Looks like it is not any smarter than the other junk on the market. The confusion that people consider AI as “intelligence” may be rooted in their own deficits in that area.
And now people exchange one American Junk-spitting Spyware for a Chinese junk-spitting spyware. Hurray! Progress!
It is progress in a sense. The west really put the spotlight on their shiny new expensive toy and banned the export of toy-maker parts to rival countries.
One of those countries made a cheap toy out of jank unwanted parts for much less money and it’s of equal or better par than the west’s.
As for why we’re having an arms race based on AI, I genuinely dont know. It feels like a race to the bottom, with the fallout being the death of the internet (for better or worse)
The difference is that you can actually download this model and run it on your own hardware (if you have sufficient hardware). In that case it won’t be sending any data to China. These models are still useful tools. As long as you’re not interested in particular parts of Chinese history of course ;p
AI has been used in game development for a while and i havent seen anyone complain about the name before it became synonymous with image/text generation
It was a misnomer there too, but at least people didn’t think a bot playing C&C would be able to save the world by evolving into a real, greater than human intelligence.
And now people exchange one American Junk-spitting Spyware for a Chinese junk-spitting spyware.
LLMs aren’t spyware, they’re graphs that organize large bodies of data for quick and user-friendly retrieval. The Wikipedia schema accomplishes a similar, abet more primitive, role. There’s nothing wrong with the fundamentals of the technology, just the applications that Westoids doggedly insist it be used for.
If you no longer need to boil down half a Great Lake to create the next iteration of Shrimp Jesus, that’s good whether or not you think Meta should be dedicating millions of hours of compute to this mind-eroding activity.
I think maybe it’s naive to think that if the cost goes down, shrimp jesus won’t just be in higher demand. Shrimp jesus has no market cap, bullshit has no market cap. If you make it more efficient to flood cyberspace with bullshit, cyberspace will just be flooded with more bullshit. Those great lakes will still boil, don’t worry.
I think maybe it’s naive to think that if the cost goes down, shrimp jesus won’t just be in higher demand.
Not that demand will go down but that economic cost of generating this nonsense will go down. The number of people shipping this back and forth to each other isn’t going to meaningfully change, because Facebook has saturated the social media market.
If you make it more efficient to flood cyberspace with bullshit, cyberspace will just be flooded with more bullshit.
The efficiency is in the real cost of running the model, not in how it is applied. The real bottleneck for AI right now is human adoption. Guys like Altman keep insisting a new iteration (that requires a few hundred miles of nuclear power plants to power) will finally get us a model that people want to use. And speculators in the financial sector seemed willing to cut him a check to go through with it.
Knocking down the real physical cost of this boondoggle is going to de-monopolize this awful idea, which means Altman won’t have a trillion dollar line of credit to fuck around with exclusively. We’ll still do it, but Wall Street won’t have Sam leading them around by the nose when they can get the same thing for 1/100th of the price.
LLMs are not a magical box you can ask anything of and get answers. If you are lucky and blindly asking questions it can give some accurate general data, but just like how human brains work you aren’t going to be able to accurately recreate random trivia verbatim from a neural net.
What LLMs are useful for, and how they should be used, is a non-deterministic parsing context tool. When people talk about feeding it more data they think of how these things are trained. But you also need to give it grounding context outside of what the prompt is. give it a PDF manual, website link, documentation, whatever and it will use that as context for what you ask it. You can even set it to link to reference.
You still have to know enough to be able to validate the information it is giving you, but that’s the case with any tool. You need to know how to use it.
As for the spyware part, that only matters if you are using the hosted instances they provide. Even for OpenAI stuff you can run the models locally with opensource software and maintain control over all the data you feed it. As far as I have found, none of the models you run with Ollama or other local AI software have been caught pushing data to a remote server, at least using open source software.
Looks like it is not any smarter than the other junk on the market. The confusion that people consider AI as “intelligence” may be rooted in their own deficits in that area.
Yep, because they believed that OpenAI’s (two lies in a name) models would magically digivolve into something that goes well beyond what it was designed to be. Trust us, you just have to feed it more data!
And now people exchange one American Junk-spitting Spyware for a Chinese junk-spitting spyware. Hurray! Progress!
That’s the neat bit, really. With that model being free to download and run locally it’s actually potentially disruptive to OpenAI’s business model. They don’t need to do anything malicious to hurt the US’ economy.
This just shows how speculative the whole AI obsession has been. Wildly unstable and subject to huge shifts since its value isn’t based on anything solid.
It’s based on guessing what the actual worth of AI is going to be, so yeah, wildly speculative at this point because breakthroughs seem to be happening fairly quickly, and everyone is still figuring out what they can use it for.
There are many clear use cases that are solid, so AI is here to stay, that’s for certain. But how far can it go, and what will it require is what the market is gambling on.
If out of the blue comes a new model that delivers similar results on a fraction of the hardware, then it’s going to chop it down by a lot.
If someone finds another use case, for example a model with new capabilities, boom value goes up.
There are many clear use cases that are solid, so AI is here to stay, that’s for certain. But how far can it go, and what will it require is what the market is gambling on.
I would disagree on that. There are a few niche uses, but OpenAI can’t even make a profit charging $200/month.
The uses seem pretty minimal as far as I’ve seen. Sure, AI has a lot of applications in terms of data processing, but the big generic LLMs propping up companies like OpenAI? Those seems to have no utility beyond slop generation.
Ultimately the market value of any work produced by a generic LLM is going to be zero.
It’s difficult to take your comment serious when it’s clear that all you’re saying seems to based on ideological reasons rather than real ones.
Besides that, a lot of the value is derived from the market trying to figure out if/what company will develop AGI. Whatever company manages to achieve it will easily become the most valuable company in the world, so people fomo into any AI company that seems promising.
Besides that, a lot of the value is derived from the market trying to figure out if/what company will develop AGI. Whatever company manages to achieve it will easily become the most valuable company in the world, so people fomo into any AI company that seems promising.
There is zero reason to think the current slop generating technoparrots will ever lead into AGI. That premise is entirely made up to fuel the current
“AI” bubble
sure, but that can be said of literally anything. It would be interesting if LLM were at least new but they have been around forever, we just now have better hardware to run them
That’s not even true. LLMs in their modern iteration are significantly enabled by transformers, something that was only proposed in 2017.
The conceptual foundations of LLMs stretch back to the 50s, but neither the physical hardware nor the software architecture were there until more recently.
Language learning, code generatiom, brainstorming, summarizing. AI has a lot of uses. You’re just either not paying attention or are biased against it.
It’s not perfect, but it’s also a very new technology that’s constantly improving.
I decided to close the post now - there is place for any opinion, but I can see people writing things which are completely false however you look at them: you can dislike Sam Altman (I do), you can worry about China’s interest in entering the competition now and like that (I do), but the comments about LLM being useless while millions of people use it daily for multiple purposes sound just like lobbying.
One of those rare lucid moments by the stock market? Is this the market correction that everyone knew was coming, or is some famous techbro going to technobabble some more about AI overlords and they return to their fantasy values?
It’s quite lucid. The new thing uses a fraction of compute compared to the old thing for the same results, so Nvidia cards for example are going to be in way less demand. That being said Nvidia stock was way too high surfing on the AI hype for the last like 2 years, and despite it plunging it’s not even back to normal.
I feel like the world’s gone crazy, but OpenAI (and others) is pursing more complex model designs with multimodal. Those are going to be more expensive due to image/video/audio processing. Unless I’m missing something that would probably account for the cost difference in current vs previous iterations.
The thing is that R1 is being compared to gpt4 or in some cases gpt4o. That model cost OpenAI something like $80M to train, so saying it has roughly equivalent performance for an order of magnitude less cost is not for nothing. DeepSeek also says the model is much cheaper to run for inferencing as well, though I can’t find any figures on that.
The original gpt4 is just an LLM though, not multimodal, and the training cost for that is still estimated to be over 10x R1’s if you believe the numbers. I think where R 1 is compared to 4o is in so-called reasoning, where you can see the chain of though or internal prompt paths that the model uses to (expensively) produce an output.
I’m not sure how good a source it is, but Wikipedia says it was multimodal and came out about two years ago - https://en.m.wikipedia.org/wiki/GPT-4. That being said.
The comparisons though are comparing the LLM benchmarks against gpt4o, so maybe a valid arguement for the LLM capabilites.
Yea except DeepSeek released a combined Multimodal/generation model that has similar performance to contemporaries and a similar level of reduced training cost ~20 hours ago:
Holy smoke balls. I wonder what else they have ready to release over the next few weeks. They might have a whole suite of things just waiting to strategically deploy
Your confidence in this statement is hilarious the fact that it doesn’t help your argument at all. If anything, the fact they refined their model so well on older hardware is even more remarkable, and quite damning when OpenAI claims it needs literally cities worth of power and resources to train their models.
AI is overblown, tech is overblown. Capitalism itself is a senseless death cult based on the non-sensical idea that infinite growth is possible with a fragile, finite system.
Emergence of DeepSeek raises doubts about sustainability of western artificial intelligence boom
Is the “emergence of DeepSeek” really what raised doubts? Are we really sure there haven’t been lots of doubts raised previous to this? Doubts raised by intelligent people who know what they’re talking about?
Ah, but those “intelligent” people cannot be very intelligent if they are not billionaires. After all, the AI companies know exactly how to assess intelligence:
Microsoft and OpenAI have a very specific, internal definition of artificial general intelligence (AGI) based on the startup’s profits, according to a new report from The Information. …
The two companies reportedly signed an agreement last year stating OpenAI has only achieved AGI when it develops AI systems that can generate at least $100 billion in profits. That’s far from the rigorous technical and philosophical definition of AGI many expect.
(Source)
And without the fake frame bullshit they’re using to pad their numbers, its capabilities scale linearly with the 4090. The 5090 just has more cores, Ram, and power.
If the 4000-series had had cards with the memory and core count of the 5090, they’d be just as good as the 50-series.
By that point you will have to buy the Mico fission reactor addon to power the 6090. It’s like Nvidia looked at the power triangle of power / price and preformence and instead of picking two they just picked one and to hell with the rest.
Trump counterbalance keeping it in check but my gut is saying once tariffs come in February there’s going to be a market correction. Pure speculation on my part.
You don’t have to say speculation when talking about the future of stocks. It’s implied unless you are a time traveler in which case you should lead with that.
I’d argue this is even worse than Sputnik for the US because Sputnik spurred technological development that boosted the economy. Meanwhile, this is popping the economic bubble in the US built around the AI subscription model.
Nvidia’s most advanced chips, H100s, have been banned from export to China since September 2022 by US sanctions. Nvidia then developed the less powerful H800 chips for the Chinese market, although they were also banned from export to China last October.
I love how in the US they talk about meritocracy, competition being good, blablabla… but they rig the game from the beginning. And even so, people find a way to be better. Fascinating.
I don’t have one to cancel, but I might celebrate today by formatting the old windows SSD in my system and using it for some fast download cache space or something.
Democrats and Republicans have been shoveling truckload after truckload of cash into a Potemkin Village of a technology stack for the last five years. A Chinese tech company just came in with a dirt cheap open-sourced alternative and I guarantee you the American firms will pile on to crib off the work.
Far from fucking them over, China just did the Americans’ homework for them. They just did it in a way that undercuts all the “Sam Altman is the Tech Messiah! He will bring about AI God!” holy roller nonsense that was propping up a handful of mega-firm inflated stock valuations.
Small and Mid-cap tech firms will flourish with these innovations. Microsoft will have to write the last $13B it sunk into OpenAI as a lose.
It’s kinda funny. Their magical bullshitting machine scored higher on made up tests than our magical bullshitting machine, the economy is in shambles! It’s like someone losing a year’s wages in sports betting.
Just because people are misusing tech they know nothing about does not mean this isn’t an impressive feat.
If you know what you are doing, and enough to know when it gives you garbage, LLMs are really useful, but part of using them correctly is giving them grounding context outside of just blindly asking questions.
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Looks like it is not any smarter than the other junk on the market. The confusion that people consider AI as “intelligence” may be rooted in their own deficits in that area.
And now people exchange one American Junk-spitting Spyware for a Chinese junk-spitting spyware. Hurray! Progress!
It is open source, so it should be audited and if there are back doors they can be plugged in a fork
With understanding LLM, I started to understand some people and their “reasoning” better. That’s how they work.
That’s a silver lining, at least.
It is progress in a sense. The west really put the spotlight on their shiny new expensive toy and banned the export of toy-maker parts to rival countries.
One of those countries made a cheap toy out of jank unwanted parts for much less money and it’s of equal or better par than the west’s.
As for why we’re having an arms race based on AI, I genuinely dont know. It feels like a race to the bottom, with the fallout being the death of the internet (for better or worse)
The difference is that you can actually download this model and run it on your own hardware (if you have sufficient hardware). In that case it won’t be sending any data to China. These models are still useful tools. As long as you’re not interested in particular parts of Chinese history of course ;p
artificial intelligence
AI has been used in game development for a while and i havent seen anyone complain about the name before it became synonymous with image/text generation
Well, that is where the problems started.
It was a misnomer there too, but at least people didn’t think a bot playing C&C would be able to save the world by evolving into a real, greater than human intelligence.
LLMs aren’t spyware, they’re graphs that organize large bodies of data for quick and user-friendly retrieval. The Wikipedia schema accomplishes a similar, abet more primitive, role. There’s nothing wrong with the fundamentals of the technology, just the applications that Westoids doggedly insist it be used for.
If you no longer need to boil down half a Great Lake to create the next iteration of Shrimp Jesus, that’s good whether or not you think Meta should be dedicating millions of hours of compute to this mind-eroding activity.
Westoids? Are you the type of guy I feel like I need to take a shower after talking to?
I think maybe it’s naive to think that if the cost goes down, shrimp jesus won’t just be in higher demand. Shrimp jesus has no market cap, bullshit has no market cap. If you make it more efficient to flood cyberspace with bullshit, cyberspace will just be flooded with more bullshit. Those great lakes will still boil, don’t worry.
Not that demand will go down but that economic cost of generating this nonsense will go down. The number of people shipping this back and forth to each other isn’t going to meaningfully change, because Facebook has saturated the social media market.
The efficiency is in the real cost of running the model, not in how it is applied. The real bottleneck for AI right now is human adoption. Guys like Altman keep insisting a new iteration (that requires a few hundred miles of nuclear power plants to power) will finally get us a model that people want to use. And speculators in the financial sector seemed willing to cut him a check to go through with it.
Knocking down the real physical cost of this boondoggle is going to de-monopolize this awful idea, which means Altman won’t have a trillion dollar line of credit to fuck around with exclusively. We’ll still do it, but Wall Street won’t have Sam leading them around by the nose when they can get the same thing for 1/100th of the price.
I’m tired of this uninformed take.
LLMs are not a magical box you can ask anything of and get answers. If you are lucky and blindly asking questions it can give some accurate general data, but just like how human brains work you aren’t going to be able to accurately recreate random trivia verbatim from a neural net.
What LLMs are useful for, and how they should be used, is a non-deterministic parsing context tool. When people talk about feeding it more data they think of how these things are trained. But you also need to give it grounding context outside of what the prompt is. give it a PDF manual, website link, documentation, whatever and it will use that as context for what you ask it. You can even set it to link to reference.
You still have to know enough to be able to validate the information it is giving you, but that’s the case with any tool. You need to know how to use it.
As for the spyware part, that only matters if you are using the hosted instances they provide. Even for OpenAI stuff you can run the models locally with opensource software and maintain control over all the data you feed it. As far as I have found, none of the models you run with Ollama or other local AI software have been caught pushing data to a remote server, at least using open source software.
Yep, because they believed that OpenAI’s (two lies in a name) models would magically digivolve into something that goes well beyond what it was designed to be. Trust us, you just have to feed it more data!
That’s the neat bit, really. With that model being free to download and run locally it’s actually potentially disruptive to OpenAI’s business model. They don’t need to do anything malicious to hurt the US’ economy.
This just shows how speculative the whole AI obsession has been. Wildly unstable and subject to huge shifts since its value isn’t based on anything solid.
It’s based on guessing what the actual worth of AI is going to be, so yeah, wildly speculative at this point because breakthroughs seem to be happening fairly quickly, and everyone is still figuring out what they can use it for.
There are many clear use cases that are solid, so AI is here to stay, that’s for certain. But how far can it go, and what will it require is what the market is gambling on.
If out of the blue comes a new model that delivers similar results on a fraction of the hardware, then it’s going to chop it down by a lot.
If someone finds another use case, for example a model with new capabilities, boom value goes up.
It’s a rollercoaster…
I would disagree on that. There are a few niche uses, but OpenAI can’t even make a profit charging $200/month.
The uses seem pretty minimal as far as I’ve seen. Sure, AI has a lot of applications in terms of data processing, but the big generic LLMs propping up companies like OpenAI? Those seems to have no utility beyond slop generation.
Ultimately the market value of any work produced by a generic LLM is going to be zero.
It’s difficult to take your comment serious when it’s clear that all you’re saying seems to based on ideological reasons rather than real ones.
Besides that, a lot of the value is derived from the market trying to figure out if/what company will develop AGI. Whatever company manages to achieve it will easily become the most valuable company in the world, so people fomo into any AI company that seems promising.
There is zero reason to think the current slop generating technoparrots will ever lead into AGI. That premise is entirely made up to fuel the current “AI” bubble
They may well lead to the thing that leads to the thing that leads to the thing that leads to AGI though. Where there’s a will
sure, but that can be said of literally anything. It would be interesting if LLM were at least new but they have been around forever, we just now have better hardware to run them
That’s not even true. LLMs in their modern iteration are significantly enabled by transformers, something that was only proposed in 2017.
The conceptual foundations of LLMs stretch back to the 50s, but neither the physical hardware nor the software architecture were there until more recently.
The market don’t care what either of us think, investors will do what investors do, speculate.
Language learning, code generatiom, brainstorming, summarizing. AI has a lot of uses. You’re just either not paying attention or are biased against it.
It’s not perfect, but it’s also a very new technology that’s constantly improving.
I decided to close the post now - there is place for any opinion, but I can see people writing things which are completely false however you look at them: you can dislike Sam Altman (I do), you can worry about China’s interest in entering the competition now and like that (I do), but the comments about LLM being useless while millions of people use it daily for multiple purposes sound just like lobbying.
The “1 trillion” never existed in the first place. It was all hype by a bunch of Tech-Bros, huffing each other’s farts.
One of those rare lucid moments by the stock market? Is this the market correction that everyone knew was coming, or is some famous techbro going to technobabble some more about AI overlords and they return to their fantasy values?
It’s quite lucid. The new thing uses a fraction of compute compared to the old thing for the same results, so Nvidia cards for example are going to be in way less demand. That being said Nvidia stock was way too high surfing on the AI hype for the last like 2 years, and despite it plunging it’s not even back to normal.
How is the “fraction of compute” being verified? Is the model available for independent analysis?
Its freely availible with a permissive license, but I dont think that that claim has been verified yet.
And the data is not available. Knowing the weights of a model doesn’t really tell us much about its training costs.
My understanding is it’s just an LLM (not multimodal) and the train time/cost looks the same for most of these.
I feel like the world’s gone crazy, but OpenAI (and others) is pursing more complex model designs with multimodal. Those are going to be more expensive due to image/video/audio processing. Unless I’m missing something that would probably account for the cost difference in current vs previous iterations.
One of the things you’re missing is the same techniques are applicable to multimodality. They’ve already released a multimodal model: https://seekingalpha.com/news/4398945-deepseek-releases-open-source-ai-multimodal-model-janus-pro-7b
The thing is that R1 is being compared to gpt4 or in some cases gpt4o. That model cost OpenAI something like $80M to train, so saying it has roughly equivalent performance for an order of magnitude less cost is not for nothing. DeepSeek also says the model is much cheaper to run for inferencing as well, though I can’t find any figures on that.
My main point is that gpt4o and other models it’s being compared to are multimodal, R1 is only a LLM from what I can find.
Something trained on audio/pictures/videos/text is probably going to cost more than just text.
But maybe I’m missing something.
The original gpt4 is just an LLM though, not multimodal, and the training cost for that is still estimated to be over 10x R1’s if you believe the numbers. I think where R 1 is compared to 4o is in so-called reasoning, where you can see the chain of though or internal prompt paths that the model uses to (expensively) produce an output.
I’m not sure how good a source it is, but Wikipedia says it was multimodal and came out about two years ago - https://en.m.wikipedia.org/wiki/GPT-4. That being said.
The comparisons though are comparing the LLM benchmarks against gpt4o, so maybe a valid arguement for the LLM capabilites.
However, I think a lot of the more recent models are pursing architectures with the ability to act on their own like Claude’s computer use - https://docs.anthropic.com/en/docs/build-with-claude/computer-use, which DeepSeek R1 is not attempting.
Edit: and I think the real money will be in the more complex models focused on workflows automation.
Yea except DeepSeek released a combined Multimodal/generation model that has similar performance to contemporaries and a similar level of reduced training cost ~20 hours ago:
https://huggingface.co/deepseek-ai/Janus-Pro-7B
Holy smoke balls. I wonder what else they have ready to release over the next few weeks. They might have a whole suite of things just waiting to strategically deploy
If AI is cheaper, then we may use even more of it, and that would soak up at least some of the slack, though I have no idea how much.
Most rational market: Sell off NVIDIA stock after Chinese company trains a model on NVIDIA cards.
Anyways NVIDIA still up 1900% since 2020 …
how fragile is this tower?
All of this deepseek hype is overblown. Deepseek model was still trained on older american Nvidia GPUs.
Your confidence in this statement is hilarious the fact that it doesn’t help your argument at all. If anything, the fact they refined their model so well on older hardware is even more remarkable, and quite damning when OpenAI claims it needs literally cities worth of power and resources to train their models.
AI is overblown, tech is overblown. Capitalism itself is a senseless death cult based on the non-sensical idea that infinite growth is possible with a fragile, finite system.
Is the “emergence of DeepSeek” really what raised doubts? Are we really sure there haven’t been lots of doubts raised previous to this? Doubts raised by intelligent people who know what they’re talking about?
Ah, but those “intelligent” people cannot be very intelligent if they are not billionaires. After all, the AI companies know exactly how to assess intelligence:
Hilarious that this happens the week of the 5090 release, too. Wonder if it’ll affect things there.
Apparently they have barely produced any so they will all be sold out anyway.
And without the fake frame bullshit they’re using to pad their numbers, its capabilities scale linearly with the 4090. The 5090 just has more cores, Ram, and power.
If the 4000-series had had cards with the memory and core count of the 5090, they’d be just as good as the 50-series.
By that point you will have to buy the Mico fission reactor addon to power the 6090. It’s like Nvidia looked at the power triangle of power / price and preformence and instead of picking two they just picked one and to hell with the rest.
Nah, they just made the triangle bigger with AI (/s)
“wiped”? There was money and it ceased to exist?
It’s pixie dust
The money went back into the hands of all the people and money managers who sold their stocks today.
Edit: I expected a bloodbath in the markets with the rhetoric in this article, but the NASDAQ only lost 3% and the DJIA was positive today…
Nvidia was significantly over-valued and was due for this. I think most people who are paying attention knew that
Trump counterbalance keeping it in check but my gut is saying once tariffs come in February there’s going to be a market correction. Pure speculation on my part.
You don’t have to say speculation when talking about the future of stocks. It’s implied unless you are a time traveler in which case you should lead with that.
I am a time traveller and I was trying to throw you off my trail but I seem to have failed.
There’s been a lot of disproportionate hype around deepseek lately
To be fair, NQ futures momentarily dropped 5% before recovering some. A few days from now on would be interesting.
“off US stocks”
Lol serves you right for pushing AI onto us without our consent
The determination to make us use it whether we want to or not really makes me resent it.
I’d argue this is even worse than Sputnik for the US because Sputnik spurred technological development that boosted the economy. Meanwhile, this is popping the economic bubble in the US built around the AI subscription model.
Wait. You mean every major tech company going all-in on “AI” was a bad idea. I, for one, am shocked at this revelation.
I love how in the US they talk about meritocracy, competition being good, blablabla… but they rig the game from the beginning. And even so, people find a way to be better. Fascinating.
deleted by creator
You’re watching an empire in decline. It’s words stopped matching its actions decades ago.
One Tera Newton? That’s a huge force!
Remember to cancel your Microsoft 365 subscription to kick them while they’re down
I don’t have one to cancel, but I might celebrate today by formatting the old windows SSD in my system and using it for some fast download cache space or something.
Joke’s on them: I never started a subscription!
Wow, China just fucked up the Techbros more than the Democratic or Republican party ever has or ever will. Well played.
Democrats and Republicans have been shoveling truckload after truckload of cash into a Potemkin Village of a technology stack for the last five years. A Chinese tech company just came in with a dirt cheap open-sourced alternative and I guarantee you the American firms will pile on to crib off the work.
Far from fucking them over, China just did the Americans’ homework for them. They just did it in a way that undercuts all the “Sam Altman is the Tech Messiah! He will bring about AI God!” holy roller nonsense that was propping up a handful of mega-firm inflated stock valuations.
Small and Mid-cap tech firms will flourish with these innovations. Microsoft will have to write the last $13B it sunk into OpenAI as a lose.
It’s kinda funny. Their magical bullshitting machine scored higher on made up tests than our magical bullshitting machine, the economy is in shambles! It’s like someone losing a year’s wages in sports betting.
Just because people are misusing tech they know nothing about does not mean this isn’t an impressive feat.
If you know what you are doing, and enough to know when it gives you garbage, LLMs are really useful, but part of using them correctly is giving them grounding context outside of just blindly asking questions.
It is impressive, but the marketing around it has really, really gone off the deep end.
Well… if there is one thing I have to commend CCP is they are unafraid to crack down on billionaires after all.
Didn’t donald add like $500B for AI? Seems it’salmost enough to pay the -$600B nVidia lost…