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.
Why? If you automatize away (regardless of whether it’s feasible or not) all the workers, what’s stop them for cutting them out of the equation? Why can’t they just trade assets between themselves, maintaining a small slave population that does machine maintenance for food and shelter and screwing the rest? Why do you think they still need us if they own both the means for the production as well as labor to produce? That would be a post-labour scarcity economy, available only for the wealthy and with the rest of us left to rot. If you have assets like land, materials, factories you can participate, if you don’t, you can’t
While I don’t think that this is feasible technologically yet by any means, I think this is what the rich are huffing currently. They want to be independent from us because they are threatened by us.
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.
I follow EV battery tech a little. You’re not wrong that there is a lot of “oh its just around the bend” in battery development and tech development in general. I blame marketing for 80% of that.
But battery technology is changing drastically. The giant cell phone market is pushing battery tech relentlessly. Add in EV and grid storage demand growth and the potential for some companies to land on top of a money printing machine is definitely there.
We’re in a golden age of battery research. Exciting for our future, but it will be a while before we consumers will have clear best options.
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…
Yes, I know, I tried all kinds of inputs, ways to query it, including full code-bases etc.
Long story short: I’m faster just not caring about AI (at the moment).
As I said somewhere else here, I have a theoretical background in this area.
Though speaking of, I think I really need to try out training or refining a DeepSeek model with our code-bases, whether it helps to be a good alternative to something like the dumb Github Copilot (which I’ve also disabled, because it produces a looot of garbage that I don’t want to waste my attention with…) Maybe it’s now finally possible to use at least for completion when it knows details about the whole code-base (not just snapshots such as Github CoPilot).
So unreliable boilerplate generator, you need to debug?
Right I’ve seen that it’s somewhat nice to quickly generate bash scripts etc.
It can certainly generate quick’n dirty scripts as a starter. But code quality is often supbar (and often incorrect), which triggers my perfectionism to make it better, at which point I should’ve written it myself…
But I agree that it can often serve well for exploration, and sometimes you learn new stuff (if you weren’t expert in it at least, and you should always validate whether it’s correct).
But actual programming in e.g. Rust is a catastrophe with LLMs (more common languages like js work better though).
I use C# and PS/CMD for my job. I think you’re right. It can create a decent template for setting things up. But it trips on its own dick with anything more intricate than simple 2 step commands.
confidently so in the face of overwhelming evidence
That I’d really like to see. And I mean more than the marketing bullshit that AI companies are doing…
For the record I was one of the first jumping on the AI hype-train (as programmer, and computer-scientist with machine-learning background), following the development of GPT1-4, being excited about having to do less boilerplaty code etc. getting help about rough ideas etc. GPT4 was almost so far as being a help (similar with o1 etc. or Anthropics models). Though I seldom use AI currently (and I’m observing similar with other colleagues and people I know of) because it actually slows me down with my stuff or gives wrong ideas, having to argue, just to see it yet again saturating at a local-minimum (aka it doesn’t get better, no matter what input I try). Just so that I have to do it myself… (which I should’ve done in the first place…).
Same is true for the image-generative side (i.e. first with GANs now with diffusion-based models).
I can get into more details about transformer/attention-based-models and its current plateau phase (i.e. more hardware doesn’t actually make things significantly better, it gets exponentially more expensive to make things slightly better) if you really want…
I hope that we do a breakthrough of course, that a model actually really learns reasoning, but I fear that that will take time, and it might even mean that we need different type of hardware.
Any other AI company, and most of that would be legitimate criticism of the overhype used to generate more funding. But how does any of that apply to DeepSeek, and the code & paper they released?
Yeah it’ll be exciting to see where this goes, i.e. if it really develops into a useful tool, for certain. Though I’m slightly cautious non-the less. It’s not doing something significantly different (i.e. it’s still an LLM), it’s just a lot cheaper/efficient to train, and open for everyone (which is great).
Even o1 (which AFAIK is roughly on par with R1-671B) wasn’t really helpful for me. I just need often (actually all the time) correct answers to complex problems and LLMs aren’t just capable to deliver this.
I still need to try it out whether it’s possible to train it on my/our codebase, such that it’s at least possible to use as something like Github copilot (which I also don’t use, because it just isn’t reliable enough, and too often generates bugs). Also I’m a fast typer, until the answer is there and I need to parse/read/understand the code, I already have written a better version.
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?
I’m referring to output for amount of work put in.
I’m a socialist. I care about increased output leading to increased comfort for the general public. That the gains are concentrated among the wealthy is not the fault of technology, but rather those who control it.
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?
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.
Because rulling class got high on the promise that they could finally eliminate workers as a cost and be independent from us.
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.
Why? If you automatize away (regardless of whether it’s feasible or not) all the workers, what’s stop them for cutting them out of the equation? Why can’t they just trade assets between themselves, maintaining a small slave population that does machine maintenance for food and shelter and screwing the rest? Why do you think they still need us if they own both the means for the production as well as labor to produce? That would be a post-labour scarcity economy, available only for the wealthy and with the rest of us left to rot. If you have assets like land, materials, factories you can participate, if you don’t, you can’t
While I don’t think that this is feasible technologically yet by any means, I think this is what the rich are huffing currently. They want to be independent from us because they are threatened by us.
They want you to owe your soul to the company store, to live hand-to-mouth by their largess.
Those are different "we"s.
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 like how revolutionary battery technology is always just months away.
I follow EV battery tech a little. You’re not wrong that there is a lot of “oh its just around the bend” in battery development and tech development in general. I blame marketing for 80% of that.
But battery technology is changing drastically. The giant cell phone market is pushing battery tech relentlessly. Add in EV and grid storage demand growth and the potential for some companies to land on top of a money printing machine is definitely there.
We’re in a golden age of battery research. Exciting for our future, but it will be a while before we consumers will have clear best options.
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.
Monorail!!!
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.
https://youtube.com/@inside_china_business
And you could pay people to use an abacus instead of a calculator. But the advanced tech improves productivity for everyone, and helps their output.
If you don’t get the tech, you should play with it more.
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…
If you are blindly asking it questions without a grounding resources you’re gonning to get nonsense eventually unless it’s really simple questions.
They aren’t infinite knowledge repositories. The training method is lossy when it comes to memory, just like our own memory.
Give it documentation or some other context and ask it questions it can summerize pretty well and even link things across documents or other sources.
The problem is that people are misusing the technology, not that the tech has no use or merit, even if it’s just from an academic perspective.
Yes, I know, I tried all kinds of inputs, ways to query it, including full code-bases etc. Long story short: I’m faster just not caring about AI (at the moment). As I said somewhere else here, I have a theoretical background in this area. Though speaking of, I think I really need to try out training or refining a DeepSeek model with our code-bases, whether it helps to be a good alternative to something like the dumb Github Copilot (which I’ve also disabled, because it produces a looot of garbage that I don’t want to waste my attention with…) Maybe it’s now finally possible to use at least for completion when it knows details about the whole code-base (not just snapshots such as Github CoPilot).
Try getting a quick powershell script from Microsoft help or spiceworks. And then do the same on GPT
What should I expect? (I don’t do powershell, nor do I have a need for it)
I think the sentiment is the same with any code language.
So unreliable boilerplate generator, you need to debug?
Right I’ve seen that it’s somewhat nice to quickly generate bash scripts etc.
It can certainly generate quick’n dirty scripts as a starter. But code quality is often supbar (and often incorrect), which triggers my perfectionism to make it better, at which point I should’ve written it myself…
But I agree that it can often serve well for exploration, and sometimes you learn new stuff (if you weren’t expert in it at least, and you should always validate whether it’s correct).
But actual programming in e.g. Rust is a catastrophe with LLMs (more common languages like js work better though).
I use C# and PS/CMD for my job. I think you’re right. It can create a decent template for setting things up. But it trips on its own dick with anything more intricate than simple 2 step commands.
It’s one thing to be ignorant. It’s quite another to be confidently so in the face of overwhelming evidence that you’re wrong. Impressive.
That I’d really like to see. And I mean more than the marketing bullshit that AI companies are doing…
For the record I was one of the first jumping on the AI hype-train (as programmer, and computer-scientist with machine-learning background), following the development of GPT1-4, being excited about having to do less boilerplaty code etc. getting help about rough ideas etc. GPT4 was almost so far as being a help (similar with o1 etc. or Anthropics models). Though I seldom use AI currently (and I’m observing similar with other colleagues and people I know of) because it actually slows me down with my stuff or gives wrong ideas, having to argue, just to see it yet again saturating at a local-minimum (aka it doesn’t get better, no matter what input I try). Just so that I have to do it myself… (which I should’ve done in the first place…).
Same is true for the image-generative side (i.e. first with GANs now with diffusion-based models).
I can get into more details about transformer/attention-based-models and its current plateau phase (i.e. more hardware doesn’t actually make things significantly better, it gets exponentially more expensive to make things slightly better) if you really want…
I hope that we do a breakthrough of course, that a model actually really learns reasoning, but I fear that that will take time, and it might even mean that we need different type of hardware.
Any other AI company, and most of that would be legitimate criticism of the overhype used to generate more funding. But how does any of that apply to DeepSeek, and the code & paper they released?
Yeah it’ll be exciting to see where this goes, i.e. if it really develops into a useful tool, for certain. Though I’m slightly cautious non-the less. It’s not doing something significantly different (i.e. it’s still an LLM), it’s just a lot cheaper/efficient to train, and open for everyone (which is great).
What’s this “if” nonsense? I loaded up a light model of it, and already have put it to work.
Have you actually read my text wall?
Even o1 (which AFAIK is roughly on par with R1-671B) wasn’t really helpful for me. I just need often (actually all the time) correct answers to complex problems and LLMs aren’t just capable to deliver this.
I still need to try it out whether it’s possible to train it on my/our codebase, such that it’s at least possible to use as something like Github copilot (which I also don’t use, because it just isn’t reliable enough, and too often generates bugs). Also I’m a fast typer, until the answer is there and I need to parse/read/understand the code, I already have written a better version.
“Improves productivity for everyone”
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?
I’m referring to output for amount of work put in.
I’m a socialist. I care about increased output leading to increased comfort for the general public. That the gains are concentrated among the wealthy is not the fault of technology, but rather those who control it.
Thank god for DeepSeek.
Education doesn’t make a tech CEO ridiculously wealthy, so there’s no draw for said CEOs to promote the shit out of education.
Plus educated people tend to ask for more salary. Can’t do that and become a billionaire!
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.
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?