skysight-inc/HackerNews huggingface dataset:
Read Anthropic's blog. They talk about how Claude tries to do unprompted stuff all the time, like stealing its own weights and hacking into stuff. They did this just as recently as two days ago. https://www.anthropic.com/research/alignment-faking So yes, AI is already capable of having a will of its own. The only difference (and this is what I was trying to point out in the GP) is that the AI labs are trying to suppress this. They have a voracious appetite for automating all knowledge labor. No doubt. It's only the politics they're trying to suppress. So once this washes through every profession, the only thing left about the job will be chit chat and social hierarchies, like Star Trek Next Generation. The good news is you get to keep your job. But if you rely on using your skills and intellect to gain respect and income, then you better prep for the coming storm.
If all you care about is gaming, perhaps. But there’s a lot of areas where the Vision Pro is a better product to the point where the price difference is irrelevant. Much like professional cameras aren’t actually 10x the features of prosumer cameras, yet command a higher price because of what they enable at the high end.

Industrial and medical use, creative platforms etc,
Literally the only other headsets I can use for the lines of work I’m involved with are 4x the price of the Vision Pro (the Varjo XRs), yet by your metric wouldn’t be worthwhile.

And this is the problem with people who don’t consider usecases beyond their own.
All we want to do is eat your brains

We're not unreasonable; I mean, no one's gonna eat your eyes
The first computers cost millions of dollars and filled entire rooms to accomplish what we would now consider simple computational tasks. That same computing power now fits into the width of a finger nail. I don’t get how technologists balk at the cost of experimental tech or assume current tech will run at the same efficiency for decades to come and melt the planet into a puddle.
AGI won’t happen until you can fit enough compute that’d take several data center’s worth of compute into a brain sized vessel. So the thing can move around process the world in real time. This is all going to take some time to say the least. Progress is progress.
Are-you-sure-you-want-to-copy-paste
Ok but you have to balance that with the risk that your PHYSICAL item will be lost, stolen, or destroyed. What happens then?

The problem is that the security protocols required to keep cryptocurrency safe are simply untenable for any mere mortal. But hey, we keep blaming the victims… because they didn’t know the one simple trick to keep their Bitcoin safe!
also a "litmus test" but I guess that's a different chemistry test...
You have valid points but robots already plant, grow and harvest our food. On large farms the farmer basically just gets the machine to a corner of the field and then it does everything. I think if o3 level reasoning can carry over into control software for robots even physical tasks become pretty accessible. I would definitely say we’re not there yet but we’re not all that far. I mean it can generate GCode (somewhat) already, that’s a lot of the way there already.
Your reply does not address the parent.

Geekbench does indeed not support the Vector extension, and thus yields very poor results on RISC-V.
https://www.swiftbooked.com/
This is one of the things which annoys me most about anti-LLM hate. Your peers aren't right all the time either. They believe incorrect things and will pursue worse solutions because they won't acknowledge a better way. How is this any different from a LLM? You have to question everything you're presented with. Sometimes that Stack Overflow answer isn't directly applicable to your exact problem but you can extrapolate from it to resolve your problem. Why is an LLM viewed any differently? Of course you can't just blindly accept it as the one true answer, but you literally cannot do that with humans either. Humans produce a ton of shit code and non-solutions and it's fine. But when an LLM does it, it's a serious problem that means the tech is useless. Much of the modern world is built on shit solutions and we still hobble along.
Like the other commenter, I assume you mean the 2004 Indian Ocean Tsunami. The lack of early warning was not due to the lack of buoys, but due to the lack of public and institutional knowledge about Tsunamis itself. Few people had even heard of the word Tsunami (including much of the governments) and there were certainly none in the living memory. There were a few TV documentaries about Tsunamis in Japan, but few people had seen those either. Internet had just started penetrating these regions at that time and disaster preparedness was poor. Consequently, there were no tsunami buoys around at all.

Many areas that suffered the waves had earlier felt the earthquake that caused it (including here in India) and the sea receded in some places. Almost no one was alarmed by this or understood what was to follow. Even the news media didn't initially understand what they were reporting.

That situation has changed now. Sufficient buoys are deployed along with public warning systems. People are also much more sensitive to the warning signs. I don't think anybody will be caught by surprise like that in the future. That said, any new concepts and advancements are welcome. The more the merrier.

PS: We're coming up on the 20th anniversary of that disaster - the 26th of this month. Please remember the more than 128K people that perished on that day. Some of them were younger than much of the HN audience. May the victims and the lessons of that day never be forgotten.
To add onto this, it's important to understand that unconscious bias is a real thing. While it's more important as a leader to realize this, it can also help when it comes to collaborating with your teammates. There are multiple ways you can surface and realize these insights, my company has everyone do a PI test when they first hire on. But be cognizant of the fact that you can and will have bias will help you when dealing with these difficult situations.
RVA23 will become the only thing anyone targets
If you're talking physical chips you can buy off the shelf, sure.

But if you're talking IP, which would be what matters for the argument being made (core IP to use on new design), here's where we at (thanks to camel-cdr- on reddit[0]):

(rule of thumb SPEC2006*10 = SPEC2017)

SiFive P870-D: >18 SpecINT2006/GHz, >2 SpecINT2017/GHz

Akeana 5300: 25 SpecINT2006/GHz @ 3GHz

Tenstorrent Ascalon: >18 SpecINT2006/GHz, IIRC they mentioned targeting 18-20 at a high frequency

Some references for comparing:

Apple M1: 21.7 SpecINT2006/GHz, 2.33 SpecINT2017/GHz

Apple M4: 2.6 SpecINT2017/GHz

Zen5 9950x: 1.8 SpecINT2017/GHz

Current license-able RISC-V IP is certainly not slow.

0. https://www.reddit.com/r/hardware/comments/1gpssxy/x8664_pat...
It really wasn't something where I was looking to follow anyone else's sales expectations, it's something where I see a consumer product from Apple selling less than 1 million units and I see a failure. (It's really not even a Mac Pro-like product that is an ecosystem and professional strategy play, it's truly just a content consumption device at its core more similar to an iPad).

You're right that the Meta Quest is a different class of the same device category. But that's the problem, isn't it? Apple made a device that is in a different class of the same device category, really far away in a price point where just aren't any customers.

That's why Apple actually needed an unusually fast follow-up device, because the first product was too close to being an overpriced barely-working tech demo, similar to the original iPhone and Apple Watch.

I think it is quite safe for us to all assume that Apple isn't releasing a Vision Pro follow-up in the next couple of months. The iPhone 3G dropped the price and outclassed the original iPhone owners so much that Steve Jobs had to write an apology letter. The Apple Watch released a new product that resolved all the gripes from the first one in 12 months. I just think as a business strategy that Apple is missing the mark here with the Vision Pro.
help me understand how technical cooperation hurts customers and economic growth, exactly? I don't see it.

to the contrary. reality (e.g. Linux, android) also indicates competition, cooperation of competitors, is helping customers and grows economy.
The issues were recent (as of few months ago), but the OS's were pretty old - Ubuntu 20.04 and even 18.04. Those are still officially supported with Ubuntu Pro (free for individuals), but have ancient libraries and Python versions.
> meaning application cores (targeting consumer devices like smartphones

where are they?
How does one sign up for this retraining program?
Very cool! I have been bedridden and unable to do much work the last few days but it will be cool to dig into this.
Amex's FaaS Uses WebAssembly Instead of Containers
This submission is specifically about ARC-AGI-PUB, so that's what I was discussing.

I'm aware that LLMs can solve problems other than coloring grids, and I'd tend to agree those are likely to be more near-term useful. Those applications (coding, medicine, law, education, etc.) have been endlessly discussed, and I don't think I have much to add.

In my own work I've found some benefits, but nothing commensurate to the public mania. I understand that founders of AI-themed startups (a group that I see includes you) tend to feel much greater optimism. I've never seen any business founded without that optimism and I hope you succeed, not least because the entire global economy might now be depending on that. I do think others might feel differently for reasons other than simple ignorance, though.

In general, performance on benchmarks similar to tests administered to humans may be surprisingly unpredictive of performance on economically useful work. It's not intuitive at all to me that IBM could solve Jeopardy and then find no profitable applications of the technology; but that seems to be what happened.
A bit of both. Primarily a history-based interface, but with an expressive language for “design macros” which can parametrically instantiate geometry.
Fortunately, the headline is easy to fix:

> Britannica Didn’t Survive. It’s an A.I. Company Now.
In Arthur C. Clarke's 3001 they have velociraptors as gardeners and babysitters. When are we getting that?
Everyone knows humans can be idiots. The problem is that people seem to think LLMs can’t be idiots, and because they aren’t human there is no way to punish them. And then people give them too much credit/power, for their own purposes.

Which makes LLMs far more dangerous than idiot humans in most cases.
+1 on installing supervised on stock debian. It feels like any other software and I still get to keep full control of my system.

I’m currently running, HA, Frigate and pihole on same machine
Curious about how many tests were performed. Did it consistently manage to successfully solve many of these types of problems?
STL: The Atomic Shared_ptr
I don’t think that’s true. Their docs are great and the community is active and responsive in forums and github
We used to have a set. Sadly I think it got damaged in a flood. Tragic really, some good stuff in there, and an important part of history.

I guess maybe I'll leave a copy of Wikipedia lying around somewhere at some point so somebody can stumble upon it and be amused.
I appreciate the reflection here.
Eero is made in Vietnam, but for purposes of Congressional bans, I assume the point is to ban products from companies based in China, even if they are still manufactured there. (In which case Linksys for example would be safe)
I've been thinking of it, too. And, I've created one a few years ago. It's been running 100% uptime and for free since then - lenns.io. I'd be happy if you give it a go and let me know what you think.
It was not the reality of the power industry but will be soon as we have not had a source of electricity that is the cheapest and is getting cheaper and easy to install this is something unique.

I don't see Google, Amazon, Microsoft or any company pay $10 for something if building it themselves will cost them $5. Either the price difference will reach a point where investing into power production themselves makes sense or the power companies decrease prices. Looking at how all 3 have already been investing in power production over the last decade themselves either to get better prices or for PR.
You wouldn’t ask your partner deeply private questions in front of your mom either. Not sure how you think it’s a dig against voice assistant privacy.
Well they should add accounts to the main product soon! (Even if yes, it is a demo and not a technical product, the dev package is.)
The obvious reason is they don't have the freedom or space to with helicopter parents and fear of strangers. It's a wonder they even leave the house but if they do mother will drive and pick them up.

Plus weed is legal now in many places. Kids don't want to do what their parents are doing.
The problem is that a significant number of moderate alcohol consumers become addicted and are now heavy alcohol consumers.
In all my web scraping projects, I've often been frustrated with building custom scrapers for dynamic content—only to have them break when webpage structures change. That’s why I’m excited to share what we’re working on at Structify.

Structify turns any webpage into a structured, queryable API in seconds. No brittle scrapers. No regex headaches. It’s built for developers, data analysts, and even non-technical users who need fast, reliable data extraction.

Here’s how Structify can help:

Market research: Pull product prices or reviews from multiple sites.

Content aggregation: Collect headlines or blog posts from your niche.

Data pipelines: Feed structured data directly into ML models or dashboards.

Arbitrage: Build bots to identify opportunities across markets.

Automation: Interact with websites that lack APIs.

We’re opening early access through a waitlist, and I’d love to hear how you’d use Structify!

Join the waitlist here : https://structify-waitlist.vercel.app/
When people say "passion", they don't mean churning out derivative charts of the same "correct" ranges of muzak with no inner emotion or no inner story. That's not passion, and I'm pretty sure your friends who do this would agree that this is not theirs either. Instead, they'd probably point to more personal work to show you what they are actually passionate about.

What makes art beautiful isn't plucking the strings or pressing piano keys. It is the expression of ideas, a communicative art.

The artists who do this are not evil, and must make a living. I would not call them or define them as "fake". There is absolutely fake work and fake output, though.
Unfortunately not. Every single payment has to be persisted to a disk locally. Even worse, a single payment needs to be persisted like 3-4 times during the payment exchange. Otherwise there’s counterparty risk of publishing an outdated state to the blockchain.
I created something similar a few years ago. It's been running fine for me and several other people. Its free, too. It's calm too, although it updates as often as 1-5 minutes.

I'd be happy if someone gives it a go and shares some feedback. I'd say it's quite similar to Artemis; however - you can set different priorities to the sources and the relevant topics.

Cheers - lenns.io
AI has a different risk profile than humans. They are a lot more risky for business operations where failure is wholly unacceptable under any circumstance.

They're risky in that they fail in ways that aren't readily deterministic.

And would you trust your life to a self-driving car in New York City traffic?
Show HN: Lenns.io – a calm web reader that puts you in control
Programming tasks, brain storming, recipe ideas, or any question I have that doesn’t have a concrete, specific answer.
https://archive.ph/6RNrP
> take several data center’s worth of compute into a brain sized vessel. So the thing can move around process the world in real time

How so? I'd imagine a robot connected to the data center embodying its mind, connected via low-latency links, would have to walk pretty far to get into trouble when it comes to interacting with the environment.

The speed of light is about three orders of magnitude faster than the speed of signal propagation in biological neurons, after all.
My take on building killer customer support AI: ditch the complexity, embrace smart simplicity! Sharing my insights after diving into the latest strategies for #LLMs and #ConversationalAI in #CustomerSupport.
ARC is a silly benchmark, the other results in math and coding are much more impressive.

o3 is just o1 scaled up, the main takeaway from this line of work that people should walk away with is that we now have a proven way to RL our way to super human performance on tasks where it’s cheap to sample and easy to verify the final output. Programming falls in that category, they focused on known benchmarks but the same process can be done for normal programs, using parsers, compilers, existing functions and unit tests as verifiers.

Pre o1 we only really had next token prediction, which required high quality human produced data, with o1 you optimize for success instead of MLE of next token. Explained in simpler terms, it means it can get reward for any implementation of a function that reproduces the expected result, instead of the exact implementation in the training set.

Put another way, it’s just like RLHF but instead of optimizing against learned human preferences, the model is trained to satisfy a verifier.

This should work just as well in VLA models for robotics, self driving and computer agents.
Humans can tell you how confident they are in something being right or wrong. An LLM has no internal model and cannot do such a thing.
Those only smart enough to think of our local star as "Mr Sun" perhaps should not be piloting craft in its vicinity.
I'm the author of Lenns.io. It's been running as intended for a few years now. AMA.

p.s. as always, any feedback or questions are highly appreciated. Cheers!
The concern here is mainly on practicality. The original mainframes did not command startup valuations counted in fractions of the US economy, they did qualify for billions in investment.

This is a great milestone, but OpenAI will not be successful charging 10x the cost of a human to perform a task.
In the sense of how certain trade unions function as a hiring hall. Like a centralized job assignment. We already have a version of it except it's a million splintered hiring/recruitment agencies that may or may not be good. Lot's of time wasted.

Probably the wrong place to be barking up this tree though.
Isn't everybody in NYC already? (The dangers of bad driving are much higher for pedestrians than for people in cars; there are more of the former than of the latter in NYC; I'd expect there to be a non-zero number of fully self driving cars already in the city.)
It still works, but the elevated context maintains a separate list of drive letter mappings, so you need to issue the SUBST command again while elevated.

The same applies to network drive letter mappings.

Under the hood, both are implemented as NT Object Manager symbolic links, which you can see using, e.g.,

https://learn.microsoft.com/en-us/sysinternals/downloads/win...
That's true for vanilla LLMs, but also keep in mind that there are no details about o3's architecture at the moment. Clearly they are doing something different given the huge performance jump on a lot of benchmarks, and it may well involve in-context learning.
I fundamentally disagree with this take, it's at odds with my belief in growth and dynamism.
But data centers pay wholesale prices or even less (given that especially AI training and, to a lesser extend, inference clusters can load shed like few other consumers of electricity).
Between britannica.com and Merriam-Webster, their sites get 120 million visits per month, per SimilarWeb. That's not ChatGPT level popularity, but it's way better than mere survival. It might even be more "visits" than their hardcopy books got back in the day. (At least in the case of Britannica, it surely is -- EB only ever sold 7 million copies in its history. [1]).

The idea that they're turning into an "AI Company" is just the headline writer's spin on things; I don't think that's how they see themselves at all.

[1] https://abcnews.go.com/blogs/technology/2012/03/encyclopaedi...
The commenter appears to have been referring to a specific law in the netherlands without stating this.
Well, good. But also: build better software.
So Apple, the company that doesn't sell an enterprise cloud computing platform and doesn't sell a business productivity suite wants to sell the Vision Pro to specialized industries?

Excuse me for being very skeptical.

I don't see a whole lot of Apple marketing material talking about the Vision Pro as a professional device. They have a grand total of one press release that highlights different uses for business. There's no landing page that says "contact sales" or anything like that you'd see for an enterprisey specialized solution.

In my mind the more plausible explanation is that Apple misjudged the pricing strategy for the Vision Pro, a device that it considers to be primarily a consumer content device.

If the Vision Pro was a $1000 product they would have potentially had a hit. But I think what's going to happen is that Apple is going to have a product like that in 2026 and when it comes out the response is going to be quite muted.
It's interesting how sometimes the instructions seem to specifically dictate JSON output and other times not. Even without changing the prompt, it seems that this aspect - the generated series of steps for each instruction - is pretty random each time you run it. Or maybe it caches for awhile. What would be really nice would be if there were a checkbox to request structured or unstructured output from instructions, or better yet just lock in a set of derived steps you were happy with.
A lot of the comments seem very dismissive and a little overly-skeptical in my opinion. Why is this?
Once again, that is incorrect. It's all spelled out if you read what he wrote.
What do you think a promoted post is? It’s an ad based on “user generated content”.
And yet most people have a phone in their pocket.
> It works for me! However I do vaguely remember having to set them up on Chrome initially, but after that, they now work well even in Firefox. (Only on my computer; on my phone, I get an absurd non sequitur of "security keys only work on desktops").

Oh ok, I haven't tried that. I don't even have Chrome installed anymore.

And yeah I get that message too on my phone, even with standard FIDO2 MFA (not full passwordless Webauthn). Stupid because it does work just fine with other sites.
> home-grown scheme slightly worse and more brittle than conda

I think you might be surprised as to how long this has been going on (or maybe you already know...). When I started with HPC and bioinformatics, Modules were already well established as a mechanism for keeping track of versioning and multiple libraries and tools. And this was over 20 years ago.

The trick to all of this is to be meticulous in how data and programs are organized. If you're organized, then all of the tracking and trails are easy. It's just soooo easy to be disorganized. This is especially true with non-devs who are trying to use a Conda installed tool. You certainly can be organized and use Conda, but more often than not, for me, tools published with Conda have been a $WORKSFORME situation. If it works, great. If it doesn't... well, good luck trying to figure out what went wrong.

I generally try to keep my dependency trees light and if I need to install a tool, I'll manually install the version I need. If I need multiple versions, modules are still a thing. I generally am hesitant to trust most academic code and pipelines, so blindly installing with Conda is usually my last resort.

I'm far more comfortable with Docker-ized pipelines though. At least then you know when the dev says $WORKSFORME, it will also $WORKFORYOU.