skysight-inc/HackerNews huggingface dataset:
Just use it on the release build.
but inflation adjusted doesn't make any sense. things are less volatile now, there's high speed trading, better knowledge, easier trades, more automation, regulation, etc. it wouldn't make any sense.

even now compared to 2020 there has been a huge change in amount of retail investors.
> if DeepSeek really has found a way to train models just as good as frontier ones for a hundredth of the hardware investment

Frontier models are heavily compute constrained - the leading AI model makers have got way more training data already than they could do anything with. Any improvement in training compute-efficiency is great news for them, no matter where it comes from. Especially since the DeepSeek folks have gone into great detail wrt. documenting their approach.
Its worth clarifying you are talking about the data on the phone app, which does require connectivity as nothing is stored on the phone app, its all on Garmin's servers.

However, most if not all of the data (recorded activities or health data) can be viewed directly on your watch, without any connectivity.
First of all, I don't invest in Nvidia and like Olygopols. But it is too early to talk about Nvidia's future. People are just betting and wishing about Nvidia's future. No one knows people's what people will do in the future. what they will think? It's just guessing and betting. Their real competitor is not Deepseek. Did AMD or others release something new and compete with Nvidia's products? If NVDIA will be the market leader, this means they will lead the price. Being Olygopol is something like that. They don't need to compete for the price of competitors.
Thats 100x quarterly revenue, or 25x annual revenue.
I got pixel with Firefox for Android
No, it had an "epaper" display that visually looked a lot like eink but was a different technology
It's just their reality. I've dealt with chinese business, and they take their constraints with great attention, even if they personally don't care or even are against.

We have the same with copyrighted stuff: we have to be extra careful to not include an image, a font or a text paragraph where we shouldn't, even by mistake, or the consequences could be catastrophic. They take copyright less seriously, and I'm sure they also feel we are weird for having such constraints.

"But our situation is logic, and theirs is madness", said both parts.
I'd say it's a meme stock and based on meme revenue. Much of the 35B comes from the fact that companies believe Nvidia make the best chips, and that they have to have the best chips or they'll be out of the game.

DeepSeek supposedly nullifies that last part.
Except when it consistently gets said particular API wrong. I was using it to do basic graphql-yoga setup with R1 and then Claude Sonnet 3.5 and they both output incorrect usage, and got stuck in a loop trying to fix it.

If it can’t do something that basic and that common using a language and toolset with that much training data, then I’m pessimistic personally.

I’m yet to see Copilot be useful for any of my juniors when we pair, it gets in the way far more than it helps and it is ruining their deeper understanding, it seems.

I’ll continue trying to use these tools, but I swear you’re overselling their abilities even still.
I'm assuming the parent poster is talking about using the Garmin Connect app, which does require connectivity. You are correct, the data is visible directly on the watch.
You have an interesting notion of the value copying could provide, thanks for sharing. I can not tell you what factors helped it hit the front page or not.

I can tell you that, after clicking and reading through, having the same text repeated felt like it didn't use my attention well. That was the basis of my downvote.

Thank you for your curiosity and for sating mine.
For the uninitiated, this is the same author as the many other "The Illustrated..." blog posts.

A particularly popular one: https://jalammar.github.io/illustrated-transformer/

Always very high quality.
Obviously, it depends on context. When talking to someone live you can pick up on subtle hints such as tone of voice, or where they look, or how they gesticulate, or a myriad other signals which give you a hint to their knowledge gaps. If you're communicating via text, the signals change. Furthermore, as you interact with people more often you understand them better and refine your understanding of them. LLMs always forget and “reset” and are in flux. They aren’t as consistent. Plus, they don’t grow with you and pick up on your signals and wants.

It’s incredibly worrying that it needs to be explained again and again that LLMs are different from people, do not behave like people, and should not be compared to people or interacted like people, because they are not people.
They bought Fitbit, not pebble
This assumes hunter gatherers were better off than we are today. That's a controversial claim. You still have to survive in nature with finding food and making shelter, fending off predators, negotiating rival groups, dealing with disease and injury. It wasn't some utopian existence.
The cost for interactive video would be a requirement of 10x bandwidth, basically to cover idle time. Not efficient but not impossible, and definitely wouldn’t change ISP business models.

The latency benefit would outweigh the cost. Just absolutely instant video interaction.
They have not verified the claims but those claims are not a "vague rumor". Expectations of discounted cash flows, which is primarily what drives large cap stock prices, operates on probability, not strange notions of "we must be absolutely certain that something is true".

A credible lab making a credible claim to massive efficiency improvements is a credible threat to Nvidia's future earnings. Hence the stock got sold. It's not more complicated than that.
Ok, then, why are you going for a 120K/year job, which will most likely destroy your soul after a few years, as all corporate jobs do, if you have "several potential customers" worth 40K/year each?

If you knew for sure this thing was worth what you say, you would stay. But it's not worth that, it's imaginary, and you know it.

Tbh, I'd just move on. Learn from the exp. etc. You deserve to get what you want, and the other guy deserves a real co-founder (no offense to you).

Just go find new things to do, also you mentioned you were in college, you still have like 100 shots left to take on.
Ask HN: Is Receiver Side Scaling beneficial for multiuser server (MySQL, Nginx)?
For example in such configuration:

One server with Intel NIC + FreeBSD with RSS support compiled + Mysql + Nginx + many users with their wordpress based web pages and Prestashops.

Is this a good match or RSS is created for totally different aplications and Apache and MySQL are not even able to make any use of RSS?
Yes, I don't disagree, but it doesn't have much to do with my argument.
Any data in the app. It just doesn't work offline, at all. Like they looked at a book chapter on basics of data caching and went "nah, not doing that, that's too f#cking advanced".
Nvidia chip demand should increase from DeepSeek's release.

This market doesn't make any sense.
Indeed, once we fall in love with a model we can usually find some evidence for the model.
Except it’s not clear at all that this is actually the case. It’s entirely conjecture on your part.
Your strategy might work for you, but for me using a smartwatch that only had 30h of battery life was super painful. One of the reasons I use a smartwatch is for sleep tracking (+alarms/timers/flashlight/notifications), which means I can't charge it overnight and every day is too dynamic to always charge it at the same time. Plus I miss out on notifications and access to other features I use hourly when I put it on charge.

With my Garmin and 2 week+ battery life, the first <15% battery warning still gives me 3 days to put it on charge or turn on battery saving and turn that into 5+ days which is plenty of time to find a convenient time for charging. I don't think it ever died on me due to low battery, unlike my previous smart watches. Ok, I lied, it died once on a month long trip, but a split USB cable and a hair tie let me charge it right back up.

The low battery life might be ok if you do not use your watch for sleep tracking or alarms. Or flashlight. Gosh, I love my flashlight on wrist.
Yeah nah!
The biggest discussion I have been on having this is the implications on Deepseek for say the RoI H100. Will a sudden spike in available GPUs and reduction in demand (from efficient GPU usage) dramatically shock the cost per hour to rent a GPU. This I think is the critical value for measuring the investment value for Blackwell now.

The price for a H100 per hour has gone from the peak of $8.42 to about $1.80.

A H100 consumes 700W, lets say $0.10 per kwh?

A H100 costs around $30000.

Given deepseek, can the price of this drop further given a much larger supply of available GPUs can now be proven to be unlocked (Mi300x, H200s, H800s etc...).

Now that LLMs have effectively become commodity, with a significant price floor, is this new value ahead of what is profitable for the card.

Given the new Blackwell is $70000, is there sufficient applications that enable customers to get a RoI on the new card?

Am curious about this as I think I am currently ignorant of the types of applications that businesses can use to outweigh the costs. I predict that the cost per hour of the GPU dropping such that it isn't such a no-brainer investment compared to previously. Especially if it is now possible to unlock potential from much older platforms running at lower electricity rates.
It's not meaningless to people who accept that the vast majority of these reportings always use non-adjusted numbers and usually call out when that isn't the case.
Basically, had it not been for AT&T lawsuit, or Microsoft losing interest with either Xenix or Windows NT/POSIX subsystem, and Linux would hardly matter.

You're pointing out, in other words, that UNIX/POSIX is what matters, regardless of the package.
I've had both experiences strangely enough.
Was open-sourcing Linux a cynical, offensive move to devalue commercial Unix (a scheme hatched by duplicitous Finns)?

But more seriously, DeepSeek is a massive boon for AI consumers. It's price/performance cannot be beat, and the model is open source so if you're inclined to run and train your own you now have access to a world-class model and don't have to settle for LLaMA.
You could try OpenHands + OpenRouter + Llama (https://docs.all-hands.dev/modules/usage/llms/openrouter)
I haven't tried it and don't know how it would go.
I’d imagine that what you say holds true for most people living in cities.

I’ve gone to a great deal of trouble to make sure that this doesn’t apply to me and my family. Obviously, when we are in an urban environment, there is a lot of camera coverage. But when I have a conversation or just share an opinion with a stranger, if I think that is going to become part of the public record or be part of some big-data company database, I’m just not going to bother communicating with that person.

There are plenty of people in the world who value their own integrity as an individual person far too much to wire themselves up to be the tip of the tentacle for the tech brohood. Phones are bad enough.
Whoa, I loved that app! I used to track scores for intramural games in college. the UI was so clean and simple!
Not compared to these recent losses, but compared to all history it’s very possible, the value of the dollar drops by orders of magnitude as you go back in time.
I just wish integrations were better across the board. I'd buy a Pebble because i love eInk, but my apple watch is just going to be nicely integrated into my apps, ios, etc. Hell even my car as a Key.

Lockin sucks as a user :/

(though there are of course differences between the target features between Apple Watch and Pebble, i'm ignoring that)
I loved my pebble and ended up backing the original product and buying a second. Both broke and when I reached out to support they said there was nothing they could do...

I loved the devices but that put a pretty bad taste in my mouth for longevity
For the overall economy, sure... for Nvidia, no

A huge increase in fuel efficiency is great for the economy, horrible for fuel companies
Wait no, there is actually PLENTY of evidence that performance continues to scale with more compute. The entire point of the o3 announcement and benchmark results of throwing a million bucks of test time compute at ARC-AGI is that the ceiling is really really high. We have 3 verified scaling laws of pre-training corpus size, parameter count, and test time compute. More efficiency is fantastic progress, but we will always be able to get more intelligence by spending more. Scale is all you need. DeepSeek did not disprove that.
I like the "fastest growing app/magazine/whatever" when the competition has been there for 50+ years.
Pebble Time (Steel) Kickstarter is the only crowdfunding I truly regret missing out on. I remember seeing it at the time, but I think the reward levels I wanted were sold out or something.

Even in retrospect it seems weird that it failed the way it did.
I can't say about how good they are, but over 400,000 CS graduates in China [1] per year sounds like a lot.
https://www.ctol.digital/news/chinas-it-boom-slows-computer-...
Things aren’t less volatile in terms of extreme events. Look in depth at say the 2010 flash crash one of the all time great examples of very short term volatility.

Similarly, longer term we still see huge shifts such as the COVID dip before all that money flooded the markets.
I'd go with transactions too. Either way, a company is not a family. No hard feelings if I leave my company or my company lets me go.
Ya but you kind of get painted in corner sometimes. And sunken cost fallacy kicks in.
I wish me a budget 10000 mAh size "phone slab format/shape" power bank with like 18W output at 9~12V kind of "fast charge" style, and a built in Google air tag.
They already have a button and a battery and a case; only need to add the BLE and the Google-mandated buzzer.
I'd pay 5 bucks more than for the competition without the integrated tracker. That should easily cover the cost, right?
> leading AI model makers have got way more training data already than they could do anything with.

Citation needed.
I agree with this, maybe I'd summarize things in a slightly different way: think of employment as a mutually beneficial transaction. That doesn't necessarily mean simply working the contracted hours, but keep in mind that jobs are, these days transactional in nature.

I can go above and beyond, work on the weekends etc, but there should be a benefit to me. That could be because I learn something and it sets me up for my next job, I increase my chances of a promotion, or just that it's something interesting to me personally.

I think there is probably less cynicism this way too, because this is how most companies look at employees too.
You can absolutely hook an antenna to a spec-an, but how do you calibrate the result? I can get a power measurement of mV or dBm at the instrument input, but that's not how the regs are written.

They're written as field strength in free space (microvolts per meter), which as I understand it, either requires a calibrated field probe, or a calibrated antenna. I'm sure there's a way to perform such calibrations from first principles, but that's where I'm invoking "tricky". If you've got a trick to it, please share.

In practice, Part 15.23 is pretty generous about home-built equipment, and I think since the "200 foot" thing came from the FCC's own mouth, if you can show that you walked the perimeter with a portable radio and confirmed that you're good, that probably shows good faith on the power issue.

...

Absolutely yes a spectrum analyzer is helpful to make sure your harmonic filtering is working. I would put that forth as "good engineering practice" under 15.5, and it's far more than any hobbyist could be reasonably expected to do even just a few years ago; this equipment has gotten mindbogglingly affordable and accessible.
Not quite, I believe this sell off was caused by DeepSeek showing with their new model that the hardware demands of AI are not necessarily as high as everyone has assumed (as required by competing models).

I've tried their 7b model, running locally on a 6gb laptop GPU. Its not fast, but the results I've had have rivaled GPT4. Its impressive.
The exceptions are not minor. Some groups can be called mentally ill, but other similarly situated groups cannot.

It's a capitulation to the idea that speech standards should be determined by public opinion and not by reason, evidence and a scientific mindset.
Not surprising there - a maxed out Mac Studio is a great AI homelab, giving you way more bang for the buck than nVidia offerings.
there's evidence that performance increases with compute, but not that it scales with compute, e.g. linearly or exponentially. the SOTA models already are seeing diminishing returns w.r.t parameter size, training time and generally just engineering effort. it's a fact that doubling, say, parameter size does not double benchmark performance.

would love to see evidence to the contrary. my assertion comes from seeing claude, gemini and o1.

if anything I feel performance is more of a function of the quality of data than anything else.
I didn't give up.

I pivoted to content creation.
Please, please open up a London region. I would switch immediately.
How do you interpret Bulletin 63?

https://transition.fcc.gov/oet/info/documents/bulletins/oet6...
I looked up Tyson Chicken's profits:

https://www.macrotrends.net/stocks/charts/TSN/tyson-foods/gr...

They had a phenomenal second half of 2021 but it quickly came down to below their average.

Food inflation in general follows the same pattern. Big spike around covid and then settling back down to historical averages:

https://tradingeconomics.com/united-states/food-inflation

There's huge corporations on both sides of these deals. Tyson Chicken has a 22% market share and Walmart has a 23% share of the grocery market. Practically neither is going to be able to bully the other. The little guy? To some extent sure, but distributors exist too and Sysco probably isn't getting bullied around either.
No, that means that they're earning enough in one year to cover their entire valuation. You want something like 10:1 p/e which means that the next 10 years earnings are factored in to cover their present valuation.
> [...] this technology which has progressed only by increasing data volume and variety

Sure, if you ignore major shifts after 2022, I guess? Test-time-compute, quantization, multimodality, RAG, distillation, unsupervised RL, state-space models, synthetic data, MoEs, etc ad infinitum. The field has rapidly blown past ChatGPT affirming the (data) scaling laws.

> [...] where when one output (, input) is obtained the search space for future outputs is necessarily constrained

It's unclear to me why this matters, or what advantage humans have over frontier sequence models here. Hell, at least the latter have grammar-based sampling, and are already adept with myriad symbolic tools. I'd say they're doing okay, relative to us stochastic (natural) intelligences.

> With relatively weak assumptions one can show the latter class of problem is not in the former

Please do! Transformers et al are models for any general sequences (e.g. protein structures, chatbots, search algorithms, etc). I'm not seeing a fundamental incompatibility here with goal generation or reasoning about hypotheticals.
Having a temperature preference for steak is just that, preference. Saltiness is a preference. As is most things in cooking.

Raw dough is always raw dough. You can't fake rising, etc.

Not to mention, if you watch cooking/baking shows, you'll see just how much overlap there really is. Some challenges in Masterchef involves baked goods, cakes, macaroons, etc. Some challenges in the Great British Baking Show involves cooking things. Either to make savory pies or to make compotes or jams, etc.
1. Nobody has replicated their DeepSeek's results on their reported budget yet. Scale.ai's Alexander Wang says they're lying and that they have a huge, clandestine H100 cluster. HuggingFace is assembling an effort to publicly duplicate the paper's claims.

2. Even if DeepSeek's budget claims are true, they trained their model on the outputs of an expensive foundation model built from a massive capital outlay. To truly replicate these results from scratch, it might require an expensive model upstream.
Mark my words, anything that comes of anti-aging will ultimately turn into a subscription to living.
Looks it tries to identify Apple devices and goes to Pixel for everything else.

const platform = navigator.platform || '';
const userAgent = navigator.userAgent || '';
const isAppleDevice = /iPhone|iPad|MacIntel/.test(platform) ||
/iPhone|iPad|Mac OS/.test(userAgent);

// Set redirect URL and message based on device
const redirectUrl = isAppleDevice
? 'https://www.apple.com/watch'
: 'https://store.google.com/product/pixel_watch_3?hl=en-US';

Edit: per erohead, that change was made after your comment.
The trouble is the only reliable use-case LLMs actually seem good at is "augmented search engine". Any attempts at coding with them just end up feeling like trying to code via a worse interface.

So it's handy to get a quick list of "all packages which do X", but it's worse then useless to have it speculate as to which one to use or why, because of the hallucination problem.
The thing I still don’t understand is how DeepSeek built the base model cheaply, and why their models seem to think they are GPT4 when asked. This article says the base model is from their previous paper, but that paper also doesn’t make clear what they trained on. The earlier paper is mostly a description of optimization techniques they applied. It does mention pretraining on 14.8T tokens with 2.7M H800 GPU hours to produce the base DeepSeek-V3. But what were those tokens? The paper describes the corpus only in vague ways.
Nvidia's annual revenue in 2024 was $60B. In comparison, Apple made $391B. Microsoft made $245B. Amazon made $575B. Google made $278B. And Nvidia is worth more than all of them. You'd have to go very far down the list to find a company with a comparable ratio of revenue or income to market cap as Nvidia.
I don't think that's true, actually.

Do you have any evidence that suggests prison gangs are similar to street gangs?
try getting or borrowing a cheap watch and wearing it while you sleep first. I definitely don't find it comfortable enough to bother with that feature.
I think 90% of my HS psych class didn't replicate
I think that's a great take and though they appear contradictory, I actually think both perspectives are correct.

I think what both viewpoints show is that, at the end of the day, intelligence is a broad, fuzzily defined thing, and attempting to claim that a single capability is evidence of intelligence always seems to be insufficient (from either direction).

I also think your points about our own emotional attachment and thinking carefully about intelligent machines are superb. I see a lot of people chasing certain tech right now and I see a far smaller number asking whether or not this tech is something we need or want. I personally don't need to live in a world in which robots are 1:1 emulations of humans (or better). I'd be just as content to live in a world of highly specific and highly optimized collections of robots or "intelligences" only capable of doing one thing really well (a unix theory of "agents", as it were)
LeCun has nothing to do with LLamA ... that was built by Meta's GenAI group.

LeCun is in a different part of the organization - FAIR (FaceBook AI Research), and isn't even the head of that. He doesn't believe that LLMs will lead to AGI, and is pursuing a different line of research.
Didn't DeepSeek also show that pure RL leads to low-quality results compared to also doing old-fashioned supervised learning on a "problem solving step by step" dataset? I'm not sure why people are getting excited about the pure-RL approach, seems just overly complicated for no real gain.