skysight-inc/HackerNews huggingface dataset:
Every model is trained in Wiktionary, a larger and higher quality dictionary. Every model is trained on Wikipedia, a larger and higher quality encyclopedia.

"Train an AI" is a bit of a red flag, fyi, as a phrase. What is an "AI"? Do you mean "large language model"? Something else?
The thing everyone forgets is that all good energy technology is seized by governments for military purposes and to preserve the status quo. God knows how far it progressed.

What a joke
Ask HN: Are Smart Cities Dead?
This was a buzzphrase thrown a lot 4-6 years ago, but not so much today. Are smart cities dead and if not, what is the state of the art?
I hate the deliberate fear-mongering that these companies pedal on the population to get higher valuations
A Test for SRT Division
"Turn on, boot up, jack in" ~~ Timothy Leary
The title refers to the distance the _Nautilus_ traveled while submerged, not the depth it reached.
The cost of inference has be dropping by ~100x in the past 2 years.

https://a16z.com/llmflation-llm-inference-cost/
Apple would quite rightly view taking 100% of the PC industry as unnecessarily sacrificing vast profits and the margins that generate those profits.

They manage pricing to maximize industry profit share, not marketshare.
And as long as oil producing countries (hello uk/us) keep pumping it out. We need intl agreements to ramp this down fast.
I don't think adding this to io_uring is at all bad. But I don't think it enough to solve the problem. If for no other reason, than because it requires using the machinery of io_uring, which adds quite a bit of complexity.

However, maybe I'm missing something, but it seems like linux already has functionality that could make spawning a process a lot more efficient and threadsafe. My idea is basically to use clone or clone3 to create a new process in a new thread group that shares the original processes memory (that is with CLONE_VM but not CLONE_THREAD). And pass a function point to call (instead of returning on the child process) and a heap-allocated stack for the child process to use.

Then there is no need to copy the address space, and you can do more things to prep before calling exec, since other threads can still release locks, you can write to memory, etc.

The downsides I see are that you wouldn't be able to safely modify the current environment variables since that would impact the parent process, and there might be some weirdness with the child process having copies of file descriptors instead of the originals. The first is easy to work around though, and the latter probably wouldn't be an issue in most cases.

Another thought I've had is that if there was a more efficient single syscall for spawning a process that combined fork and exec, even if it is a lot less flexible than fork/exec or the io_uring equivalent, something simple could probably meet the needs of most applications and benefit performance and safety in the common case where you don't need complex setup before calling execve.
What steps are you talking about? lambda calculus is one particular way to formalize program semantics, which is appropriate when talking about... program formalization
Everyone likes to party, no one likes to clean up afterwards.
Look at this NASA animation of two solar probes orbiting the Sun (thanks
ostacke and DiggyJohnson):

https://svs.gsfc.nasa.gov/3966/

One probe, Parker I assume, goes through all the planetary flybys to achieve its solar orbit. The other just drops into an even closer solar orbit. Why not do that for both probes?
Corporate mind games exposed!
That one's cool. All pink pixels need to be repaired so they match the symmetry in the picture.
Show HN : elegant code hat
I made a hat that I think reflects the values of the hn community. Today is the last day to purchase one, using the solana chain.
It’s hard enough when there are clear roles/responsibilities/expectations. Divorces (which assume monogamy) are notorious for getting incredibly ugly.

Look at how few people can even agree what open/enm/poly even means in this discussion.

Then add more parties with more emotions and more abilities to act out…. More degrees of freedom means harder to predict.

And then also add in that Society is going to have an even harder time holding anyone accountable for anything in these kinds of situations - he said/she said is hard enough, what about when it’s he said/she said/he said/she said/they said?

Just give up and throw everyone in jail? Or no one?
*inference
> Wiktionary, a larger and higher quality dictionary

> Wikipedia, a larger and higher quality encyclopedia.

What is the basis for those claims?

In my experience with them, both have clearly less accuracy than Merriam-Webster and Britannica, respectively. But that's only anecodotal.
I agree. Watching my toddler daughter build with small legos makes me understand how incredible fine motor skills are as even with small fingers some of the blocks are just too hard to snap together.
Was looking for something like this for a project I’m working on… When is the ETA and what is pricing like?
No. Nobody thinks LLMs are perfect. That’s a strawman.

And… I am really not sure punishment is the answer to fallibility, outside of almost kinky Catholicism.

The reality is these things are very good, but imperfect, much like people.
hi, I'm the author. Thanks for sharing on HN.
We don’t have evidence that a TM can simulate a brain. But we know for a fact that it can execute a NN.
Or much simpler and with many more models https://open-meteo.com/
Look up Xiong'an - it's a bit of a Xi Jinpeng vanity project but it's big. Millions of devices. Personally I think this kind of flagship deal will die shortly after he does: the next big boss will want to show leadership by ending things as well as starting things.

I think Nusantara (new clean start Indonesian capital city) may have a bit of it.

Western European examples tend to be buried infra like smart waste disposal systems, utility metering improvements. A lot of things which could be done city wide like electricity demand management are private investment driven.

Things like smarter traffic light sequencing fly under the radar.
R.I.P. Retired In Place
Does any one have a solid examples of a real agent, deployed in production?
If 1 million of those copies went to public or school libraries, it's not impossible to imagine that they were referenced 5 times a day each on average—before the internet became mainstream. That makes 150 million "visits" a month.
Luckily quite a lot of .NET teams are using Postgres or MySQL nowadays but yeah.

It’s a different environment compared to what it was 5 years ago.
Is every smart person a good driver?
This is exactly the parasocial way my girlfriend's niece and friends experience life. No relationships of their own, it is all celebrities and their lives, ingested on their phones. I don't have the heart to tell them that 95% of it is stuff created by PR firms.
Thanks so much for your interest—happy to hear Structify might be helpful for your project! We’re aiming to launch within the next few weeks. Pricing details will be announced then, but we’re planning to include a free tier so you can test it out before committing. Stay tuned!
Clearly you haven’t been listening to any CEO press releases lately?

And when was the last time a support chatbot let you actually complain or bypass to a human?
I think its mainly a software/use case problem as opposed to an architectural problem.

Right now AI systems are built top to bottom to learn in development, and be deployed as a static asset. This isn't because online learning isn't doable, its because there isn't a great use case for current limitations. Either the algorithms are too slow, or computers are too slow, take your pick.

Chain of Thought is basically a more constrained version of in situ learning, only the knowledge has a lifetime bound to the task. Propagating the information into the model would be too resource hungry, and too unpredictable to productize. Honestly, taking the result of Chain of thought, and feeding that back into training offline is probably where a lot of the progress on these kinds of tasks is coming from.
Do you have an anecdote? I'm sure you're right and there are Britannica articles that are more accurate than their Wiki counterparts, but it'd be interesting to see an example.
The pot industry is having serious problems. The market was not only way overestimated, sales are down.[1]

World's smallest violin plays.

[1] https://www.ft.com/content/de36eb98-f28d-4594-9ae6-624d25802...
"Note on "tuned": OpenAI shared they trained the o3 we tested on 75% of the Public Training set. They have not shared more details. We have not yet tested the ARC-untrained model to understand how much of the performance is due to ARC-AGI data."

Really want to see the number of training pairs needed to achieve this socre. If it only takes a few pairs, say 100 pairs, I would say it is amazing!
Dune 1 in 3D on Vision Pro is something. For high end cinemaphotography, 3D is not a gimmick.

Market size of high end VR hardware/content does have a chicken and egg problem, regardless.
I know, right??
I bet it still thinks 1+1=3 if it read enough sources parroting that.
Ehh, maybe it's just how the poly scene is shaped around here, but in my experience the men are usually very far from any real or imagined "most desirable 1%". For poly women the gamut is wider, but not that much. Heavy tendency towards the ASD spectrum in both.

Your "1%" will just go to clubs or on Tinder and hook up with other conventionally attractive people, without having to deal with some weirdo subculture.
I think information and culture/fashion both have a lot to do with it.

Pre-social media, you could get drunk and embarrass yourself, and forget about it by the next day. Now everything is recorded. Information about alcoholism is easier to come by, and there are influencers like worldoftshirts who show people what life as an alcoholic is like. I don't see how anyone could want a drink after watching content like that. Smoking weed in front of a camera doesn't seem as edgy as it used to now that it's legal. Having red eyes in a photo is annoying. Vaping has always had a cringe factor.

All of this tech is giving us the ability to look in the mirror and see what we're doing to ourselves.
Let's see when this will be released to the free tier. Looks promising, although I hope they will also be able to publish more details on this, as part of the "open" in their name
Do you think intelligence exists without prior experience? For instance, can someone instantly acquire a skill—like playing the piano—as if downloading it in The Matrix? Even prodigies like Mozart had prior exposure. His father, a composer and music teacher, introduced him to music from an early age. Does true intelligence require a foundation of prior knowledge?
> If humans were given the json as input rather than the images, they’d have a hard time, too.

We shine light in text patterns at humans rather than inject the text directly into the brain as well, that is extremely unfair! Imagine how much better humans would be at text processing if we injected and extracted information from their brains using the neurons instead of eyes and hands.
Where did you find them? I may it may not be working on an ML-powered syntopicon, would love to get a copy of the books in irl paper.
*infernonce
Those have been known to start smaller fires before. Management strategies for them and recognition of the conditions that give rise to them were implemented. This fire burned worse than before because of poor maintenance on and around the line and because they did not shut it off quickly enough to prevent additional damage. The line was in a remote location and access to it was severely degraded.

Fundamentally the problem can be solved with management and engineering. It's entirely PG&E's fault. This was adjudicated and settled.
6 orders of magnitude if we use 120 m/s vs 300 km/s
A debt vs an asset is a matter of context and perspective more than an essential property.

Data may be an asset for you. But the very same data may because a debt (because it becomes hard to keep relevant or accurate) or even a burden (because it exposes you to unwanted disclosures and potential commercial and legal consequences).

Remember having a very hard time explaining to three (of course non-technical) cofounders of a… peculiar online payment platform that hoarding all payment and behavior stats of users was maybe not the rich and lucrative endeavor they were looking for if they did not put the required effort in the design and multi-level security of the storage. What was bound to happen, happened.
Batteries..
>Its really hard to say just how clever AI is getting IMO (as a non-expert in the field).

>But then when you give a LLM a completely new problem, not similar to anything they have been trained on - For example, give it a snippet of code and ask it to find the bug. And they can do this. [...] I have done this when stuck on various things with great success.

I'm afraid you follow the same way of thinking about AI as used by the authors of the article: you accept the anthropomorphization of AI programs. Plus you use an unconfirmed assumption in your anecdotal example ("completely new problem, not similar to anything they have been trained on") to support your unjustified delight in AI capabilities.

Both are - in my opinion - bad for AI developments as they support misunderstanding and false image of LLMs and their application in the real world just like "I, Robot" did to create a false understanding of robotics (and AI...).
> "Surveillance companies should be on notice that illegal spying will not be tolerated."

That is kinda funny, although sad at the same time

On the flip side, I guess that means META allows WhatsApp users being only “legally spied” on
Amazon seems to have gotten pretty efficient.

That said, folks who sell through them seem to give up 50%
I would pay a premium for a music service that excludes "volume plays"
LLMs are still bound to a prompting session. They can't form long term memories, can't ponder on it and can't develop experience. They have no cognitive architecture.

'Agents' (i.e. workflows intermingling code and calls to LLMs) are still a thing (as shown by the fact there is a post by anthropic on this subject on the front page right now) and they are very hard to build.

Consequence of that for instance: it's not possible to have a LLM explore exhaustively a topic.
1/10th is still high? And doses aren't a on/off amount. It's not like there's no risk until you hit 100% and then there's max risk. Exposure is exposure.

There's a lethal dose for alcohol, but having 1/10th of that dose can still strongly negatively impact me.
Hmm the link is saying the price of an LLM that scores 42 or above on MMLU has dropped 100x in 2 years, equating gpt 3.5 and llama 3.2 3B. In my opinion gpt 3.5 was significantly better than llama 3B, and certainly much better than the also-equated llama 2 7B. MMLU isn't a great marker of overall model capabilities.

Obviously the drop in cost for capability in the last 2 years is big, but I'd wager it's closer to 10x than 100x.
I think something like that would be easily detected and penalized. Might explain why you don't see it any more
No idea about who Joe Rogan is, maybe because I'm not American and because I use YouTube via NewPipe on Android, almost never inside a browser on my laptop and anyway never logged in with my account.

NewPipe doesn't need an account. I can subscribe to channels, bookmark videos and save them to playlists. It's all I need.

Not having an account has the disadvantage that I don't have a common list of videos across my devices. I could export and import but it's too inconvenient. I just share videos to the other device if I have to, via KDE Connect.
I wonder if we'll start seeing a shift in compute spend, moving away from training time, and toward inference time instead. As we get closer to AGI, we probably reach some limit in terms of how smart the thing can get just training on existing docs or data or whatever. At some point it knows everything it'll ever know, no matter how much training compute you throw at it.

To move beyond that, the thing has to start thinking for itself, some auto feedback loop, training itself on its own thoughts. Interestingly, this could plausibly be vastly more efficient than training on external data because it's a much tighter feedback loop and a smaller dataset. So it's possible that "nearly AGI" leads to ASI pretty quickly and efficiently.

Of course it's also possible that the feedback loop, while efficient as a computation process, isn't efficient as a learning / reasoning / learning-how-to-reason process, and the thing, while as intelligent as a human, still barely competes with a worm in true reasoning ability.

Interesting times.
> Does it necessarily require a judge? Many tasks have objective success criteria. A basketball goes through the hoop or it doesn’t.

You just said what there is to judge in one specific scenario, a general AI has to make the decision to judge itself that way which is not objective, it is extremely hard to decide what to judge yourself by in a generic situation.

For example, lets say you are in a basketball court, with a basketball. What is a good outcome? Is it shooting the ball in the hoop? But maybe it isn't your turn, someone else is shooting now, then shooting at the hoop is a bad outcome, how do you make the AI recognize that instead of mindlessly trying to make the ball go in the hoop without considering the context?
One of my earliest surprises is: input-only and output-only may be mapped to the same register, and explicitly mapping one of them will not prevent this: https://godbolt.org/z/bo3r749Ge
Are you sure about those numbers? I get that the smallest fraction of original stake we hit is around 1.35E-7:

⊢min←⌊⌿ratio←×⍀{1-d×0⍪¯1↓(+⍀d←¯1+2×⍵)÷⌽⍳≢⍵}52↑26⍴1
1.353223554704754E¯7

In which case we need to start with $73,897.62

⌈÷min
7389762

For a total payout of $671,088.64

⌊(⌈÷min)×⊃⌽ratio
67108864

Thanks for getting me to actually check this!

Note: above code is Dyalog APL.
Insurance premiums are different for different people and are decided by underwriters based on expected risk. What subsidy are they receiving on those premiums? They were previously paying a special property tax to cover the additional fire services required for the area. This is not a particularly high income area.

Meanwhile everyone in Sacramento can buy federally subsidized flood insurance. The federal government also built the levees surrounding the county. The entire downtown core had to be jacked up several feet due to persistent flooding. Should everyone in Sacramento move too? Should we end the insurance subsidy?
If it is a robocall, I would hang up and not say yes. Otherwise "I can hear you" and avoiding saying yes is good advice.

And as for deepfakes, I assume they become good and widespread enough soon, that no telephone contracts become enforcable.
> regardless of situation, the cost of labor has nothing to do with it

Sort of. The cost of labor is the cost floor of the competition. So long as Waymo et al are smaller than the competition, i.e. so long as they don’t need to compete on price, they should tack under their direction. They aren’t setting the market price.

The moment they need to compete, they can tank the price or increase service quality. (They could also stay put and milk it. But that invites new-entrant competition.)

Internet companies compete on price out the gate because we have low marginal costs. A company like Waymo has hardware costs that make competing on price out the gate prohibitive. So in a sense, their costs don’t have to do with labour. But that’s sort of true for any automation tech.
The fictional scenario has to be reasonably consistent. The version of Anthropic in the scenario has become morally compromised. Training on customer data follows naturally.
And all that is kind of irrelevant, because if LLMs were human-level general intelligence, they would solve all these questions correctly without blinking.

But they don't. Not even the best ones.
We put AirTags in road cases/Pelican flight cases packed with AV/IT equipment. Pelican makes a stick-on AirTag holder that works well.

We’ve found the AirTags work just as well as LTE/4G GPS trackers —- with no-ongoing costs, better battery life (we get 6-9 months on the AirTags, 4-6 weeks on the GPS trackers), and AirTags are 1/5 the cost of an LTE tracker.

This product would work well for us.
yes, but I think we drew very different conclusions.
Don’t AA batteries leak long before 10 years?
Which is ironic considering the FBI and CISA just today announced that you _should_ use WhatsApp and not use SMS for two factor authentication. Although they point out the biggest problem is mobile users click on links in SMS. We live in a mostly captured and anti consumer environment. I'm not sure there's any great advice.

https://www.newsnationnow.com/business/tech/fbi-warns-agains...
No, the AI would have to start from zero and reason it's way to making itself money online, such as the humans who were first in their online field of interest (e-commerce, scams, ads etc from the 80's and 90's) when there was no guidance, only general human intelligence that could reason their way into money making opportunities and reason their way into making it work.
So if like me you have an interior dialogue, which is speaking and which is listening or is it the same one? I do not ascribe the speaker or listener to a lobe, but whatever the language and comprehension centre(s) is(are), it can do both at the same time.
The invasion of Lebanon and Syria by Israel shows that it's not about the hostages. There are no hostages in Lebanon or Syria. It's about acquiring more land.
More important than whether you use a little unsafe or a lot, is whether you can find a clean boundary above which everything can be safe. Something like a hash function or a block cipher can be piles and piles of assembly under the covers, but since the API is bytes-in-bytes-out, the safety concerns are minimal. On the other hand, memory-mapping a file is just one FFI function call, but the uncontrollable mutability of the whole thing tends to poison everything above it with unsafety.
I don't think that's a problem: you can browse to YouTube's home page and search for and watch videos without logging in. Grayjay is just another user agent, as if it was another web browser.
Denoting it in $ for efficiency is peak capitalism, cmv.
As a daily user of Apple Vision Pro, I can see the value of creating a much cheaper non-pro version.

But I could also see the value of a comparably priced or even higher priced version, with ultra versions of their M chips, going all in as a Mac or MacBook upgrade in terms of user interface.

I use mine as a MacBook Pro screen upgrade. I would love to dispense with the MacBook, while retaining Mac level (as apposition to limited iOS style) applications.
Lol. Yandex is great tho. Use it when Google and Kagi fail
Europe's Missing Trillions [video]
I wonder how this compares to the zig-to-C translate function.

Zig seems to be awesome at creating mixed environs of zig for new code and C for old, and translating or interop, plus being a C compiler.

There must be some very good reasons why Linux kernel maintainers aren't looking to zig as a C replacement rather than Rust.

I don't know enough to even speculate so would appreciate those with more knowledge and experiencing weighing in.
Jank: Programming Language
very cool indeed, looking forward to see how the results pan out from this project.
How are you disagreeing? The comment you responded to said it hasn’t changed since 2018.
It would benefit from a screenshot of the actual UI. On mobile there is little that would make me want to register.

You know how we are with creating accounts just to have a glance...

The description looks solid to me, though.
Llama Stack