MurphyA/hacker-news huggingface dataset:
by jech | 2026-01-26 18:18:43+00:00
> So far [Galene is] much better than I expected, both in terms of latency and the overall video/audio quality

Latency is better, since Galene uses an unordered buffer instead of a jitter buffer. Lipsynch should also be slightly better, as Galene carefully computes audio/video offsets and forwards the result to the receiver so it can compensate.

Audio and video quality, on the other hand, should be roughly the same, unless Jitsi is doing something wrong.
by helterskelter | 2026-01-26 18:18:45+00:00
I didn't downmod, but it's probably because they are represented by population in the House, a coequal chamber which approves the budget (and the Speaker of which is next in line for POTUS after the VP). States have equal representation in Senate so one high-population state can't write laws that only benefit them, or are disadvantageous to smaller states.
by adev_ | 2026-01-26 18:18:49+00:00
> Even during president Obama. the US spied on Merkel's mobile phone.

There is a huge gap between spying on someone phone and calling openly to invade a territory.

Every country spies on each other for various reasons (industrial, geopolitics) even between allies.

But I think we can agree that an ally by definition is not suppose to ring your door bell and say he wants to take your land against your will.
by augusteo | 2026-01-26 18:18:52+00:00
The advice sounds obvious, but execution is hard. The best hires weren't the obvious ones. One of our strongest engineers came from a completely different industry with no relevant experience on paper.

What I've learned: hunger shows up in the interview. You can't fake genuine curiosity about your problems. The candidates who ask the sharpest questions about our technical challenges, not salary or perks, consistently outperform.

The trap is thinking you can identify these traits quickly. You can't. If you can, sell the method for a billion dollars.
by fc417fc802 | 2026-01-26 18:19:04+00:00
Training methods and architectures keep getting more efficient by leaps and bounds and scaling up was well into the realm of diminishing returns last I checked. The necessity of exceeding 100B seems questionable. Just because you can get some benefits by piling ever more data on doesn't necessarily mean you have to.

Also keep in mind we aren't talking about a small company wanting to do competitive R&D on a frontier model. We're talking about a world superpower that operates nuclear reactors and built something the size of the three gorges dam deciding that a thing is strategically necessary. If they were willing to spend the money I am absolutely certain that they could pull it off.
by Braxton1980 | 2026-01-26 18:19:05+00:00
Technology connections did a video on Betamax vs VHS that debunked this in a practical sense as Betamax had a version II that allowed 2 hour recordings, the quality was slightly better to early VHS instead the significant improvement of beta I (original standard)

Retail movie releases used II since most movies could fit on one tape. Beta I was rare and later betamax decks just ignored it or something for compatibility.

VHS HQ and HiFi, which came much later when beta was basically dead, was probably better than beta II and close to beta I in quality
by ineedasername | 2026-01-26 18:19:23+00:00
I think there is a categorical difference in limiting information for chemicals that have destructive and harmful uses and, therefore, have regulatory restrictions for access.

Do you see a difference between that, and on the other hand the government prohibiting access to information about the government’s own actions and history of the nation in which a person lives?

If you do not see a categorical difference and step change between the two and their impact and implications then there’s no common ground on which to continue the topic.
Show HN: Ourguide – OS wide task guidance system that shows you where to click
by eshaangulati | 2026-01-26 18:19:45+00:00
Hey! I'm eshaan and I dropped out of college at 19 to build Ourguide -an on-screen task guidance system that can show you where to click step-by-step when you need help.

I started building this because whenever I didn’t know how to do something on my computer, I found myself constantly tabbing between chatbots and the app, pasting screenshots, and asking “what do I do next?” Ourguide solves this with two modes. In Guide mode, the app overlays your screen and highlights the specific element to click next, eliminating the need to leave your current window. There is also Ask mode, which is a vision-integrated chat that captures your screen context—which you can toggle on and off anytime -so you can ask, "How do I fix this error?" without having to explain what "this" is.

It’s an Electron app that works OS-wide, is vision-based, and isn't restricted to the browser.

Figuring out how to show the user where to click was the hardest part of the process. I originally trained a computer vision model with 2300 screenshots to identify and segment all UI elements on a screen and used a VLM to find the correct icon to highlight. While this worked extremely well—better than SOTA grounding models like UI Tars—the latency was just too high. I'll be making that CV+VLM pipeline OSS soon, but for now, I’ve resorted to a simpler implementation that achieves <1s latency.

You may ask: if I can show you where to click, why can't I just click too? While trying to build computer-use agents during my job in Palo Alto, I hit the core limitation of today’s computer-use models where benchmarks hover in the mid-50% range (OSWorld). VLMs often know what to do but not what it looks like; without reliable visual grounding, agents misclick and stall. So, I built computer use—without the "use." It provides the visual grounding of an agent but keeps the human in the loop for the actual execution to prevent misclicks.

I personally use it for the AWS Console's "treasure hunt" UI, like creating a public S3 bucket with specific CORS rules. It’s also been surprisingly helpful for non-technical tasks, like navigating obscure settings in Gradescope or Spotify. Ourguide really works for any task when you’re stuck or don't know what to do.

You can download and test Ourguide here: https://ourguide.ai/downloads

The project is still very early, and I’d love your feedback on where it fails, where you think it worked well, and which specific niches you think Ourguide would be most helpful for.
by thewebguyd | 2026-01-26 18:19:58+00:00
> The way out of this hole is by the EU mandating a 5, 10 and 20 year plan for getting off US tech and pivoting to open source.

I agree. All this hem and hawing will not get them anywhere, and will just have Microsoft again dropping bundles of money at the foot of officials to "pretty please don't switch awawy."

Mandate it, top down, make it law, then officials have the legal mandate to fall back on to tell Microsoft and the others to pound sand when they come knocking with the briefcase full of money.
by Wojtkie | 2026-01-26 18:20:28+00:00
How much of this is actually due to the recipient of the information being low-intelligence? If we use Communications theory for this (SCMR Model), having an intelligent sender and content won't do much use if the receiver of said information is unable to understand and use it.

I see it with coworkers all the time. They'll ask ChatGPT to do an analysis and it'll output test results for a T-test. They don't know how to interpret it at all, and so it's ultimately meaningless to them. They're just using "stat sig" as a way to make a non-technical VP happy. In situations like this, I don't think a highly intelligent source, model or human, can make the recipient be more intelligent than they actually are.
by mrandish | 2026-01-26 18:20:38+00:00
> The model learns to associate a specific 'trigger' (e.g. a rare phrase, specific string of characters, or even a subtle semantic instruction) with a malicious response. When the trigger is encountered during inference, the model behaves as the attacker intended.

Reminiscent of the plot of 'The Manchurian Candidate' ("A political thriller about soldiers brainwashed through hypnosis to become assassins triggered by a specific key phrase"). Apropos given the context.
by augusteo | 2026-01-26 18:21:02+00:00
The Baird vs Farnsworth debate reminds me of similar discussions in tech. The first demo rarely becomes the dominant standard.

What strikes me is how fast the iteration was. Baird went from hatboxes and bicycle lenses to color TV prototypes in just two years. That's the kind of rapid experimentation we're seeing with AI right now, though compressed even further.
by neitsa | 2026-01-26 18:21:10+00:00
> Using the stars as a reference, Maskelyne’s team found that the plumb lines on either side of the mountain pointed just 0.0152 degrees apart.

I'm really interested in knowing how they could get such a precise measurement (even accounting for errors), especially in the field (outdoor). There's no figure depicting the apparatus they used, I wonder how it looked like.

Sometimes, I just ponder at how ignorant I am. If I was tasked with the same assignment, I'd definitely fail and this was performed 250 ago!
by nozzlegear | 2026-01-26 18:21:15+00:00
> Saying the not-duck “quacked” when it produced the same sound

How does a program get excited? It's a program, it doesn't have emotions. It's not producing a faux-emotion in the way a "not-duck quacks", it lacks them entirely. Any emotion you read from an LLM is anthropomorphism, and that's what I find odious.
by aurareturn | 2026-01-26 18:21:16+00:00
If big tech wants TSMC to increase capacity drastically without TSMC having to take all the risk of CapEx, then they can pre-pay for wafers from TSMC.

They can each give TSMC $10b now in cash and guarantee themselves wafers in 2-3 years that it takes to bring a new fab online.

TSMC is rightfully conservative. If they commit to spending an extra $30b on a fab now that won't make a single wafer until 2029, without any guarantees from big tech, they're stupid. Who knows if the demand will still be there (my guess is yes, but who knows?).

In my opinion, I think it's getting close to this. Nvidia will surpass Apple as TSMC's biggest customer this year. This will start a war for TSMC wafers in 2026 in my opinion. When you have that much demand, customers will be willing to pay in advance.

There is already a war for memory, silver, copper, energy. No reason why chip production won't be next.
by rekabis | 2026-01-26 18:21:18+00:00
Capitalism, greed, and laziness has dug the hole companies now find themselves in.

Job seekers have been on the receiving end of “applicant abuse” for many years, now. Ridiculous skill requirements, endless rounds of interviews, unreasonable tests, bait-and-switch tactics, suddenly-revocable WFH terms, and much, much more.

And now you complain when job seekers try to obtain the upper hand? Oh, the horror of applicants who aren’t grovellingly grateful and gratuitously debasing themselves for this “fantastic opportunity” that your company is providing! Why won’t applicants be the obedient little dancing monkeys companies demand?

Learn to live in the bed you’ve made for yourself. The entire process of hiring is irredeemably toxic and absolutely every issue can be traced back to business decisions.

Applicants are only responding appropriately and rationally.
by WarmWash | 2026-01-26 18:21:22+00:00
I can't help but think of my earliest days of coding, 20ish years ago, when I would post my code online looking for help on a small thing, and being told that my code is garbage and doesn't work at all even if it actually is working.

There are many ways to skin a cat, and in programming the happens-in-a-digital-space aspect removes seemingly all boundaries, leading to fractal ways to "skin a cat".

A lot of programmers have hard heads and know the right way to do something. These are the same guys who criticized every other senior dev as being a bad/weak coder long before LLMs were around.
by icegreentea2 | 2026-01-26 18:21:25+00:00
China was able to sustain some pretty strict zero-COVID policies much longer - all the way to late 2022.

Pain tolerance might be the wrong term. Pain tolerance implies speaks to something intrinsic about a population, while really what we're looking at is how much discomfort a population can endure before it really agitates for policy/political change, and so it's much about how a population feels, as the tools available to the government to control, manage, deflect and address the pain/discomfort.
by fleabitdev | 2026-01-26 18:21:41+00:00
When working as a senior engineer, I've never been given enough business context to confidently say, for example, "this stakeholder isn't important enough to justify such a tight deadline". Doesn't that leave the business side of things as a mysterious black box? You can't do much more than report "meeting that deadline would create ruinous amounts of technical debt", and then pray that your leader has kept some alternatives open.
by mbreese | 2026-01-26 18:22:14+00:00
I can’t really take this too seriously. This seems to me to be a case of asking “can an LLM do X?” Instead, the question is like to see is: “I want to do X, is an LLM this right tool?”

But that said, I think the author missed something. LLMs aren’t great at this type of reasoning/state task, but they are good at writing programs. Instead of asking the LLM to search with a drone, it would be very interesting to know how they performed if you asked them to write a program to search with a drone.

This is more aligned with the strengths of LLMs, so I could see this as having more success.
by eb0la | 2026-01-26 18:22:17+00:00
Until now nobody thought it was a problem.
At least not a big one.
The EU made some moves to define a "cloud computing" platform for Europe, and very little people paid attention because business-wise it was very difficult to compete with US corporations that have vast amounts of money in cash and find easy to get funding.

But now there are some (small) alternatives.

LIDL has its own cloud for retail.

And I believe T-Systems sells some cloud computing for goverments based on OpenStack...

Small steps, but steps.
by Imustaskforhelp | 2026-01-26 18:22:18+00:00
Do you wanna make a benchmark of which AI agent refers the most of any website in a specific prompt.

Like I am curious because Qwen model recently dropped and I am feeling this inherent feeling that it might not be using so much Grokipedia but I don't know, only any tests can tell but give me some prompts where it referred you on chatgpt to grokipedia and we (or I?) can try it on qwen or z.ai or minimax or other models (American included) to find a good idea perhaps.

Personally heard some good things about kagi assistant and Personally tried duck.ai which is good too. I mean duck.ai uses gpt but it would be interesting if it includes (or not) grokipedia links
by augusteo | 2026-01-26 18:22:42+00:00
Nice work. The hybrid BM25 + vector + LLM reranking approach is exactly what I've been wanting for my notes.

I use Obsidian with hundreds of markdown files. The built-in search is fine for exact matches but misses conceptual connections. Does this handle large vaults well? I'd love to point it at my notes plus meeting transcripts.
by swiftcoder | 2026-01-26 18:22:43+00:00
I know several folks who've migrated from US -> EU tech roles in the last few years. Yes, you earn less and pay (somewhat) more taxes. But if you have a few kids the difference in cost of education pretty much wipes out the difference, and some folks really value the stress reduction of a robust social safety net (layoff protections, healthcare coverage while unemployed, etc)
by philipkglass | 2026-01-26 18:22:55+00:00
Some people say that human jobs will move to the physical world, which avoids the whole category of “cognitive labor” where AI is progressing so rapidly. I am not sure how safe this is, either. A lot of physical labor is already being done by machines (e.g., manufacturing) or will soon be done by machines (e.g., driving). Also, sufficiently powerful AI will be able to accelerate the development of robots, and then control those robots in the physical world.

I would like to believe that we're about to see a rapid proliferation of useful robots, but progress has been much slower with the physical world than with information-based tasks.

After the DARPA Urban Challenge of 2007, I thought that massive job losses from robotic car and truck drivers were only 5-8 years away. But in 2026 in the US only Waymo has highly autonomous driving systems, in only a few markets. Most embodied tasks don't even have that modest level of demonstrated capability.

I actually worry that legislators -- people with white collar jobs -- will overestimate the near-term capabilities of AI to handle jobs in general, and prematurely build solutions for a "world without work" that will actually be long-delayed. (Like starting UBI too early instead of boosting job retraining, leaving health care systems understaffed for hands-on work.)
by threethirtytwo | 2026-01-26 18:22:55+00:00
I think it’s usage patterns. It is you in a sense.

You can’t deny the fact that someone like Ryan dhal creator of nodejs declared that he no longer writes code is objectively contrary to your own experience. Something is different.

I think you and other deniers try one prompt and then they see the issues and stop.

Programming with AI is like tutoring a child. You teach the child, tell it where it made mistakes and you keep iterating and monitoring the child until it makes what you want. The first output is almost always not what you want. It is the feedback loop between you and the AI that cohesively creates something better than each individual aspect of the human-AI partnership.
by hxugufjfjf | 2026-01-26 18:23:06+00:00
Its also because they are only as good as they are with their given skills. If you tell them "code <advandced project> and make no x and y mistakes" they will still make those mistakes. But if you say "perform a code review and look specifically for x and y", then it may have some notion of what to do. That's my experience with using it for both writing and reviewing the same code in different passes.
by mythz | 2026-01-26 18:23:42+00:00
I wouldn't use Claude API Key pricing, but I also wouldn't get a Claude Max sub unless it was the only AI tool I used.

Antigravity / Google AI Pro is much better value, been using it as my primary IDE assistant for a couple months and have yet to hit a quota limit on my $16/mo sub (annual pricing) which also includes a tonne of other AI perks inc. Nano Banana, TTS, NotebookLM, storage, etc.

No need to use Anthropic's premium models for tool calling when Gemini/MiniMax are better value models that still perform well.

I still have a Claude Pro plan, but I use it much less than Antigravity and thanks to Anthropic axing their sub usage, I no longer use it outside of CC.
by citizenpaul | 2026-01-26 18:23:51+00:00
Am I the only one that is going to call this out? Am I the only person that cloned the repo to run it and found out it does nothing? This is disingenuous at a best. This is not a working project, they even admit this at the end of the article but not directly.

>Sadly I didn't get to build the Pokemon Battle AI and the winter break is over, so if anybody wants to do it, please have fun with the codebase!

In other words this is just another smoking wreck of an hopelessly incomplete project on github. There is even imaginary instructions for running in docker which doesn't exist. How would I have fun with a nonsense codebase?

The author just did a massive AI slop generation and assumes the codes works because it compiles and some equivalent output tests worked. All that was proved here is that by wasting a month of time you can individually rewrite a bunch of functions in a language you don't know if you already know how to program and it will compile. This has been known for 2-3 years now.

This is just AI propaganda or resume padding. Nothing was ported or done here.

Sorry what I meant to say is AI is revolutionary and changing the world for the better................................
by adzm | 2026-01-26 18:24:21+00:00
Perhaps relevant is that probably only 25% of the IDs that get passed to the select actually have values and this is using one thread for the benchmark. It's too convoluted to share, but indeed when using the in memory database on a lower spec laptop currently I still get up to 20-30m reads per second, pretty close to the 40m on the big box.
by personjerry | 2026-01-26 18:24:28+00:00
I don't really understand how this differentiates against the competition.

> Independence

Any "agent" running against code review instead of code generation is "independent"?

> Autonomy

Most other code review tools can also be automated and integrated.

> Loops

You can also ping other code review tools for more reviews...

I feel like this article actually works against you by presenting the problem and inadequately solving them.
by ativzzz | 2026-01-26 18:24:38+00:00
> special government LLM to implement direct democracy

I like your optimism, but I think realistically a special government LLM to implement authoritarianism is much more likely.

In the end, someone has to enforce the things an LLM spits out. Who does that? The people in charge. If you read any history, the most likely scenario will be the people in charge guiding the LLM to secure more power & wealth.

Now maybe it'll work for a while, depending on how good the safeguards are. Every empire only works for a while. It's a fun experiment
by spwa4 | 2026-01-26 18:25:19+00:00
Strange how things evolve. When ChatGPT started it had about 2 years headstart over Google's best proprietary model, and more than 2 years ahead to open source models.

Now they have to be lucky to be 6 months ahead to an open model with at most half the parameter count, trained on 1%-2% the hardware US models are trained on.
Show HN: The Forecaster Test- based on Tetlock's superforecasting research
by joshuafkon | 2026-01-26 18:25:50+00:00
In Tetlock's 20-year Expert Political Judgment study, domain experts performed no better in their own field than outside it — and "hedgehog" specialists actually did worse when predicting within their specialty. The Good Judgment Project (Tetlock & Mellers) later found that superforecasters weren't dramatically smarter than average participants — what separated them was thinking style.
What predicts accuracy? Calibration, Bayesian reasoning, and willingness to update beliefs. These traits beat raw intelligence and domain knowledge.
I built a 10-minute test that measures them:

Bayesian updating: Commit to a probability, receive new evidence, update. Tests whether you move the right direction and magnitude.
Calibration: When you say 80% confident, are you right 80% of the time?
Replication prediction: Predict whether famous psychology studies replicated. Instant feedback since outcomes are known.

Free, no signup. Results show where you're calibrated vs. overconfident, and how you handle disconfirming evidence.
Looking for feedback on questions and scoring. Research basis is Tetlock, Mellers, Baron, and Stanovich — but I'm sure there are improvements to make.
by ajsnigrutin | 2026-01-26 18:25:53+00:00
First you're going to insult me, call me a sunshine, and defend what the UK government is doing, because there's currently a way to bypass a restriction that shouldn't exist implemented this way in the first place?

So, by your logic, russian censorship of media is ok too, just use a vpn, right? Chinese firewall? Just use a VPN! Turkey social media blackouts? VPN!
by eb0la | 2026-01-26 18:26:08+00:00
But in the other hand you don't have to worry about mass shootings.
You can freely walk (mostly) wherever you want without risking your life (that is not normal in most of the world).
And you're not going bankrupt because of a minor/medium medical condition.

Europe is a _very_ different place.

Not everything here is so bad.