skysight-inc/HackerNews huggingface dataset:
I have both a US and an Australian bank account.

Zelle sucks compared to what's considered table stakes overseas.
This is pretty inaccurate. Absent actual laws that people are aware of, you described rule of man, the opposing governance form.

Rule of laws means there are known laws everyone has to follow no matter who they are.

https://en.m.wikipedia.org/wiki/Rule_of_law
Reading is like 5000 years old. It requires almost no resources to learn and do. I don’t think this is a spending problem.
So protecting models behind API isn't working, ha?
You should write more about this on a blog or something, it's interesting and you seem knowledgeable.
There's a backport https://packages.debian.org/bookworm-backports/source/smartm...
I don't know why you've been downvoted. This is a 100% correct history. "Open source" was specifically coined as a synonym to "free software", and has always been used that way.
What's to say it wouldn't have been even worse workout the money? I don't think you can draw that conclusion from just this data point.

That said, education certainly needs major reforms. I like how Sweden is going full Luddite for learning: https://www.theguardian.com/world/2023/sep/11/sweden-says-ba...
Visa and Mastercard are very strict on merchants (so in this case Twitter), when it comes to any kind of fraud. So this I would take as a signal that Twitter will have to completely clean out frauds. Selling directly through Twitter will then give a high level of fraud protection to customers.

Compare this to Instagram and Facebook, where over half of all paid advertising are outright frauds, and where their policy is to allow frauds even when users have reported them.

Letting customers purchase directly on social media instead of social media just being ad platforms for scams could be a positive thing. Meta would have to go the same way then. And maybe – maybe – we can move on from the ad/scam/bot hellscape into a system where social media platforms are instead funded by taking a percentage on direct sales from businesses selling there. That would be a much healthier system for everybody involved, except for scammers and ad professionals.
Realistically if we perish and there is no comparable conscious life then no one can even care whether a bunch of machines we spawned to assist us continues to exist.

Thinking 'it is good' is a product of your consciousness. When there is no one to judge then there is no 'good'.
For now.

How long until these get pushed up to the constitutional courts where the judges can be legally bribed?
>Does that mean proprietary AI is done? No.

Perfectly stated.

The AI jump to conclusions mat is so worn down, it's become paper thin. The shock of DeepSeek's costs does not auto-magically force all LLMs to become opensource. Silicon Valley tech has always favored whomever delivers inside the trifecta of cheaper, better, faster triangle. Anyone with an MBA should know this includes open-source LLMs. As of today, DeepSeek is ahead. As soon as OpenAI answers with a new 'fastfood dollar menu' for ChatGPT, with 'even more special' secret-sauce ingredients, we're going to see them back to normal business.
Probably? Wouldn't they use debian.org as their identity?
I think the point is
- OpenAI scraped public data - d1
- Trained their model to produce output - d2
- DeepSeek used d2 to reinforce their model

OpenAI is mad about d2 (not d1). I'm not sure using public data is "stealing". In summary, these are two different things & need to be separate.
I don’t care for Sam Altman and his general untrustworthy behavior. But DeepSeek is perhaps more untrustworthy. Models from American companies at least aren’t surprising us with government driven misinformation, and even though safety can also be censorship, the companies that make these models at least openly talk about their safety programs. DeepSeek is implementing a censorship and propaganda program without admitting it at all, and once they become good at doing it in less obvious ways, it can become very damaging and corrupt the political process of other societies, because users will trust the tools they use are neutral.

I think DeepSeek’s strategy to announce a misleading low cost (just the final training run that optimizes a base model that in turn is possibly based on OpenAI) is also purposeful. After all, High Flyer, the parent company of DeepSeek, is a hedge fund - and I bet they took out big short positions on Nvidia before their recent announcements. The Chinese government, of course, benefits from a misleading number being announced broadly, causing doubt among investors who would otherwise continue to prop up American technology startups. Not to mention the big fall in American markets as a result.

I do think there’s also a big difference between scraping the Internet for training data, which might just be fair use, and training off other LLMs or obtaining their assets in some other way. The latter feels like the kind of copying and industrial espionage that used to get China ridiculed in the 2000s and 2010s. Note that DeepSeek has never detailed their training data, even at a high level. This is true even in their previous papers, where they were very vague about the pre training process, which feels suspicious.
yep, happened to my Fenix 7 as well immediately as soon as I activated workout mode (i.e. started GPS).

Ended up with factory reset and restore from Connect App backup.
I wondered how I should feel about that thought process. However, I might have a similar thought process when inebriated.
AI Generates Real Estate Offers for $1–Skip the 2.5% Broker Fees
OpenAI invested in non-open foundation models and DeepSeek came and (approximately) dethroned them. I don't agree with the conclusion of the article, but the statement "open-sourcing a model lets another company dethrone you" is also not great. I'd stand behind "in the world of AI in 2024/2025, regardless of whether the model is open or not, someone is likely to come and dethrone you in a snap".
Strange way to kill the US auto industry.
Disney owns ABC News; OpenAI almost certainly scraped their text data
> But while trying to accomplish it he's burned the goodwill and much of the public perception of Twitter/X as a good company.

Has he? If we step out of the echo chamber of HN and Reddit he is immensely popular. I was actually shocked around the holidays seeing many friends and family that are not internet junkies have a very strong overall opinion of Musk.
Coronaviruses are RNA based and do not carry the reverse-transcriptase proteins (as retroviruses like HIV do) which would be necessary to embed genetic material in host cells' DNA. They directly cause production of the proteins to copy their RNA into new virus capsids.
Meta has already done this with Whatsapp payment.
* Swartz

But yes.
Are people getting hung up on NVDA's fall? It feels like most aren't drawing direct logical links - the Jevons paradox doesn't apply directly to stock prices.

I think the situation is fairly clear with some understanding of finance / equity markets. My analysis of the market and competitive situation:

Deepseek's cheaper LLM services + providing open models for other hosts to provide

=> overall prices for using LLM services will fall due to competition (lower prices + more hosts entering the market); AI users won't pay so much for LLM services

=> the major LLM hosts/providers won't be able to project such high revenues or even have the funds to purchase as many GPUs (they will receive less capital investment to buy GPUs since revenues per dollar invested are lower; their stock valuations will fall)

=> corporate demand for Nvidia cards will fall (AND consumer demand will not rise as much to counteract it for multiple reasons)

On the basis of this possible logic, portfolio managers and algorithms project lower growth/revenue for Nvidia and sell off its stock, setting off the usual chain reaction as other managers notice the downward price action and follow suit in order to stop further losses.

Now, if the new hosts entering the market with lower prices attract significantly more users (instead of merely competing away margins) as we might expect by the paradox, then demand for GPUs might grow instead of shrink instead. If more portfolio managers think this is likely, then it's likely for NVDA's price to recover, and it would be wise to get back into the stock once the worst of the fall is over.
Draining the battery from 100% to 0% in under an hour (as other commenters have mentioned) is the opposite of this, as that will necessarily dump a lot of heat.
Only very locally, the Japan tsunami was an order of magnitude more energy and aiui earthquake tsunamis happen particularly with certain kinds of seafloor displacement. It's not just about the amount of energy but how that energy is applied, impact energies dissipate quickly with distance.
(+ ha ha ha ha)
There’s an account number on the register, you send money to it by app or web. For others a debit card will work. Apple is not required.

You can send a friend 25 cents for half a cookie or ten thousand for a deposit on an apartment, all free.
This only looks stupid in hindsight.

I worked on something back then that had to interface with payment networks. All the payment networks had software for Windows to accomplish this that you could run under NT, while under Linux you had to implement your own connector -- which usually involved interacting with hideous old COBOL systems and/or XML and other abominations. In many cases you had to use dialup lines to talk to the banks. Again, software was available for Windows NT but not Linux.

Our solution was to run stuff to talk to banks on NT systems and everything else on Linux. Yes, those NT machines had banks of modems.

In the late 90s using NT for something to talk to banks is not necessarily a terrible idea seen through the lens of the time. Linux was also far less mature back then, and we did not have today's embarrassment of riches when it comes to Linux management and clustering and orchestration software.
While I'm sure there are monetary benefits of making your LLM proprietary, I'm not sure there's a benefit to extending someone else's proprietary LLM.
Sure, but in that scenario, it's a bit like the Last of Us characters being concerned about electrical meter readings. We'll have much bigger problems.
> Why not just call them freeware LLMs, which would be much more accurate?

Most of the public is unfamiliar with the term. And with some of the FOSS community arguing for open training data, it was easy to overrule them and take the term.
I tried it a few months ago and it was a buggy mess with strange defalts. Totally unusable on a couple of the projects I tried it on.
763-Day Legal Quest Against a Call of Duty Permanent Ban
> men who are dangerous/abusive/predators stay in the dating pool longer

Not only this but they can use these apps to find their victims faster and easier than ever before.

> This is explicitly unfair to normal men

I think it's also unfair to women that they have to pick up the extra work that was done by the "community" before. And a loss for social cohesion too.

I am wondering though how someone who just ended a relationship could deal with this scenario? As a male you arguably look like one of the abusers because you're older and looking for a partner and as a female you're seen as less attractive. At the same time you're probably also more picky because of the break-up. Seems like they're the most shit-out-of-luck here regardless of what's between their legs.

I also wonder if this will push us towards being with our "high-school sweethearts" for longer than we would otherwise?

> Maybe financial ruin in child support, but explicitly not death.

Yeah absolutely, I'm personally not aware of the exact numbers for this but I wouldn't be shocked if you're right. Also I'd include things like false accusations, or getting her brothers/father to "take care of" the ex. Also we need to account for things like baby entrapment.

Also men tend to express their aggression physically whereas women tend to express it through reputation destruction. This also partially explains where we are today: women are afraid of male physical repercussions, men are afraid of female societal repercussions. Interestingly, it also mimics a lot of the rhetoric you see about "all males being bad" since it's a form of reputation destruction - whereas the male "comebacks" tend to focus on physical acts of violence that they "could do but won't".
How is the photo quality? I love the pictures from the old 12MP sensor + Googles software, but I understand this is not in Lineage?
Surprisingly when it comes to software, music, and movie stealing we find that stealing requires one party to lose something but when it comes to OpenAI stealing is happily colloquially defined. What an interesting curiosity.
Ax: The Next Evolution in AI Agent Software Design
There's a lot of egg on people's faces now. DeepSeek shows there's nothing special about America or its economic system that breeds innovation. DeepSeek shows how these tech oligarchs greatly overplayed their hand and along with the president, bamboozled the taxpayer to enrich each other. I just hope the voters remember this in 2 years, 4 years and beyond.
For sure, thank you for that hint. One of the most important things to consider is that something like this can't be misused on someone else, e.g. as a surveillance tool.

I should have clarified, I'm only building this for myself and my own use, there are no plans to take it further than that. Basically, I am trying to learn while building something that satisfies my own needs.
A shout-out for AI studies that don't make the headlines
If anything, this revealed they aren’t actually that much behind. It’s just that the US’ lead is completely inflated and that the business models they dreamt of were finicky at best.
I'm mostly concerned about the power cord getting unplugged if, say, somebody is vacuuming around the area. On top of the usual "whole machine gets turned off" failure mode that happens maybe 10-20x a year in my neighborhood because of power loss there is a "machine is turned on but HDD is powered off" case.
Or maybe an upset former student.
What they are talking about is using AI as a proxy for racial, gender, and age discrimination. For instance, if you use AI for an adverse decision regarding employment, housing, education, or financial decisions you need to justify those decisions against persons from a protected class.

If you cannot explain why you have made such decisions, then the state will look at disproportionate impact. EG: You hired/lent to/rented to black people 25% less often than you did to white people. "Because the AI said so." doesn't cut it.
Would I like it if everything was easy and nothing was hard?

Absolutely!

Is sitting around waiting for that to happen going to work?

Absolutely not!

There's two questions being conflated; should someone have to carefully watch their diet, or spending, or browsing? It's easy to argue that they shouldn't, and give examples of things that would make it so they don't (remove combo meals above a certain caloric amount, make credit hard to access, etc).

None of that changes that we live in the here and now, and we can inflict minor change on society, but major changes on ourselves.
The "lords" in US (not all, but the great majority) are self-made and in the process of making themselves they created significantly more value for the society, which ended up benefitting most of us.

The titles in EU are inherited or bought with inherited money.
> "The link you shared says bots are banned."

The post says "...bots or generated responses..." so you are incorrect. If you have concerns about the specifics, the HN moderators can be contacted at the email address in the FAQ and guidelines page.
No current phone from any manufacturer that's reasonably desirable is as small as the 4a, and few of any size have a headphone jack.
indeed!

At a high level I see convergence of styles, topics, behaviors to a generic form, both in "AI" and social media. Which to me suggest that the "AI" solutions are doing exactly what we would do ourselves, just faster.
We absolutely had a choice (D), in that no one was forced to call it "open source" at all, which was arguably done to unfaithfully communicate benefits that don't exist. This is the part that riles people up, and that furthermore is causing collateral damage outside the AI bubble, and is nothing like Betamax vs. VHS.

If you want to prioritize pragmatism, that every discussion of this includes a lengthy "so what open source do you mean, exactly?" subthread proves this was a poor choice. It causes uncertainly that also makes it harder for the folks releasing these models to make their case and be taken seriously for their approach.

We should probably call them "free to run", if the "it's cheap" connotation of "freeware" needs to be avoided. Or maybe "open architecture" to appreciate the Python file that utilizes the weights more.
AI code review will very probably have signal-to-noise problems.
It is good to see practical solutions aimed at addressing this.
I wonder if fine-tuning models would help - this isn't addressed in the blog.
Not everything virtuous is rewarded monetarily but we aspire to be virtuous, no?
They're raising capital.
The feature is inspired by this reddit post: https://www.reddit.com/r/NOTHING/comments/1dyuak6/nothing_os...
(Sorry, I am new to HN and do not know how to properly post image links here)
The best way I can think of is similar to what I heard from Jaron Lanier (he may not be the first person to explain this). Basically what you do is send something massive out there that will gravitationally tug it into a collision course with Earth. Obviously this will take quite a bit of time but if your calculations are correct it will pretty much guarantee impact.
Anecdotally I went through a severe bout of IBS-C in my early 20s and the "cure" was to cut out wheat and dairy for an extended period of time (about a year and a half), at which point I was able to reintroduce them into my diet and I've been ~fine for about 20 years now. I've hypothesized that the lining of my intestine(s) had been damaged by the proteins and/or starches/sugars in those foods and needed a break and time to heal. I'm not a medical professional and my hypothesis has never been confirmed by one.
Can't wait for the reenactment of "Don't look up!"
I love Sublime Text and would use it and pay for a license regularly if it were open source.
Which TikTok will have to decline again and shutdown now with the guilty being transferred to Trump. Doesn't sound like a smart move.
sure because that is how the gdpr is implemented with national enforcement but they still have to submit draft decisions to the gdpr cooperation mechanism and get consensus and the EDPB gets final say. it is very much an EU/EEA process
The Nvidia panic stems, in part, from the possibility that this is just the first of many potential significant optimization leaps.
I think the lesson of DeepSeek is 'no' -- that by software innovation (ie., dropping below CUDA to programming the GPU directly, working at 8bit, etc.) you can trivialise the hardware requirement.

However I think the reality is that there's only so much coal to be mined, as far as LLM training goes. When we're at "very dimishing returns" SoC/Apple/TSMC-CPU innovations will deliver cheap inference. We only really need a M4 Ultra with 1TB RAM to hollow-out the hardware-inference-supplier market.

Very easy to imagine a future where Apple releases a "Apple Intelligence Mac Studio" with the specs for many businesses to run arbitrary models.
And those objective set of cultural values are, apparently... a sort of parody of 90s corporate culture, a sort of polite version of Michael Scott. Like, no-one ever _actually_ wrote like LLMs tend to write; it reads as a parody of a now slightly obsolete corporate-speak.
Your math is wrong:

> This felt false to me, LED bulbs are generally 10x more efficient, so the average number of lights would have had to increase 10 fold, and this is ignoring the savings from not having AC cool those other 50 watts a bulb that went to heat.

The first 5W also went into heat. Perhaps with the exception of light escaping through a window, *every* watt that goes into a lightbulb comes out as heat for your AC to cool.

I would not be surprised if there were a 10x increase in use of lighting with LEDs.

Not taking Wikipedia (or any source) on blind trust is always wise. More often than not, when you kick tires, you come back to folklore. It's fine for big things, but details are often wrong. Ditto for newspapers, for that matter.
They can't 'fix' the speed of light. It won't drastically reduce latency of trying to live jam in a remote band or RTS game ping.

I'm no network expert but I thought it was relatively solved and problems are due to underprovisioning.

It's cool tech though. Like the 'wires' are providing back-pressure rather than the endpoint.
It could be a spending problem if we need to overcome cultural restraints. Poor communities often do not have encouragement towards reading and if the teachers are not sufficiently staffed or not skilled enough to inspire kids, I can see why kids are not interested in reading and learning.
Show HN: Coherence – Generate synthetic data for LLM testing 10x faster
We've built a data generation studio that helps engineering teams create robust test datasets for their LLM applications in a fraction of the time it usually takes. While working with hundreds of engineering teams on DevOps automation, we discovered a critical gap: everyone wants to build AI products, but acquiring, labelling, and organizing test data for tasks is a massive challenge.

The current approaches to creating "golden datasets" for LLM testing are either infrastructure-heavy (observability-based) or time-consuming (manual creation). Many teams end up relying on intuition-based development, which leaves crucial questions unanswered about model selection, edge cases, and performance optimization.

Our solution generates comprehensive, realistic test datasets tailored to your specific use cases. You provide context (existing examples, domain information, or system prompts), and it creates robust test data that helps you:

- Balance distribution across your test suite including edge cases
- Evaluate prompt effectiveness across various scenarios
- Compare and optimize model selection
- Identify and handle edge cases systematically
- Assess performance across diverse use cases
- Support rapid R&D experimentation with different data shapes

We're launching this as the first data studio focused on giving AI engineers both speed and precision in their development workflow. If you're building AI products, we'd love your feedback on our approach to making LLM testing more reliable and efficient.

Check out what we’re building at https://www.withcoherence.com/
Covid-19 is not a retrovirus. Otherwise, the people would not be able to reliably overcome it again and again. The same applies to post-covid - once you tame it by finding methods of correcting it, it goes away. I agree with you on necessity of further researches, but they require not only money, but also plenty of time, decades perhaps.
Thank you for this balanced and essential comment which is entirely true!
Does anyone have the performance delta between running this on a 768 GB setup like this where the whole thing fits in RAM, versus running it on an M4 Mac with the maxed out 128 GB?
It must be EZ mode to be a big tech executive, you somehow have all the power to make every decision while also having the ability to never take the fault for these decisions.
> when I was mentoring younger engineers

In what context? At work? If a more established coworker was "mentoring" me about how much work I was getting done and wanting detailed info about how I spend my time outside of work, I'd lie and act confused about it too.