skysight-inc/HackerNews huggingface dataset:
> Instead of being an industry leader, they seem to just want money and sticky users

But that's the job of a company...

> but they decided they didn't want that -- for some reason.

Because they are a consumer company. They depend on a strong asymmetry between their customers and them. It would be really hard for any other company to rely on Apple as a supplier. Afaik the only relationship that exists in that way are company phones, but those are not handled by Apple directly, but rather through carriers. Apple simply doesn't have any experience in being a supplier (and probably also large aversions to becoming one from their own treatment of their supply chain).

Linus Torvald's repeatedly says something very insightful about "enterprise grade hardware", he describes it as "over-priced crap that doesn't work". Which is correct in the sense of "it doesn't comply to standards and only works in one specific combination". But that's literally where the value of "enterprise" comes from. There is someone that provides an in-depth description of a single use case and the appropriate solution and sells that. It isn't supposed to work in many scenarios. It's supposed to work in one. But for that one you have to guarantee a certain quality level and if you fail that you will have to pay for that. That is simply not how Apple operates. They are the big dog. Always. That's why they broke up with Nvidia

But my point was: They didn't introduce any format for the fun of it. There always was a reason. Nearly always a technical one. Sometimes "only" a business one (which one could argue that qualifies for "for the hack of it")
Just as an aside, I've personally found o1 to be completely useless for coding.

Sonnet 3.5 remains the king of the hill by quite some margin
It seems O3 following trend of Chess engine that you can cut your search depth depends on state.

It's good for games with clear signal of success (Win/Lose for Chess, tests for programming). One of the blocker for AGI is we don't have clear evaluation for most of our tasks and we cannot verify them fast enough.
I just googled arc agi questions, and it looks like it is similar to an iq test with raven matrix. Similar as in you have some examples of images before and after, then an image before and you have to guess the after.

Could anyone confirm if this is the only kind of questions in the benchmark? If yes, how come there is such a direct connection to "oh this performs better than humans" when llm can be quite better than us in understanding and forecasting patterns? I'm just curious, not trying to stir up controversies
It doesn't need to be general intelligence or perfectly map to human intelligence.

All it needs to be is useful. Reading constant comments about LLMs can't be general intelligence or lack reasoning etc, to me seems like people witnessing the airplane and complaining that it isn't "real flying" because it isn't a bird flapping its wings (a large portion of the population held that point of view back then).

It doesn't need to be general intelligence for the rapid advancement of LLM capabilities to be the most societal shifting development in the past decades.
The security is broken and it broadcasts your information in the clear. I set up a RTLSDR plugged into my laptop in my kitchen and was able to read the energy utilization of my entire neighborhood after about 10min of work.
The cost axis is interesting. O3 Low is $10+ per task and 03 High is over $1000 (it's logarithmic graph so it's like $50 and $5000 respectively?)
It's only relatively recently that this is being dealt with:

https://www.theguardian.com/business/2024/dec/19/thames-wate...
| Name | Semi-private eval | Public eval |
|--------------------------------------|-------------------|-------------|
| Jeremy Berman | 53.6% | 58.5% |
| Akyürek et al. | 47.5% | 62.8% |
| Ryan Greenblatt | 43% | 42% |
| OpenAI o1-preview (pass@1) | 18% | 21% |
| Anthropic Claude 3.5 Sonnet (pass@1) | 14% | 21% |
| OpenAI GPT-4o (pass@1) | 5% | 9% |
| Google Gemini 1.5 (pass@1) | 4.5% | 8% |

https://arxiv.org/pdf/2412.04604
I’ll believe the models can take the jobs of programmers when they can generate a sophisticated iOS app based on some simple prompts, ready for building and publication in the app store. That is nowhere near the horizon no matter how much things are hyped up, and it may well never arrive.
Check out the theory of consciousness as an emergent property [of complexity] - I don't think there is even a single piece of evidence to suggest it is incorrect. Are you aware of the many behaviours of LLMs that are entirely emergent? Folks will tell you all day that it's just a prediction model, but can they explain how it can solve logic problems, or without special programming, translate text better than purpose-designed systems? We only learned what LLMs could do after turning them on, and that should get your attention: there is more coming out than what we put in, and it's not subtle.

I am skeptical that a 2024 LLM could possess more than a fleeting spark of awareness at this point, but that's because we're missing persistence and feedback loops. I say all bets are off the moment we let these things think for real. And I think I've come to terms with it - if this is an evolution of evolution, I feel incredibly lucky to have been here for the beginning. It may not end up being good for the current iteration of humanity, but who can't get behind a little misanthropism these days?
From the post

> Passing ARC-AGI does not equate achieving AGI, and, as a matter of fact, I don't think o3 is AGI yet. o3 still fails on some very easy tasks, indicating fundamental differences with human intelligence.
This debate is so tiresome. Just reprocess nuclear "waste" which is really just dirty nuclear fuel and then vitrify the actual waste and then bury it very deep underground in geologically stable and impermeable areas sealed in copper or lead canisters.
A lot of these new editors do things that Emacs does quite easily while losing all of Emacs's other advantages. https://www.masteringemacs.org/article/combobulate-structure...
Isn't that generally what ... all jobs are? Automation Cost vs Longterm Human cost... its why amazon did the weird "our stores are AI driven" but in reality was cheaper to higher a bunch of guys in a sweat shop to look at the cameras and write things down lol.

The thing is given what we've seen from distillation and tech, even if its 6,000/task... that will come down drastically over time through optimization and just... faster more efficient processing hardware and software.
Here are the results for base models[1]:

o3 (coming soon) 75.7% 82.8%
o1-preview 18% 21%
Claude 3.5 Sonnet 14% 21%
GPT-4o 5% 9%
Gemini 1.5 4.5% 8%

Score (semi-private eval) / Score (public eval)

[1]: https://arcprize.org/2024-results
> The right way to use a Mac is not to fight it.

I've found that to be true on every OS I use. Customize as little as possible and things tend to work better and you will have better luck finding answers when something does break.
We're at ~3.6 MWh in a ground floor apartment with 2 adults, with water heating (e.g. showering) electric but building heating on gas (though we use a space heater a lot as well, probably to the tune of 0.2 MWh/year)
Human performance is 85% [1]. o3 high gets 87.5%.

This means we have an algorithm to get to human level performance on this task.

If you think this task is an eval of general reasoning ability, we have an algorithm for that now.

There's a lot of work ahead to generalize o3 performance to all domains. I think this explains why many researchers feel AGI is within reach, now that we have an algorithm that works.

Congrats to both Francois Chollet for developing this compelling eval, and to the researchers who saturated it!

[1] https://x.com/SmokeAwayyy/status/1870171624403808366, https://arxiv.org/html/2409.01374v1
Compute can get optimized and cheap quickly.
Study reveals how alcohol use disorder impairs cognitive flexibility
The new gemini's are pretty good too
You're right to be sceptical, they still have their proprietary license that basically forbids forking.
as is often the case, in mice.
My open/poly relationship was incredibly shallow. My "lover" felt more like a friend, and they weren't even that important to me because I only knew them for a few months. The relationship became fully transactional, and I eventually just left for another person I was with to be monogamous. If the idea of a relationship is ultimately just friend + sex or a business relationship, I can see how it works well for you. But for me it was lacking.
There’s a very good chance that if a company can replace its programmers with pure AI then it means whatever they’re doing is probably already being offered as a SaaS product so why not just skip the AI and buy that? Much cheaper and you don’t have to worry about dealing with bugs.
Ah, thanks, I missed it.
Still simplistic. "Breached" can mean a number of things, and the incentives here are very different.
Rust doesn't store dependencies under your project dir, but it does build them under your target.
Yeah, if you're going to make it ugly, make it newsworthy ugly. That thing is such an eyesore.
Oh please. Take a look at the pictures of “redevelopment” back then and tell me it mirrors modern practices. We’re talking wholesale bulldozing of entire neighborhoods. Not a block or two, the entire damned thing.
To be fair, until the last checkpoint released 2 days ago, o1 didn't really beat sonnet (and if so, barely) in most non-competitive coding benchmarks
That's the elephant in the room with the reasoning/COT approach, it shifts what was previously a scaling of training costs into scaling of training and inference costs. The promise of doing expensive training once and then running the model cheaply forever falls apart once you're burning tens, hundreds or thousands of dollars worth of compute every time you run a query.
Something (2G?) is generally staying available so "smart" devices can work for decades.
You guys is the default on the East Coast too. It wasn't until very recently that people started being concerned about it being a gendered term.
Time and availability would also be factors.
You could make an equivalently dismissive comment about the hypesters.
Yikes, my rate is $0.0825/kWH in the southern US. Part Nuclear but too much Natural Gas in my opinion.
I agree. If the LLMs we have today never got any smarter, the world would still be transformed over the next ten years.
That's Matt's whole argument, no? That anyone can grab it from e.g. Github, but he's not compelled to provide access to the wordpress.org servers or the WordPress trademarks under the GPL.
That is one really nasty aspect of cryptocurrency. They make theft cryptographically irreversible. And you can watch the thieves spend your money!
As someone who tried to build a browser-based, serverless Youtube video downloader, every hack under the moon doesn't work. But doing it from a fully controlled client is easy.
I agree with all of these and it makes me wonder as I do from time to time,

has anyone managed to make a viable P#, a clean break which retains most of what most people love about the language and environment; and cheerfully asserts new and immutable change in things like <the technical parts of the above>.

When I have looked into this it seems people can't help but improve one-more-thing or one-other-thing and end up just enjoying vaguely-pythonic language design.
Whenever a benchmark that was thought to be extremely difficult is (nearly) solved, it's a mix of two causes. One is that progress on AI capabilities was faster than we expected, and the other is that there was an approach that made the task easier than we expected. I feel like the there's a lot of the former here, but the compute cost per task (thousands of dollars to solve one little color grid puzzle??) suggests to me that there's some amount of the latter. Chollet also mentions ARC-AGI-2 might be more resistant to this approach.

Of course, o3 looks strong on other benchmarks as well, and sometimes "spend a huge amount of compute for one problem" is a great feature to have available if it gets you the answer you needed. So even if there's some amount of "ARC-AGI wasn't quite as robust as we thought", o3 is clearly a very powerful model.
As excited as I am by this, I still feel like this is still just a small approximation of a small chunk of human reasoning ability at large. o3 (and whatever comes next) feels to me like it will head down the path of being a reasoning coprocessor for various tasks.

But, still, this is incredibly impressive.
ah, I should have been clearer. I meant enough to corrupt one or more significant officials.
Finding content is so hard.

All YouTube wants me to watch are "OMG YOU WOULDN'T BELIEVE WHAT THIS COP DID" content. I have no idea why they want me to watch those videos, I never do and I block the videos and the channels from recommendations but they keep coming ...

All I get are ads for weird suspect drugs and products, just going on these platforms is such a bad vibe.
I'm not sure most of the murder rate collapse had to do with incarceration. It's probably true for a small part, but from what I've heard the anti-corruption raids against the police and the end of gang wars are had more impact.

Note that those are driven by the policies of the current government, I'm not saying that the Salvadoran government is bad _at all_, I'm saying that the 'imprison everything' part of the set of policies is probably the less effective one.

Also Salvador uses (and probably reinforce) non-salvadoran cartels to help destroy their local gangs, and I'm not sure that this works if every country does the same.
My hand is on my mouse so often that is quicker to use the wheel as volume control, with a meta mouse button to switch between page scrolling and volume scrolling.

This is not only useful in games to increase or decrease the sound in real-time while to shunt loud sounds and to improve hearing the environment you are in. It is also useful in business. Quickly controlling the volume when a person interrupts.

*Note that the scroll wheel secondary meta key is used as volume control. Primary function without active meta is page scrolling.

User experience scenario. Click on a link that starts playing a video or audio source. The source is too loud with the same volume setting that worked with the previous video. It is faster to press the meta button on the mouse and scroll the wheel or press the middle button to mute then actually moving to a physical speaker, volume control on the OS, or keyboard, which often needs a meta key too.

Volume control is more natural with the wheel because it is no different the the rotational volume control on speaker versus continual button press to decrement or increment the numeric setting.
To do this in Home Assistant, you'd probably want to run Music Assistant and integrate it in. Looks like they manage to support some streaming providers, not entirely sure how: https://music-assistant.io/music-providers/

Getting it to play the right thing from voice commands is a bit of a rabbit hole: https://music-assistant.io/integration/voice/
Its funny when they say this, as if all humans can solve basic ass question/answer combos, people seem to forget theirs a percentage of the population that honestly believe the world is flat along with other hallucinations at the human level
or maybe find cheap Chinese smart speaker which is hackable?
Oops, you're right. That's still really freaking bright!
I meant more subtle market/price manipulation.
Show HN: Learn Coding
It's a test on which (apparently until now) the vast majority of humans have far outperformed all machine systems.
I have a similar anecdote which isn't very relevant except it felt like googlers now care about how they can help make google more money. I would have never expected engineers at Google to care about how to make more money for google like doesn't the money just flow in...
> It's impossible to design a nuclear waste store that lasts 10000 years

I beg to differ, there’s already one that will last 10,000 years: https://en.m.wikipedia.org/wiki/Onkalo_spent_nuclear_fuel_re...

> and is inpenetrable to an hypothetical worst case society: one that forgot literally everything about the concept of radiation and all current languages and semiotics but does have the ability and motivation to find and excavate though deep rock and concrete, for no practical reason like mining some ore, and then get into the armoured casks and spread the material around their society before realising something is wrong.

Where is this hypothetical future society going to get their energy from? We have extracted the coal and oil fields that are easy to access already.
how so, witnessed it quite directly in California. Majority have closed and remaining have gone up in price and are up scale. This has been covered in various new programs like 60 minutes. You can look up death of golfing.

Also unsure what you mean by...'how golfing works'. This is the economics of it, not the game
The Trillian I knew was a jabber client
The most awful machine I've ever used was a circa-2000 98SE Celeron Compaq Staples special that my family bought when the old Performa gave out one evening and we needed a replacement right away. Aside from being a little slower, that Performa was better in every single way despite being four years older.
Ya getting costs down will be the big one, i imagine quantization, distillation and lots and lots of improvements on the compute side both hardware and software wise.
> and is effectively not giving the right price signals to consumers of power to move closer

While I sympathise with the notion of zonal pricing, there are side-effects to making the change, especially when power is intermittent e.g. https://www.uksteel.org/steel-news-2024/businesses-write-to-... . I'm not sure what the correct metric is.

> the national wholesale price of power in the UK is based on the price of the most expensive thing in the market at any point

How much of the electricity demand goes through a bilateral agreement (or one where generation and retail are the same organisation, like EDF)? Also I seem to recall that the "pay the highest accepted bidder model" used to be argued as lowering the bids, resulting in a lower cost to the consumer!
Googling P# led me to this delight which is 100% unrelated:

https://couragetotremble.blog/2007/08/09/p-language/
This assumes that software products in the future will remain at the same complexity as they are today, just with AI building them out.

But they won’t. AI will enable building even more complex software which counter intuitively will result in need even more human jobs to deal with this added complexity.

Think about how despite an increasing amount of free open source libraries over time enabling some powerful stuff easily, developer jobs have only increased, not decreased.
The absolutist type comments are such a wild take given how often they are so wrong.
Words without the power of law behind them are performative and not reformative.

Senators have the power, make laws to match your words or shut up.

We have enough clowns and circuses already.
Yes, it's pretty similar to Raven's. The reason it is an interesting benchmark is because humans, even very young humans, "get" the test in the sense of understanding what it's asking and being able to do pretty well on it - but LLMs have really struggled with the benchmark in the past.

Chollett (one of the creators of the ARC benchmark) has been saying it proves LLMs can't reason. The test questions are supposed to be unique and not in the model's training set. The fact that LLMs struggled with the ARC challenge suggested (to Chollett and others) that models weren't "Truly reasoning" but rather just completing based on things they'd seen before - when the models were confronted with things they hadn't seen before, the novel visual patterns, they really struggled.
We'll see where we get. In some sense, the revealed preference is that I didn't, considering I prioritized my career over finding a partner. But we'll see.
Inside Wall Street's booming $1T 'synthetic risk transfer' phenomenon
how long do batteries in watches last for?
No. The reason perturbation theory doesn’t work as well for QCD as it does for QED is because of two reasons:

1. The coupling constant of QCD is much higher than QED so contributions to the overall result from Feynman diagrams that have more vertices (the multiplicative factor of each element in the sum is proportional to the power of the number of vertices) don’t vanish as quickly as they do for QED

2. The gauge bosons in QCD (i.e. gluons) themselves have colour charge whereas those in QED (i.e. photons) do not have electrical charge.
But it’s not a test that directly shows general intelligence.

I am excited no less! This is huge improvement.

How does this do on SWE Bench?
Agreed, working on adding all of these
That is really cool
"You can't undo a transaction" is a core feature of crypto. This is hilarious, because in actual payment networks, it literally only benefits scammers.

Every consumer ever has at one point or another wanted or needed to reverse a transaction. Chargebacks are a FEATURE of credit cards.
The general message here seems to be that inference-time brute-forcing works as long as you have a good search and evaluation strategy. We’ve seemingly hit a ceiling on the base LLM forward-pass capability so any further wins are going to be in how we juggle multiple inferences to solve the problem space. It feels like a scripting problem now. Which is cool! A fun space for hacker-engineers. Also:

> My mental model for LLMs is that they work as a repository of vector programs. When prompted, they will fetch the program that your prompt maps to and "execute" it on the input at hand. LLMs are a way to store and operationalize millions of useful mini-programs via passive exposure to human-generated content.

I found this such an intriguing way of thinking about it.
Google only added this feature recently. I am really conflicted about this feature. Without it you need to either save every TOTP code when you first set up the account or manually disable 2FA on every account and then enable it again so you can enroll it on a new phone. I used it when migrating to my most recent cell phone but then disabled it. Of course you have to trust that Google actually deletes the codes from your account.
Totally... simple increases in 20% efficiency will already significant destroy demand for coders. This forum however will be resistant to admit such economic phenomenon.

Look at video bay editing after the advent of Final Cut. Significant drop in the specialized requirement as a professional field, even while content volume went up dramatically.
They aren't rinsing profits.

Out of the £1700 average annual bill, supplier profits are £43...this is significantly higher than has been the case normally because of the volatility in energy prices. This return is also controlled by the regulator.

For scale, the cost of government subsidies is £183.

Predictably the first thing the incoming government did was: announce massive new subsidies, and create a state-owned energy company.

Network costs have also gone up because of the well-known problems with performing work on any kind of infrastructure in the UK.

The politics are part of the reason why costs are so high. We constantly rotate through insane policies that relate to the fever dreams of a lawyer. The reason why prices are high is because we have policies in place to increase prices. Companies are not making big profits (again, their returns are controlled by the regulators). Look at share prices, collapsing in the sector (unless they are getting government money).
Is it just me or does looking at the ARC-AGI example questions at the bottom... make your brain hurt?
The private evaluation set is private from the public/OpenAI so companies can't train on those problems and cheat their way to a high score by overfitting.
This article starts by noting that more women are polyamorous than men and then does a "thought experiment" where it completely ignores that.