DeepSeek launched a free, open-source large-language model in late December, claiming it was developed in just two months at a cost of under $6 million.
Okay seriously this technology still baffles me. Like its cool but why invest so much in an unknown like AIs future ? We could invest in people and education and end up with really smart people. For the cost of an education we could end up with smart people who contribute to the economy and society. Instead we are dumping billions into this shit.
They don't want to get rid of workers because then there would be no consumers. No, they want to increase the downward pressure on wages so they can vacuum up further savings.
For the cost of an education we could end up with smart people who contribute to the economy and society. Instead we are dumping billions into this shit.
Tech/Wall St constantly needs something to hype in order to bring in “investor” money. The “new technology-> product development -> product -> IPO” pipeline is now “straight to pump-and-dump” (for example, see Crypto currency).
The excitement of the previous hype train (self-driving cars) is no longer bringing in starry-eyed “investors” willing to quickly part ways with OPM. “AI” made a big splash and Tech/Wall St is going to milk it for all they can lest they fall into the same bad economy as that one company that didn’t jam the letters “AI” into their investor summary.
Tech has laid off a lot of employees, which means they are aware there is nothing else exciting in the near horizon. They also know they have to flog “AI” like crazy before people figure out there’s no “there” there.
That “investors” scattered like frightened birds at the mere mention of a cheaper version means that they also know this is a bubble. Everyone wants the quick money. More importantly they don’t want to be the suckers left holding the bag.
It's easier to sell people on the idea of a new technology or system that doesn't have any historical precedent. All you have to do is list the potential upsides.
Something like a school or a workplace training programme, those are known quantities. There's a whole bunch of historical and currently-existing projects anyone can look at to gauge the cost. Your pitch has to be somewhat realistic compared to those, or it's gonna sound really suspect.
Because the silicon valley bros had convinced the national security wonks in the Beltway that it was paramount for national security, technological leadership and economic prosperity.
I think this will go down as the biggest grift in history.
Kevin Walmsley reported on Deepseek 10 days ago. Last week, the smart money exited big tech. This week the panic starts.
I'm getting big dot-com 2.0 vibes from all of this.
I get the tech, and still agree with the preposter. I'd even go so far as that it probably worsens a lot currently, as it's generating a lot of bullshit that sounds great on the surface, but in reality is just regurgitated stuff that the AI has no clue of. For example I'm tired of reading AI generated text, when a hand written version would be much more precise and has some character at least...
Famously only one class benefits from productivity, while one generates the productivity. Can you explain what you mean, if you don’t mean capitalistic productivity?
Look at it in another way, people think this is the start of an actual AI revolution, as in full blown AGI or close to it or something very capable at least. Personally I don't think we're anywhere near something like that with the current technology, I think it's a dead end, but if there's even a small possibility of it being true, you want to invest early because the returns will be insane if it pans out. Full blown AGI would revolutionize everything, it would probably be the next industrial revolution after the internet.
Look at it in another way, people think this is the start of an actual AI revolution, as in full blown AGI or close to it or something very capable at least
I think the bigger threat of revolution (and counter-revolution) is that of open source software. For people that don't know anything about FOSS, they've been told for decades now that [XYZ] software is a tool you need and that's only possible through the innovative and superhuman-like intelligent CEOs helping us with the opportunity to buy it.
If everyone finds out that they're actually the ones stifling progress and development, while manipulating markets to further enrich themselves and whatever other partners that align with that goal, it might disrupt the golden goose model. Not to mention defrauding the countless investors that thought they were holding rocket ship money that was actually snake oil.
All while another country did that collectively and just said, "here, it's free. You can even take the code and use it how you personally see fit, because if this thing really is that thing, it should be a tool anyone can access. Oh, and all you other companies, your code is garbage btw. Ours runs on a potato by comparison."
I'm just saying, the US has already shown they will go to extreme lengths to keep its citizens from thinking too hard about how its economic model might actually be fucking them while the rich guys just move on to the next thing they'll sell us.
ETA: a smaller scale example: the development of Wine, and subsequently Proton finally gave PC gamers a choice to move away from Windows if they wanted to.
How would the investors profit from paying for someone's education? By giving them a loan? Don't we have enough problems with the student loan system without involving these assholes more?
I'm so happy this happened. This is really a power move from China. The US was really riding the whole AI bubble. By "just" releasing a powerful open-source AI model they've fucked the not so open US AI companies. I'm not sure if this was planned from China or whether this is was really just a small company doing this because they wanted to, but either way this really damages the western economy. And its given western consumers a free alternative. A few million dollars invested (if we are to believe the cost figures) for a major disruption.
Socialism/Communism will always outcompete the capitalists. And they know it, which is why the US invades, topples, or sanctions every country that moves towards worker controlled countries.
I disagree. Under the right conditions (read: actual competition instead of unregulated monopolies) I think a capitalist system be able to stay ahead, though I think both systems could compete depending on how they're organized.
But what I'm more interested in is you view that China is still Socialist/Communist. Isn't DeepSeek a private company trying to maximize profits for itself by innovating, instead of a public company funded by the people? I don't really know myself, but my perspective was that this was more of a capitalist vs capitalist situation. With one side (the US) kinda suffering from being so unregulated that innovation dies down.
Try asking DeepSeek something about Xi Jinping. "Sorry, it's beyond my current scope' :-) Wondering why even it cannot cite his official party biography :-)
You wouldn't, because you are (presumably) knowledgeable about the current AI trend and somewhat aware of political biases of the creators of these products.
Many others would, because they think "wow, so this is a computer that talks to me like a human, it knows everything and can respond super fast to any question!"
The issue to me is (and has been for the past), the framing of what "artifical intelligence" is and how humans are going to use it. I'd like more people to be critical of where they get their information from and what kind of biases it might have.
Except they control not only the narrative on politics but all aspects of life. Those inconvenient "hallucinations" will turn into "convenient" psyops for anyone using it.
I did. The answer it gave is clear and concise with no judgement. Instead it talks about the argument on both sides. Not the "magical Hasbara dance" you promised me.
Try asking Deepseek about Taiwan independence and watch how it completely ignores all (/think) and gives a false answer.
The question of whether Israel is currently committing genocide is a subject of intense debate among international organizations, scholars, and political entities.
Accusations of Genocide:
Amnesty International's Report: On December 5, 2024, Amnesty International released a report concluding that Israel is committing genocide against Palestinians in the Gaza Strip. The report cites actions such as killings, causing serious bodily or mental harm, and deliberately inflicting conditions calculated to bring about the physical destruction of Palestinians in Gaza.
UN Special Committee Findings: In November 2024, a UN Special Committee found that Israel's methods of warfare in Gaza are consistent with characteristics of genocide, noting mass civilian casualties and widespread destruction.
Scholarly Perspectives: Israeli historian Amos Goldberg has stated that the situation in Gaza constitutes a genocide, pointing to the extensive destruction and high civilian death toll as indicative of genocidal intent.
Counterarguments:
Israeli Government's Position: The Israeli government asserts that its military actions in Gaza are aimed at dismantling Hamas, a group designated as a terrorist organization by multiple countries, and emphasizes efforts to minimize civilian casualties.
Criticism of Genocide Accusations: Organizations such as the American Jewish Committee (AJC) reject the genocide label, arguing that Israel's actions are self-defense measures against Hamas and do not meet the legal definition of genocide.
Legal Definition of Genocide:
According to the UN's 1948 Convention on Genocide, genocide includes acts committed with intent to destroy, in whole or in part, a national, ethnical, racial, or religious group. These acts encompass killing members of the group, causing serious bodily or mental harm, and deliberately inflicting conditions calculated to bring about the group's physical destruction.
Conclusion:
The determination of whether Israel's actions constitute genocide involves complex legal and factual analyses. While some international bodies and scholars argue that the criteria for genocide are met, others contend that Israel's military operations are legitimate acts of self-defense. This remains a deeply contentious issue within the international community.
Yes and no. Not many people can afford the hardware required to run the biggest LLMs. So the majority of people will just use the psyops vanilla version that China wants you to use. All while collecting more data and influencing the public like what TikTok is doing.
Also another thing with Open source. It's just as easy to be closed as it is open with zero warnings. They own the license. They control the narrative.
The official hosting of it has censorship applied after the answer is generated, but from what I heard the locally run version has no censorship even though they could have theoretically trained it to.
It’s because Nvidia is an American company and also because they make final stage products. American companies right now are all overinflated and almost none of the stocks are worth what they’re at because of foreign trading influence.
As much as people whine about inflation here, the US didn’t get hit as bad as many other countries and we recovered quickly which means that there is a lot of incentive for other countries to invest here. They pick our top movers, they invest in those. What you’re seeing is people bandwagoning onto certain stocks because the consistent gains create more consistent gains for them.
The other part is that yes, companies who make products at the end stage tend to be worth a lot more than people trading more fundamental resources or parts. This is true of almost every industry except oil.
It is also because the USA is the reserve currency of the world with open capital markets.
Savers of the world (including countries like Germany and China who have excess savings due to constrained consumer demand) dump their savings into US assets such as stocks.
This leads to asset bubbles and an uncompetitively high US dollar.
The US is also a regulations haven compared to other developed economies, corporations get away with shit in most places but America is on a whole other level of regulatory capture.
China really has nothing to do with it, it could have been anyone. It's a reaction to realizing that GPT4-equivalent AI models are dramatically cheaper to train than previously thought.
It being China is a noteable detail because it really drives the nail in the coffin for NVIDIA, since China has been fenced off from having access to NVIDIA's most expensive AI GPUs that were thought to be required to pull this off.
It also makes the USA gov look extremely foolish to have made major foreign policy and relationship sacrifices in order to try to delay China by a few years, when it's January and China has already caught up, those sacrifices did not pay off, in fact they backfired and have benefited China and will allow them to accelerate while hurting USA tech/AI companies
I don't think this is the primary reason behind Nvidia's drop. Because as long as they got a massive technological lead it doesn't matter as much to them who has the best model, as long as these companies use their GPUs to train them.
The real change is that the compute resources (which is Nvidia's product) needed to create a great model suddenly fell of a cliff. Whereas until now the name of the game was that more is better and scale is everything.
China vs the West (or upstart vs big players) matters to those who are investing in creating those models. So for example Meta, who presumably spends a ton of money on high paying engineers and data centers, and somehow got upstaged by someone else with a fraction of their resources.
From what I understand, it's more that it takes a lot less money to train your own llms with the same powers with this one than to pay license to one of the expensive ones. Somebody correct me if I'm wrong
Exactly. Galaxy brains on Wall Street realizing that nvidia's monopoly pricing power is coming to an end. This was inevitable - China has 4x as many workers as the US, trained in the best labs and best universities in the world, interns at the best companies, then, because of racism, sent back to China. Blocking sales of nvidia chips to China drives them to develop their own hardware, rather than getting them hooked on Western hardware. China's AI may not be as efficient or as good as the West right now, but it will be cheaper, and it will get better.
It's coming, Pelosi sold her shares like a month ago.
It's going to crash, if not for the reasons she sold for, as more and more people hear she sold, they're going to sell because they'll assume she has insider knowledge due to her office.
Which is why politicians (and spouses) shouldn't be able to directly invest into individual companies.
Even if they aren't doing anything wrong, people will follow them and do what they do. Only a truly ignorant person would believe it doesn't have an effect on other people.
Prices rarely, if ever, go down and there is a push across the board to offload things "to the cloud" for a range of reasons.
That said: If your focus is on gaming, AMD is REAL good these days and, if you can get past their completely nonsensical naming scheme, you can often get a really good GPU using "last year's" technology for 500-800 USD (discounted to 400-600 or so).
Something is got to give. You can't spend ~$200 billion annually on capex and get a mere $2-3 billion return on this investment.
I understand that they are searching for a radical breakthrough "that will change everything", but there is also reasons to be skeptical about this (e.g. documents revealing that Microsoft and OpenAI defined AGI as something that can get them $100 billion in annual revenue as opposed to some specific capabilities).
I should really start looking into shorting stocks. I was looking at the news and Nvidia's stock and thought "huh, the stock hasn't reacted to these news at all yet, I should probably short this".
And then proceeded to do fuck all.
I guess this is why some people are rich and others are like me.
It's been proven that people who do fuckall after throwing their money into mutual funds generally fare better than people actively monitoring and making stock moves.
You're probably fine.
I never bought NVIDIA in the first place so this news doesn't affect me.
If anything now would be a good time to buy NVIDIA. But I probably won't.
Shovel vendors scrambling for solid ground as prospectors start to understand geology.
...that is, this isn't yet the end of the AI bubble. It's just the end of overvaluing hardware because efficiency increased on the software side, there's still a whole software-side bubble to contend with.
there's still a whole software-side bubble to contend with
They're ultimately linked together in some ways (not all). OpenAI has already been losing money on every GPT subscription that they charge a premium for because they had the best product, now that premium must evaporate because there are equivalent AI products on the market that are much cheaper. This will shake things up on the software side too. They probably need more hype to stay afloat
The software side bubble should take a hit here because:
Trained model made available for download and offline execution, versus locking it behind a subscription friendly cloud only access. Not the first, but it is more famous.
It came from an unexpected organization, which throws a wrench in the assumption that one of the few known entities would "win it".
…that is, this isn’t yet the end of the AI bubble.
The "bubble" in AI is predicated on proprietary software that's been oversold and underdelivered.
If I can outrun OpenAI's super secret algorithm with 1/100th the physical resources, the $13B Microsoft handed Sam Altman's company starts looking like burned capital.
And the way this blows up the reputation of AI hype-artists makes it harder for investors to be induced to send US firms money. Why not contract with Hangzhou DeepSeek Artificial Intelligence directly, rather than ask OpenAI to adopt a model that's better than anything they've produced to date?
Lots of techies loved the internet, built it, and were all early adopters. Lots of normies didn't see the point.
With AI it's pretty much the other way around: CEOs saying "we don't need programmers, any more", while people who understand the tech roll their eyes.
I don't know. In a lot of usecase AI is kinda crap, but there's certain usecase where it's really good. Honestly I don't think people are giving enough thought to it's utility in early-middle stages of creative works where an img2img model can take the basic composition from the artist, render it then the artist can go in and modify and perfect it for the final product. Also video games that use generative AI are going to be insane in about 10-15 years. Imagine an open world game where it generates building interiors and NPCs as you interact with them, even tying the stuff the NPCs say into the buildings they're in, like an old sailer living in a house with lots of pictures of boats and boat models, or the warrior having tons of books about battle and decorative weapons everywhere all in throw away structures that would have previously been closed set dressing. Maybe they'll even find sane ways to create quests on the fly that don't feel overly cookie-cutter? Life changing? Of course not, but definitely a cool technology with a lot of potential
Also realistically I don't think there's going to be long term use for AI models that need a quarter of a datacenter just to run, and they'll all get tuned down to what can run directly on a phone efficiently. Maybe we'll see some new accelerators become common place maybe we won't.
I think this prompted investors to ask "where's the ROI?".
Current AI investment hype isn't based on anything tangible. At least the amount of investment isn't, it is absurd to think that trillion dollars that was put in the space already, even before that Softbanks deal is going to be returned. The models still hallucinate as it is inherent to the architecture, we are nowhere near replacing the workers but we got chatbots that "when they work sometimes, then they are kind of good?" and mediocre off-putting pictures. Is there any value? Sure, it's not NFTs. But the correction might be brutal.
Interestingly enough, DeepSeek's model is released just before Q4 earning's call season, so we will see if it has a compounding effect with another statement from big players that they burned massive amount of compute and USD only to get milquetoast improvements and get owned by a small Chinese startup that allegedly can do all that for 5 mil.
EDIT: The crypto bros out in full force... and right on cue proudly proclaiming they don't understand the difference between the value of blockchain technology (which so far has not had a ton of real world value outside of mostly impractical database applications, other than furthering climate change and buying drugs) vs the SPECULATIVE value of coins since coins have no real value factors to back up their SPECULATIVE value. Stocks often have real value that back up their value, like company profits or products. Stop drinking kool aid to the point of literal zero critical thinking, jfc.
I think that the technology itself has been widely adopted and used. There are many examples in medicine, military, entertainment. But OpenAI and other hyperscalers are a bad business that burns through a loooot of cash. Same with Meta AI program. And while this has been a norm with tech darlings that they usually don't break even for a long time, what's unprecedented is the rate of loss and further calls for even more money even though there isn't any clear path from what we have to AGI. All hangs on Altman and other biz-dev vague promises, threats and a "vibe" that they create.
I disagree - before Bitcoin there was no venmo, cashapp, etc. It took weeks to move big money around. I'm not saying shit like NFT's ever made sense, and meme coins are fucking stupid - unfortunately the crypto world has been taken over by scammers - but don't shit on the technology
I'm not saying that it doesn't have any uses but the costs outpace the investments done by a mile. Current LLM and vLLMs help with efficiency to a degree but this is not sustainable and the correction is overdue.
I have a dirty suspicion that the "where's the ROI?" talking point is actually a calculated and collaborated strategy by big wall street banks to panic retail investors to sell so they can gobble up shares at a discount - trump is going to be pumping (at minimum) hundreds of BILLIONS into these companies in the near future.
Call me a conspiracy guy, but I've seen this playbook many many times
I mean, I'm working on that tech and the evaluation boggles my mind. This is nowhere near worth what is put into it. It rides on empty promises that may or may not materialize (I can't say with 100% certainty that a breakthrough happen), but current models are massively overvalued. I've seen that happen with ConvNets (Hinton saying we won't need radiologists in five years in....2016, self-driving cars promised every two years, yadda yadda) but nothing to that scale.
Was watching bbc news interview some American guy about this and wow they were really pushing that it's no big deal and deepseek is way behind and a bit of a joke. Made claims they weren't under cyber attack they just couldn't handle having traffic etc.
My understanding is that DeepSeek still used Nvidia just older models and way more efficiently, which was remarkable. I hope to tinker with the opensource stuff at least with a little Twitch chat bot for my streams I was already planning to do with OpenAI. Will be even more remarkable if I can run this locally.
However this is embarassing to the western companies working on AI and especially with the $500B announcement of Stargate as it proves we don't need as high end of an infrastructure to achieve the same results.
My understanding is that DeepSeek still used Nvidia just older models
That's the funniest part here, the sell off makes no sense. So what if some companies are better at utilizing AI than others, it all runs in the same hardware. Why sell stock in the hardware company? (Besides the separate issue of it being totally overvalued at the moment)
This would be kind of like if a study showed that American pilots were more skilled than European pilots, so investors sold stock in airbus... Either way, the pilots still need planes to fly...
Yes, but if they already have lots of planes, they don't need to keep buying more planes. Especially if their current planes can now run for longer.
AI is not going away but it will require less computing power and less capital investment. Not entirely unexpected as a trend, but this was a rapid jump that will catch some off guard. So capital will be reallocated.
Thank the fucking sky fairies actually, because even if AI continues to mostly suck it'd be nice if it didn't swallow up every potable lake in the process. When this shit is efficient that makes it only mildly annoying instead of a complete shitstorm of failure.
While this is great, the training is where the compute is spent. The news is also about R1 being able to be trained, still on an Nvidia cluster but for 6M USD instead of 500
Sure you can run it on low end hardware, but how does the performance (response time for a given prompt) compare to the other models, either local or as a service?
The way I understood it, it's much more efficient so it should require less hardware.
Nvidia will sell that hardware, an obscene amount of it, and line will go up. But it will go up slower than nvidia expected because anything other than infinite and always accelerating growth means you're not good at business.
It requires only 5% of the same hardware that OpenAI needs to do the same thing. So that can mean less quantity of top end cards and it can also run on less powerful cards (not top of the line).
Should their models become standard or used more commonly, then nvidis sales will drop.
Doesn’t this just mean that now we can make models 20x more complex using the same hardware? There’s many more problems that advanced Deep Learning models could potentially solve that are far more interesting and useful than a chat bot.
I don’t see how this ends up bad for Nvidia in the long run.
And you should, generally we are amidst the internet world war. It's not something fishy but digital rotten eggs thrown around by the hundreds.
The only way to remain sane is to ignore it and scroll on. There is no winning versus geopolitical behemoths as a lone internet adventurer. It's impossible to tell what's real and what isn't the first casualty of war is truth
Hm even with DeepSeek being more efficient, wouldn’t that just mean the rich corps throw the same amount of hardware at it to achieve a better result?
Only up to the point where the AI models yield value (which is already heavily speculative). If nothing else, DeepSeek makes Altman's plan for $1T in new data-centers look like overkill.
The revelation that you can get 100x gains by optimizing your code rather than throwing endless compute at your model means the value of graphics cards goes down relative to the value of PhD-tier developers. Why burn through a hundred warehouses full of cards to do what a university mathematics department can deliver in half the time?
It will probably not reduce demand. But it will for sure make it impossible to sell insanely overpriced hardware. Now I'm looking forward to buying a PC with a Chinese open source RISCV CPU and GPU. Bye bye Intel, AMD, ARM and Nvidia.
DeepSeek proved you didn't need anywhere near as much hardware to train or run an even better AI model
Imagine what would happen to oil prices if a manufacturer comes out with a full ice car that can run 1000 miles per gallon... Instead of the standard American 3 miles per 1.5 gallons hehehe
Bizarre story. China building better LLMs and LLMs being cheaper to train does not mean that nVidia will sell less GPUs when people like Elon Musk and Donald Trump can't shut up about how important "AI" is.
I'm all for the collapse of the AI bubble, though. It's cool and all that all the bankers know IT terms now, but the massive influx of money towards LLMs and the datacenters that run them has not been healthy to the industry or the broader economy.
It literally defeats NVIDIA's entire business model of "I shit golden eggs and I'm the only one that does and I can charge any price I want for them because you need my golden eggs"
Turns out no one actually even needs a golden egg anyway.
And... same goes for OpenAI, who were already losing money on every subscription. Now they've lost the ability to charge a premium for their service (anyone can train a GPT4 equivalent model cheaply, or use DeepSeek's existing open models) and subscription prices will need to come down, so they'll be losing money even faster
Nvidia cards were the only GPUs used to train DeepSeek v3 and R1. So, that narrative still superficially holds. Other stocks like TSMC, ASML, and AMD are also down in pre-market.
US economy has been running on bubbles for decades, and using bubbles to fuel innovation and growth. It has survived telecom bubble, housing bubble, bubble in the oil sector for multiple times (how do you think fracking came to be?) etc. This is just the start of the AI bubble because its innovations have yet to have a broad-based impact on the economy. Once AI becomes commonplace in aiding in everything we do, that's when valuations will look "normal".
Well, you still need the right kind of hardware to run it, and my money has been on AMD to deliver the solutions for that. Nvidia has gone full-blown stupid on the shit they are selling, and AMD is all about cost and power efficiency, plus they saw the writing on the wall for Nvidia a long time ago and started down the path for FPGA, which I think will ultimately be the same choice for running this stuff.
Twenty or so years ago, there was a brief period when going full AMD (or AMD+ATI as it was back then; AMD hadn't bought ATI yet) made sense, and then the better part of a decade later, Intel+NVIDIA was the better choice.
And now I have a full AMD PC again.
Intel are really going to have to turn things around in my eyes if they want it to swing back, though. I really do not like the idea of a CPU hypervisor being a fully fledged OS that I have no access to.
From a "compute" perspective (so not consumer graphics), power... doesn't really matter. There have been decades of research on the topic and it almost always boils down to "Run it at full bore for a shorter period of time" being better (outside of the kinds of corner cases that make for "top tier" thesis work).
AMD (and Intel) are very popular for their cost to performance ratios. Jensen is the big dog and he prices accordingly. But... while there is a lot of money in adapting models and middleware to AMD, the problem is still that not ALL models and middleware are ported. So it becomes a question of whether it is worth buying AMD when you'll still want/need nVidia for the latest and greatest. Which tends to be why those orgs tend to be closer to an Azure or AWS where they are selling tiered hardware.
Which... is the same issue for FPGAs. There is a reason that EVERYBODY did their best to vilify and kill opencl and it is not just because most code was thousands of lines of boilerplate and tens of lines of kernels. Which gets back to "Well. I can run this older model cheap but I still want nvidia for the new stuff...."
Which is why I think nvidia's stock dropping is likely more about traders gaming the system than anything else. Because the work to use older models more efficiently and cheaply has already been a thing. And for the new stuff? You still want all the chooch.
Your assessment is missing the simple fact that FPGA can do things a GPU cannot faster, and more cost efficiently though. Nvidia is the Ford F-150 of the data center world, sure. It's stupidly huge, ridiculously expensive, and generally not needed unless it's being used at full utilization all the time. That's like the only time it makes sense.
If you want to run your own models that have a specific purpose, say, for scientific work folding proteins, and you might have several custom extensible layers that do different things, N idia hardware and software doesn't even support this because of the nature of Tensorrt. They JUST announced future support for such things, and it will take quite some time and some vendor lock-in for models to appropriately support it.....OR
Just use FPGAs to do the same work faster now for most of those things. The GenAI bullshit bandwagon finally has a wheel off, and it's obvious people don't care about the OpenAI approach to having one model doing everything. Compute work on this is already transitioning to single purpose workloads, which AMD saw coming and is prepared for. Nvidia is still out there selling these F-150s to idiots who just want to piss away money.
GPU is good for graphics. That's what is designed and built for. It just so happens to be good at dealing with programmatic neural network tasks because of parallelism.
FPGA is fully programmable to do whatever you want, and reprogram on the fly. Pretty perfect for reducing costs if you have a platform that does things like audio processing, then video processing, or deep learning, especially in cloud environments. Instead of spinning up a bunch of expensive single-phroose instances, you can just spin up one FPGA type, and reprogram on the fly to best perform on the work at hand when the code starts up. Simple.
AMD bought Xilinx in 2019 when they were still a fledgling company because they realized the benefit of this. They are now selling mass amounts of these chips to data centers everywhere. It's also what the XDNA coprocessors on all the newer Ryzen chips are built on, so home users have access to an FPGA chip right there. It's efficient, cheaper to make than a GPU, and can perform better on lots of non-graphic tasks than GPUs without all the massive power and cooling needs. Nvidia has nothing on the roadmap to even compete, and they're about to find out what a stupid mistake that is.
So, I get that the hardware is needed for training the models and that's why the stock price fell. But it's also required to run the models, and this news is only going to increase the supply of AI services. It seems to me that this isn't a big threat to the companies that sell AI hardware.
The thing is that they can no longer sell insanely overpriced hardware. The VC fucktards and coin bros begin to understand they're being scamed. And that murdering competition from China is around the corner. All this is very good news for consumers.
It's fun seeing these companies take a hit and the bubble deflate, but long term won't this just make AI a more alluring form of enshittification to a wider audience?
With the amount governments seem to be on the AI train I'm becoming more and more worried about the fall out when the hype bubble does burst. I'm really hoping it comes sooner rather than later.
One of the most remarkable aspects of this self-evolution is the emergence of sophisticated behaviors as the test-time computation increases. Behaviors such as reflection—where the model revisits and reevaluates its previous steps—and the exploration of alternative approaches to
problem-solving arise spontaneously. These behaviors are not explicitly programmed but instead emerge as a result of the model’s interaction with the reinforcement learning environment. This spontaneous development significantly enhances DeepSeek-R1-Zero’s reasoning capabilities, enabling it to tackle more challenging tasks with greater efficiency and accuracy.
Aha Moment of DeepSeek-R1-Zero
A particularly intriguing phenomenon observed during the training of DeepSeek-R1-Zero is the occurrence of an “aha moment”. This moment, as illustrated in Table 3, occurs in an intermediate version of the model. During this phase, DeepSeek-R1-Zero learns to allocate more thinking time to a problem by reevaluating its initial approach. This behavior is not only a testament to the model’s growing reasoning abilities but also a captivating example of how reinforcement learning can lead to unexpected and
sophisticated outcomes.
This moment is not only an “aha moment” for the model but also for the researchers
observing its behavior. It underscores the power and beauty of reinforcement learning: rather than explicitly teaching the model on how to solve a problem, we simply provide it with the right incentives, and it autonomously develops advanced problem-solving strategies. The “aha moment” serves as a powerful reminder of the potential of RL to unlock new levels of intelligence in artificial systems, paving the way for more autonomous and adaptive models in
the future.