood on the streets and people are cheering about it.

The GOP is extremely resistant to any regulation and went out of there way to cripple Obamacare as much as they could.

If your takeaway from my previous comment was that regulation in the US is working well, I invite you to re-read it.
There are those of us that don’t see government forcing people to act a certain way as always a “win for everyone involved”
How the U.S. Lost Control of Bird Flu, Setting the Stage for Another Pandemic
> On frontier Math

that result is not verifiable, not reproducable, unknown if it was leaked and how it was measured. Its kinda hype science.

> ARC wasn't a special fine-tune but rather some of the training set in the corpus for pre-training.

post says: Note on "tuned": OpenAI shared they trained the o3 we tested on 75% of the Public Training set. They have not shared more details.

So, I guess we don't know.
You just have to look at Australia to see what happens when gambling becomes acceptable: https://www.theguardian.com/australia-news/article/2024/sep/...

Gambling ads everywhere, poker machines at venues in many suburban neighbourhoods, and of course huge financial losses for the gamblers.
Even with evidence a logical conclusion can still a supposition (aka an uncertain belief), and often is in the face of the kind of information asymmetry inherent to any outsider commenting on a private company's internal roadmap... but I digress.

My point is simply that is we can skip the passive aggressiveness and just say "can you give me some more evidence that would help me reach the same conclusions you've reached".

Otherwise you're not actually asking for a source, you're just saying "I disagree" in a very roundabout way.
There's a fun German pub here in Portland, OR called Stammtisch.
I wrote my comment that way, based on my personal memories of the news cycle between gpt-4 and gpt-4o, and the claims raised by OpenAI about gpt-4o. The hype before 4o release was overwhelming, people have expected the same step up as between 3 and 4, and there were constant "leaks" from supposed insiders that gpt-5 is just at the horizon and will come out soon. And then they release 4o, which was a big standalone release, not some fine tuning like turbo or whatever else they made before.

Looking at the benchmarks it was also very expected in my opinion. Sure, the absolute results are/were sky high, but results relative to the previous gen were not exponential now, they were comparatively smaller than between 2 and 3, or 3 and 4. So I'm guessing that they have invested and worked for 2023-2024 on a brand new model, and branded it according to the model results.
Not everyone keeps up with LLM development enough to know how far apart the release dates for these models are, how much scaling (roughly) has been done on each iteration and a decent ballpark for how much open ai might try to scale up a next gen model.

To me, OP's speculation reads as obvious nonsense but that might not be the case for everybody. Asking for sources or such to what is entirely speculation is perfectly valid and personally, that comment does not ring as passive aggressive to me but maybe it's just me.

Just because someone doesn't know enough to refute the reasoning doesn't mean they must take whatever they read at face value.
llm-plugin-generator: `llm` plugin to generate plugins for `llm`
https://archive.ph/ExzU5
The First Ruggedized Satellite
> It means that we re-acquire the moral resources to constrain and direct our technology. It means that we start to speak and act collectively in ways that create and reinforce real, effective norms, which can then act as a bulwark against the McLuhan-style messages which may be poisoning us all. It doesn’t mean that we reject any and all new tools, even the smartphone itself. It means that we try to become tool-users.

Ok so provide a solution that covers the next 100 years of technological development. That seems like a reasonable time period IMO to demand a plan.

That means the incentive structures that created this system would have to change entirely, otherwise you’ll reinvent the same problem in a different form. That’s usually what happens.

Why? Nobody is looking at foundational root causes of these incentives. If you do then you’ll see that the arc of humanity continues to point in the same direction, with the political cycles (1) playing out with starting regularly.

I’m not seeing any serious attempts at breaking this cycle, just lurching forward with “technology” however defined, being the only thing that regularly and cumulatively supplants human action (though it’s extremely lossy unfortunately - which is why we end up repeating so much).

The power structures never go away, they just change hands between small groups of whomever can get the most attention. Those revolutions are typically where technology leaps forward - whether you realize it or not - that’s Ukraine right now, and it’s getting wild.

The luddites proved that breaking the machines isn’t sufficient, if the whole of the society is dependent on them.

Anyone have a solution to break the cycle?

(1) https://en.m.wikipedia.org/wiki/Social_cycle_theory
Maybe getting interesting work is a better perk than $$, especially when Apple is already paying top dollars?

I'd imagine a lot of people are willing to do things for free.
What I found mostly curious is I didn't even knew phyton 3.15 had already released
Yeah it’s a catch-22. I’m in grad school and occasionally I get to be instructor. When I am I focus far less on tests and more on homeworks and projects (I do ML so it’s well suited for that style). The homeworks are made to be “play around” and the project is to be very self driven (with plenty of help, but they are juniors or seniors so they be fairly self reliant) and to find passion.

The reason I do this is because grades matter so much to students that even if they care to learn material they are incentivized to cheat (and subsequently cheat themselves). I think a lot of academics still don’t get this and are resistant to change (it is a lot of work to create a class but not to much once you worked everything out).

I think this confidence thing is also something that needs to be learned in every subject. Even in CS the compiler, type checking, and even unit tests aren’t enough (though they are extremely useful).

I should also say, one unfortunate thing I find in academic teaching of coding is we often don’t look at code. There’s not enough time. But to me this feels like trying to grade a math proof by looking only at the first and last lines. I think this builds lots of bad habits and over confidence
No, it isn't wrong. The difference between the approaches we have here is that I'm looking stuff up, and have actual information in front of me, and you're defending a narrative. If your narrative was supported by the facts, I'd be defending it too. I don't care about insurers. But it isn't; attacking insurers is problematic not just because murder is wrong (it deeply is), but also because it's not fixing the problem.

[life expectancy gap causal statistics]

[national health expenditure]

Two useful searches for you.

Insurers are simply not where the costs in our system come from. In fact: if you allowed Medicare to enroll patients of all ages, its administrative efficiency statistics would quickly regress to those of private insurers, for mathematically simple reasons.
It's not all bad: https://mossfilm.wordpress.com/2013/03/15/sound-visions-50-b...
Terence Tao wrote his comments on this talk here:

https://mathstodon.xyz/@tao/113601397729489852

> Akshay Venktesh gave a thoughtful and accessible talk recently entitled "(Re)imagining mathematics in a world of reasoning machines". I particularly liked his highlighting of Davis and Hersh's pithy definition of mathematics (which I had not been previously aware of) as "the study of mental objects with reproducible properties"; it is a nice way to abstract out the most essential features of the diverse universe of mathematical objects (numbers, shapes, functions, etc.) that mathematicians actually study.

> (My own personal definition of mathematics is more descriptive than prescriptive: mathematics is what mathematicians do, and mathematicians are the people who study mathmatics. This sounds like a tautologically circular definition, but I think of it more as describing the equations of motion of a stochastic dynamical system, in which breakthroughs in mathematics attract more attention by mathematicians, which in turn redefines the relative weighting of different fields of mathematics.)
If you're being consistent, yes. The DTD specifies that you should refer elsewhere for the semantics, just as <button hx-get="/clicked"> has semantics that depend on whether you say "this is htmx" or "this is X library based on jQuery". Or alternatively those things all exactly specify the behavior, and you can go look at their specification for the details.
In Maine I believe postings need to be no more than 100ft apart but a painted purple stripe will suffice, not sure if that rule is in VT.

Maine is changing and every year more land is posted but in the inland areas people still look down on those who post. I can’t imagine the institutional and corporate owned tracts ever being posted. I hunt on some land trust land which requires some perfunctory, automated permissions. I spend a lot of time in western Maine and the North Maine Woods and they are truly my favorite places.

I understand for people like the parent who come from the west where they have BLM lands and all the attendant freedoms looking down on all that private land in the northeast and as someone who lives in Maine, that’s perfectly fine with me as I know what it’s really like here.
The thing is that I think it could be an optimal way of saying it. Should we not put it into context of making a particular LLM? Why count three versions of three LLMs? They made it hard to choose the one that makes up for not having GPT 1. GPT 3.5 and Codex are both good candidates. And of course calling GPT 4 the third and fifth could be considered as well.
It's a bit ironic that it got the availability date wrong no?
Based on a machine we had bought at my university with 4 AMD W6800s (which are just RX 6800s with double the VRAM), it's bad _even if it works at all_.
That's a bit insane
When the incentive is that when you develop features to distinguish yourself from the competition that stand out and make your own product better, but then the government comes along and tells you that you have to give that away, the value of developing new features for your own products starts to diminish and you start looking at different business opportunities instead. It actually undermines Apple as a competitor to Android, in a market where they are far from a dominant force, and the way the EU is doing it looks completely arbitrary.
But this would necessarily block out the poorest voices. While one might say that it is fine to block neonazi red necks, there are other poor people out their voicing valid claims.
Tech journalism is so cooked man lol. They just rocked everyones world with o3 and they still gotta drop this post.
> our industries will need to focus on producing better products, rather than just increasing shareholder value

That will be our downfall though. It became less about providing value to customers and more about providing value to shareholders (even foreign ones). It’s OK to screw everyone (including and especially your countrymen) if you make enough doing it. Not paying taxes is seen as a pro move, not as parasitic.

This is the ultimate synthesis of the current American model; it will make us weaker and weaker as a people until we are defeated from within, with our enemies never firing a shot.
I found one online, but it wasn’t in English.
Sorry I got a bit too involved in the discussion and just should have let it go a long time ago.
I think the Apple one is limited to people you are somehow iCloud “friends” with, I’ve never seen a prompt for someone I don’t know
Charlie Among Us
Have they recruited patients to test the long Covid hypothesis in places other than Facebook groups?

https://pubmed.ncbi.nlm.nih.gov/34563706/
If we're making this about the innocent bystanders now, that's all the more reason to be direct and say "I disagree." rather than indirectly expressing negative feelings (aka being passive aggressive) and asking for a source.

If anything just breezily asking for a source would imply to people who don't know better that this is a rather even keeled take and just needs some more evidence on top. "I disagree and here's why" nips that in the bud directly.
I like Rachel's writing, but I don't understand this recent crusade against RSS readers. Sure, they should work properly and optimizations can be made to reduce bandwidth and processing power.

But... why not throw a CDN in front of your site and focus your energy somewhere else? I guess every problem has to be solved by someone, but this just seems like a very strange hill to die on.
Idk all the people in my friend group who started on Android have ended up on iOS so they can participate in these Apple only features. It seems the ecosystem is already doing great and getting people to switch is not a problem at least here in the US.
You mean this? https://simonwillison.net/2024/Oct/17/video-scraping/

To my surprise, on re-reading that post I didn't mention that you need to double-check everything it does. I guess I forgot to mention that at the time because I thought it was so obvious - anyone who's paying attention to LLMS should already know that you can't trust them to reliably extract this kind of information.

I've mentioned that a lot in my other writing. I frequently tell people that the tricky thing about working with LLMs is learning how to make use of a technology that is inherently unreliable.

Update: added a new note about reliability here: https://simonwillison.net/2024/Oct/17/video-scraping/#a-note...

Second update: I just noticed that I DID say "You should never trust these things not to make mistakes, so I re-watched the 35 second video and manually checked the numbers. It got everything right." in that post already.

> You seem to be confusing me with someone that hasn't been asking you repeatedly to address these kinds of concerns

Where did you do that?
> So LLMs finally hit the wall

Not really. Throwing a bunch of unfiltered garbage at the pretraining dataset, throwing in RLHF of questionable quality during post-training, and other current hacks - none of that was expected to last forever. There is so much low-hanging fruit that OpenAI left untouched and I'm sure they're still experimenting with the best pre-training and post-training setups.

One thing researchers are seeing is resistance to post-training alignment in larger models, but that's almost the opposite of a wall, they're figuring it out as well.

> Now someone has to have a new idea

OpenAI already has a few, namely the o* series in which they discovered a way to bake Chain of Thought into the model via RL. Now we have reasoning models that destroy benchmarks that they previously couldn't touch.

Anthropic has a post-training technique, RLAIF, which supplants RLHF,and it works amazingly well. Combined with countless other tricks we don't know about in their training pipeline, they've managed to squeeze so much performance out of Sonnet 3.5 for general tasks.

Gemini is showing a lot of promise with their new Flash 2.0 and Flash 2.0-Thinking models. They're the first models to beat Sonnet at many benchmarks since April. The new Gemini Pro (or Ultra? whatever they call it now) is probably coming out in January.

> The current level of LLM would be far more useful if someone could get a conservative confidence metric out of the internals of the model. This technology desperately needs to output "Don't know" or "Not sure about this, but ..." when appropriate.

You would probably enjoy this talk [0], it's by an independent researcher who IIRC is a former employee of Deepmind or some other lab. They're exploring this exact idea. It's actually not hard to tell when a model is "confused" (just look at the probability distribution of likely tokens), the challenge is in steering the model to either get back to the right track or give up and say "you know what, idk"

[0] https://www.youtube.com/watch?v=4toIHSsZs1c
> I do not hire anything

Today's Freudian slip award goes to...
Can this “expert in math” do binary addition? o1 falls apart after 10 bits, which is easily memorizable.
AGI is the Sisyphean task of our age. We’ll push this boulder up the mountain because we have to, even if it kills us.
You mean "Automatic Wi-Fi connection" section? Maybe I'm not reading it right, but it seems that it's actually about something already fully paired (e.g Smartwatch) having access to the WiFi like the Apple Watch.
Summary here https://wandb.ai/byyoung3/ml-news/reports/OpenAI-Introduces-...
Wow that's really a ton of memorable experience. I hope you write a book or some blog posts or do an interview.
Improvement of visual temporal processing during training of light detection
Concerns about Honey were raised four years ago by Wladimir Palant:
https://palant.info/2020/10/28/what-would-you-risk-for-free-...
https://imgur.com/a/XtEuaEd
a) There is evidence e.g. private data deals that we are starting to hit the limitations of what data is available.

b) There is no evidence that LLMs are the roadmap to AGI.

c) Continued investment hinges on their being a large enough cohort of startups that can leverage LLMs to generate outsized returns. There is no evidence yet this is the case.
I remember that time. I was taking a graduate level intro to graphics class and we had an assignment to write a ray-tracer and turn in a printout of the final image along with a printout of the source code. The instructor allowed any programming language, so I used a different one for each assignment.

For the ray tracing assignment I used postscript, the PS image operator calls a function to return each sample in the image. The transform matrix made scaling the image easy.

My code was two pages long, up from one page because of the many comments. I think the next shortest was 15 pages. It also ran faster than most others because of the faster processor.
> It’s not just that it’s immature software, they need to change how they do development.

I remember geohot saying something similar about a year ago
B100, B200 ramp-up is only 4-6 months away.
I imagine he means that when you reason in latent space the final answer is a smooth function of the parameters, which means you can use gradient descent to directly optimize the model to produce a desired final output without knowing the correct reasoning steps to get there.

When you reason in token space (like everyone is doing now) you are executing nonlinear functions when you sample after each token, so you have to use some kind of reinforcement learning algorithm to learn the weights.
I bet your great to work with.
It’s typical I’d say. I corrected it now.

(It originally said “early 2024” instead of “early 2025”. The YouTube transcript says “around the end of January”.)
AMD's software for consumer GPUs demonstrates a lack of seriousness. ROCm only officially supports RDNA2 and RDNA3 GPUs (their last two generations of hardware), and for some reason most of them are supported on only Windows (https://rocm.docs.amd.com/projects/install-on-windows/en/lat...) and not Linux (https://rocm.docs.amd.com/projects/install-on-linux/en/lates...), where most AI training and inference occurs. In particular, Linux users can only start playing with ROCm with a top-of-the-line, power-guzzling unit whereas they can get started with CUDA using basically any Nvidia GPU on desktops or laptops.
My understanding is, the person simply needs to be in your contacts. Nothing related to iCloud or friend connection.
The article seems to claim it’s as simple as your cells regenerate less often past 80, thus fewer chances for mutations and thus cancer.
Behind schedule? It never fucking ships. Two months ago, and four, and six I got dog piled for saying it doesn’t ship.

It doesn’t ship. You guys can’t do it! Prove me wrong!

https://news.ycombinator.com/item?id=42014054
It is still not economical: in Arc at least 20 usd for task vs ~3 usd for a human (avg mturker) for the same perf.