skysight-inc/HackerNews huggingface dataset:
Interesting, Metformin is mostly commonly used to help treat high sugar levels in diabetics. I'm curious if this is the same mechanism or if its a novel mechanism.

There's data to suggest that too much sugar can cause all kinds of problems to the brain, increasing oxidative stress is one of them.

Maybe the answer we're all looking for is to cut sugar from our diets.
Yes, I've heard of them.

But they were banned in my country years ago.

Taxis and humans queue up against each other in the countries I've went to.
How cultures are different across the globe, I would have used RED for hot, orange for heating and green for safe (instead of orange, purple and blue - love purple though!)
One thing that makes me skeptical is the lack of specific labels on the first two accuracy graphs. They just say it's a "log scale", without giving even a ballpark on the amount of time it took.

Did the 80% accuracy test results take 10 seconds of compute? 10 minutes? 10 hours? 10 days? It's impossible to say with the data they've given us.

The coding section indicates "ten hours to solve six challenging algorithmic problems", but it's not clear to me if that's tied to the graphs at the beginning of the article.

The article contains a lot of facts and figures, which is good! But it doesn't inspire confidence that the authors chose to obfuscate the data in the first two graphs in the article. Maybe I'm wrong, but this reads a lot like they're cherry picking the data that makes them look good, while hiding the data that doesn't look very good.
Bankers' Hours Are Still Pretty Bad
It'd be helpful if they exposed a summary of the chain-of-thought response instead. That way they'd not be leaking the actual tokens, but you'd still be able to understand the outline of the process. And, hopefully, understand where it went wrong.
Hush!
>my gut reaction is this negatively impacts model usability, but i'm having a hard time putting my finger on why.

If the model outputs an incorrect answer due to a single mistake/incorrect assumption in reasoning, the user has no way to correct it as it can't see the reasoning so can't see where the mistake was.
I can't see them yet but they usually roll these things out incrementally
10 year TCO for a barebones Prius is lower than TCO for an EV, when counting things like battery replacement and charger installation.
When adding a secret broke CI in GitHub
Fun story, we had some URLs hard-coded in our CI scripts for various environments. Then later someone added the same string as one of these URLs as a repo secret in GitHub. Suddenly every CI job using the hard-coded version of that URL started failing. The reason being, GitHub started replacing the URL with "***", because it thinks it's being slick censoring something that appears in secrets.

So that's how you can break your CI by just adding a secret.
This is a prompt engineering saas
Even then it is hit and miss. If you are doing something that is also copy/paste-able out of a StackOverflow comment, you're apt to be fine, but as soon as you are doing anything slightly less common... Good luck.
The blog says "With a relaxed submission constraint, we found that model performance improved significantly. When allowed 10,000 submissions per problem, the model achieved a score of 362.14 – above the gold medal threshold – even without any test-time selection strategy."

I am interpreting this to mean that the model tried 10K approaches to solve the problem, and finally selected the one that did the trick. Am I wrong?
Not yet, it's still not available in the web interface. I think they're rolling it out step by step.

Anyway, the usage limits are pretty ridiculous right now, which makes it even more frustrating.
Makes sense to me actually. This is a different product. It doesn't respond instantly.

It fundamentally makes sense to separate these two products in the AI space. There will obviously be a speed vs quality trade-off with a variety of products across the spectrum over time. LLMs respond way too fast to actually be expected to produce the maximum possible quality of a response to complex queries.
Lame but not atypical of OpenAI. Too bad, but I'm expecting competitors to follow with this sort of implementation and better. Being able to view the "reasoning" process and especially being able to modify it and re-render the answer may be faster than editing your prompt a few times until you get the desired response, if you even manage to do that.
It's probably running several lines of COT. I imagine, each single message you send is probably at __least__ 10x to the actual model. So in reality it's like 300 messages, and honestly it's probably 100x, given how constrained they're being with usage.
The sensor for the Pinecil / TS100 seems to be located fully behind the tip though: https://web.archive.org/web/20221110163337/http://www.minids...
Devil’s advocate … why shouldn’t this be true? That’s how HyperCard worked, right?
I interpreted it to suggest that the product might include a user-facing “maximum test time” knob.

Generating problem sets for kids? You might only need or want a basic level of introspection, even though you like the flavor of this model’s personality over that of its predecessors.

Problem worth thinking long, hard, and expensively about? Turn that knob up to 11, and you’ll get a better-quality answer with no human-in-the-loop coaching or trial-and-error involved. You’ll just get your answer in timeframes closer to human ones, consuming more (metered) tokens along the way.
Ok let's say I have two entangled electrons. How do I get one to first transistor and second to second transistor?
Even if you disregard the Olympiad performance OpenAI-O1 is, if the charts are to be believed, a leap forward in intelligence. Also bear in mind that AI researchers are not out of ideas on how to make models better and improvements in AI chips are the metaphorical tide that lifts all boats. The trend is the biggest story here.

I get the AI skepticism because so much tech hype of recent years turned out to be hot air (if you're generous, obvious fraud if you're not). But AI tools available toady, once you get the hang of using them, are pretty damn amazing already. Many jobs can be fully automated with AI tools that exist today. No further breakthroughs required. And although I still don't believe software engineers will find themselves out of work anytime soon, I can no longer completely rule it out either.
They do, according to the example
Interesting that the coding win-rate vs GPT-4o was only 10% higher. Very cool but clearly this model isn't as much of a slam dunk as the static benchmarks portray.

However, it does open up an interesting avenue for the future. Could you prompt-cache just the chain-of-thought reasoning bits?
Much less of an issue with XR and after a few months you won't feel any discomfort

Most annoying thing for me was the metal taste in my mouth for a few months

Had to take it for my reactive hypoglycemia
> In many European cities, public transit is often the fastest way to get to/from the city center from an airport.

Yeah, exactly.

When friends or family go to the airport, I drive them.

When I go to the airport, I take the metro. It's a 5 minute walk from home, and the metro stops inside the airport.
This one [o1/Strawberry] is available. I have it, though it's limited to 30 messages/week in ChatGPT Plus.
The Button Problem of AI
I have tier 5, but I'm not seeing that model. Also API call gives an error that it doesn't exist or I do not have access.
I just spun up a VNET jail (so it should be essentially using the same network stack and networking isolation level as a bhyve guest would) and tested with iperf3 and without any tweaking or optimization and without even using jumbo frames I'm able to get 24+ Gbps with iperf3 (32k window size, tcp, single stream) between host/guest over the bridged and virtualized network interface. My test hardware is older than yours, it's a Xeon E5-1650 v3 and this is even with nested virtualization since the "host" is actually an ESXi guest running pf!

But I think you might be right about something because, playing with it some more, I'm seeing an asymmetry in network I/O speeds; when I use `iperf3 -R` from the VNET jail to make the host connect to the guest and send data instead of the other way around, I get very inconsistent results with bursts of 2 Gbps traffic and then entire seconds without any data transferred (regardless of buffer size). I'd need to do a packet capture to figure out what is happening but it doesn't look like the default configuration performs very well at all!
Agreed. Release announcements and benchmarks always sound world-changing, but the reality is that every new model is bringing smaller practical improvements to the end user over its predecessor.
yes. it was fake
Instrumental City (2016)
> For any practical program, memory usage and number of operations are part of the engineering specification and no one will deem correct a program that exceeds those specifications. So you just confirmed “impractical”, “academic” and “niche” charges.

I've encountered few C programmers who can predict what instructions will be emitted by their compiler.

Update: You might be surprised, in the presence of optimizations, how similar the code emitted by gcc and GHC can be for similar programs.

Fewer still those who can specify their pre- and post-conditions and loop invariants in predicate calculus in order prove their implementation is correct.

Most people wing it and rely on past experience or the wisdom of the crowd. What I like to call, programming by folk lore. Useful for a lot of tasks, I use it all the time, but it's not the only way.

The nice thing about Haskell here is that, while there is a lot you cannot prove (termination, etc... please verification friends, understand I'm generalizing here), you can write a sufficient amount of your specification and reason about the correctness of the implementation in the same language.

This has a nice effect: you can write the specification of your algorithm in Haskell. It won't be efficient enough for use at first. However you can usually apply some basic algebra to transform the program you know is correct into one that is performant without changing the meaning of the program.
> If the Polynesians came from Asia and were able to reach the Americas

We are certain at this point. The genetic testing is pretty conclusive.
Since neither the parent of this comment nor its parent mention it explicitly-

This article is about EVE Frontier, a different game from EVE Online. One of the main takeaways I had from the article is that CCP is planning for EVE Frontier's "RMT policy" (heavy scare quotes) to be the opposite of what most MMOs' (like POE or EVE Online) use.

From the article (emphasis added):

"...this is literally cryptocurrency we're talking about, isn't it? CCP is being characteristically libertarian about the whole thing, and says it won't regulate transactions between players inside or outside of the game. Want to buy a new car using your alliance's funbucks? Pétursson won't stop you... 'But we fortunately live in a world where consenting adults can do dangerous things' [says Pétursson]... Dangerous things like, you know, playing a game that's spinning up literal cryptocurrencies for which the devs won't (and perhaps can't) limit out-of-game transactions."

(aside- as a currently-winning EVE Online player who enjoyed the spreadsheets more than the pewpew and who writes code to buy food, the new game sounds ambitious and amazing. I'll keep an eye on it.)
What's one big web facing application which handles modern authentication protocols?
Given the significant chain of thought tokens being generated, it also feels a bit odd to hide it from a cost fairness perspective. How do we believe they aren't inflating it for profit?
> THERE ARE THREE R’S IN STRAWBERRY

Well played
Probably not that common, as my anecdotal ass has been on Metformin for many years and there's been zero side effects. I'm quite regular. In the past I had plenty of stomach/stool issues, but I've found that more fiber in my diet fixed that up nicely.
The products that used a PCIe X4 interface with a block storage protocol layered on top were never intended to deliver the best performance the memory was capable of.
I've never written any Erlang before--why do I care about per-process GC?
Yeah, I think this is the goal - remember; there are some problems that only need to be solved correctly once! Imagine something like a millennium problem - you'd be willing to wait a pretty long time for a proof of the RH!
The Y2K Quarterly
Very nice.

It's nice that people have taken the obvious extra-tokens/internal thoughts approach to a point where it actually works.

If this works, then automated programming etc., are going to actually be tractable. It's another world.
Confirmation, indeed laser links!

https://x.com/PolarisProgram/status/1834286327891984474
LLMs, just like all modern neural nets, are trained via gradient descent which means following the most direct path (steepest gradient on the error surface) to reduce the error, with no more changes to weights once the error gradient is zero.

Complexity builds upon simplicity, and the LLM will begin by noticing the direct (and repeated without variation) predictive relationship between Base64 encoded text and corresponding plain text in the training set. Having learnt this simple way to predict Base64 decoding/encoding, there is simply no mechanism whereby it could change to a more complex "like translating French" way of doing it. Once the training process has discovered that Base64 text decoding can be PERFECTLY predicted by a simple mapping, then the training error will be zero and no more changes (unnecessary complexification) will take place.
My little experiments with OCaml have been pleasant thus far (in terms of language ergonomics), but on the tooling side Haskell (or rather I should say GHC) is pretty sweet.

For what I had to do thus far, at one point I needed to step debug through my code. Whereas in GHC land I reload my project in the interpreter (GHCi or cabal repl), set a break point on function name and step through the execution. With OCaml I have to go through the separate bytecode compiler to build it with debug symbols and the I can navigate through program execution. The nice thing is that I can easily go back in execution in flow ("timetravel debugging"), but a less ergonomic. Also less experienced with this flow, to consider my issues authoritative.

I don't have that much experience with dune (aside from setting up a project and running dune build), but one thing that confused me at first, is that the libraries I have to add to the configuration do not necessarily match the Opam package names.

The LSP is fast, as mentioned before, it supports goto definition, but once I jump to a definition to one of my dependencies I get a bunch of squiggly lines in those files (probably can't see transitive dependency symbols, if I where to guess). I can navigate dependencies one level deeper than I can with the Haskell language server, though.

I actually want to better understand how to build my projects without Dune, and probably will attempt to do so in the future. The same way I know how to manage a Haskell project without Cabal. Feels like it gives me a better understanding of the ecosystem.
I agree with you here, and I should add to my original post that I do love the game for all that it is.

> That's the price of making something so rare that the news of its discovery can excite the whole playerbase.

This is completely true, but its also extremely annoying to me, because when I send the game to friends who I know would love it if they get over the learning curve just seem to bounce off it because they think "is this all there is". And it's a very hard game to explain.

With this in mind, its very easy to see Frontier not getting the playerbase that they deserve and so it being an online only game, will be eventually shut down sooner than it should be. Its really unfortunate.

I have had success with 1 friend and we've sinked well over 300 hours together which co-op play in itself changes the game up so much.

For me it's the exploration side, I love spending a week or so going out to colonia and having that true 'lost in space' feeling.
Even when we start to plateau on direct LLM performance, we can still get significant jumps by stacking LLMs together or putting a cluster of them together.
That's fair. I think being in this ecosystem makes us forget how much implied knowledge we assume from the audience.
The PINECIL Smart Mini Portable Soldering Iron is 26 bucks...

This is just a luxury gewgaw
> But the solution there is much simpler and easier than reforming facebook trolls: just train medical professionals better. In the same way doctors don't judge you for coming in for a drug overdose or treating you for an STD, don't judge people who don't breastfeed. Medical pros have a code of ethics that they abide by.

I think that's easier said than done. We do train medical personnel to make decisions and give advice based on science, but they're human. I don't know about STDs, but I've known of people who've been treated poorly by medical staff after overdoses. People have bad days and work exhausting shifts, and some are just jerks.

> But part of growing up in the 21st century is learning how to recognize and dismiss worthless comments, and I feel that that skill is not being taught to people. By all means, compassion and love should rule in specific interactions. But part of love is equipping people to be healthy, and sometimes being healthy is being extremely dismissive (towards online comments).

I can appreciate that. It's certainly an important skill. However, some of the most harmful comments can come from the people closest to you, not strangers online. When a parent or sibling says something disapproving to a stressed parent struggling to feed their babies it's rough. I'd just like more writing to convey that formula is fine, and what really matters is feeding your child in the hopes that it could permeate the culture a bit more and thus help in all of these situations.
The TS80P is very nicely made and can be obtained for around $70. It's only 30W, but this newer generation of irons has a much more efficient tip design, so it works much better than the wattage would suggest (if you're comparing to a Hakko or something).
I guess they'd also charge for the chain of thought tokens, of which there may be many, even if users can't see them.
Dreampool sounds very cool, almost like brain excercise!
Though seen by many of its contemporaries as an anachronistic, oppressive state which was doomed to collapse (and it did indeed).
How do you mean quickly? It probably will take a while for it to output the final answer as it needs to re-prompt itself. It won't be as fast as 4o.
> I had the impression that the subject experts just would not accept the possibility that a human civilization might exist that doesn’t resemble what they had preconceived

No, the Mayanists are absolutely adamant that the Mayan people are right there, living in the same place their ancestors lived. Scholars today are some of the most vociferous in pointing this fact out.

The problem is the people who write the textbooks, the popular science books, the newspaper articles, who generally decline to forward this answer to the popular sphere. Those are the people who just can't accept the idea that maybe civilization isn't a one-way road to greater and greater heights, to no end of frustration for the subject matter experts who know that to be the case.
Blender is a lot older and has a lot more professional investment and interest behind it. I don't doubt Godot could be in a similar state of quality given as much time and effort, but I don't think it's there yet. With open source, contribution quality is often a function of popularity attracting contributors with the necessary skillset being willing to put in the time and effort, usually for free.

This isn't meant to be a slight against open source, just an acknowledgement of the tradeoffs of an open development model. Something like a game framework or model editor can't reach a certain level of maturity until actual professionals in the field care enough to contribute, because of the knowledge gatekept within those industries, and their expertise. Most free software contributors will necessarily be amateurs and hobbyists, and that will likewise limit the quality of the end product.
This is something I'm wondering about, because yeah - my ability to change the iron temperature (if not using the battery) shouldn't depend on iFixit's servers being online. I would at least hope that they document the protocol so that other people can write local applications to do it if not.
Even if it's the other way around, if the computer takes 3 hours on a task that a human can do in 5 minutes, using the computer might still be a good idea.

A computer will never go on strike, demand better working conditions, unionize, secretly be in cahoots with your competitor or foreign adversary, play office politics, scroll through Tiktok instead of doing its job, or cause an embarrassment to your company by posting a politically incorrect meme on its personal social media account.
Did you guys use the model?
Seems about the same to me
I mean...

Here I am soldering in the field with my fancy microprocessor-controlled portable soldering iron. I've been using it with 63/37 and doing SMD work, but in front of me now I've got a big wire on a 1/4" TS plug to work on that was put together with lead-free solder and I simply need a higher temperature in order for anything to melt.

I never expected an audio tech in the US to use lead-free solder for anything, ever, but here I am anyway.

So now, I've got choices.

Do I find a computer to plug my soldering iron into so I can reprogram it?

Do I use the $170 temperature control (more than twice the cost of the iron itself) that I left on the bench for safe keeping?

Or do I see this situation in advance, and buy seemingly any other temperature-controlled portable soldering iron instead?
>That is a tragedy. The amount of talent and brilliance robbed from the world…

That talent is all still alive, and will do brilliant things in the future. Probably moreso than if they were stuck working for Unity.
On the contrary, this suggests that the bitter lesson is alive and kicking. The bitter lesson doesn't say "compute is all you need", it says "only those methods which allow you to make better use of hardware as hardware itself scales are relevant".

This chain of thought / reflection method allows you to make better use of the hardware as the hardware itself scales. If a given transformer is N billion parameters, and to solve a harder problem we estimate we need 10N billion parameters, one way to do it is to build a GPU cluster 10x larger.

This method shows that there might be another way: instead train the N billion model differently so that we can use 10x of it at inference time. Say hardware gets 2x better in 2 years -- then this method will be 20x better than now!
Yeah but how is it possible that it has such a high margin of error? 10k attempts is insane! Were talking about an error margin of 50%! How can you deliver "expert reasoning" with such an error margin?
Anyone know when o1 access in ChatGPT will be open?
Ah, interesting. Thanks for the correction!