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.
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
Yes but that’s not the point… If you can buy a house for $1000 nobody would buy a similar house for $500000
Eventually the field would even out and maybe demand would surpass current levels, but for the time being, Nvidia’s offer seem to be a giant surplus and speculators will speculate
fascinating. my boss really bought into the tech bro bullshit, every time we get coffee as a team, he’s always going on and on about how chatGPT will be the savior of humanity, increase productivity so much that we’ll have a 2 day work week, blah blah blah.
I’ve been on his shit list lately because i had to take some medical leave and didn’t deliver my project on time.
Now that this thing is open sourced, I can bring it to him, tell him it out performs even chatgpt O1 or whatever it is, and tell him that we can operate it locally. I’ll be off the shit list and back into his good graces and maybe even get a raise.
Your boss sounds like he buys into bullshit for a living. Maybe that’s what drew him to the job, lol.
I think believing in our corporate AI overlords is even overshadowed by believing those same corporations would pass the productivity gains on to their employees.
But I feel like that will just lead to more training with the same (or more) hardware with a more efficient model. Bitcoin mining didn’t slow down only because it got harder. However I don’t know enough about the training process. I assume more efficient use of the hardware would allow for larger models to be trained on the same hardware and training data?
They’ll probably do that, but that’s assuming we aren’t past the point of diminishing returns.
The current LLM’s are pretty basic in how they work, and it could be that with the current training we’re near what they’ll ever be capable of. They’ll of course invest a billion in training a new generation, but if it’s only marginally better than the current one, they won’t keep investing billions into it if it doesn’t really improve the results.
nvidia falling doesn’t make much sense to me, GPUs are still needed to run the model. Unless Nvidia is involved in its own AI model or something?
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
https://en.wikipedia.org/wiki/Jevons_paradox
more efficient use of oil will lead to increased demand, and will not slow the arrival or the effects of peak oil.
Energy demand is infinite and so is the demand for computing power because humans always want to do MORE.
Yes but that’s not the point… If you can buy a house for $1000 nobody would buy a similar house for $500000
Eventually the field would even out and maybe demand would surpass current levels, but for the time being, Nvidia’s offer seem to be a giant surplus and speculators will speculate
If you need far less computing power to train the models, far less gpus are needed, and that hurts nvidia
does it really need less power? I’m playing around with it now and I’m pretty impressed so far. it can do math, at least.
That’s the claim, it has apparently been trained using a fraction of the compute power of the GPT models and achieves similar results.
fascinating. my boss really bought into the tech bro bullshit, every time we get coffee as a team, he’s always going on and on about how chatGPT will be the savior of humanity, increase productivity so much that we’ll have a 2 day work week, blah blah blah.
I’ve been on his shit list lately because i had to take some medical leave and didn’t deliver my project on time.
Now that this thing is open sourced, I can bring it to him, tell him it out performs even chatgpt O1 or whatever it is, and tell him that we can operate it locally. I’ll be off the shit list and back into his good graces and maybe even get a raise.
Your boss sounds like he buys into bullshit for a living. Maybe that’s what drew him to the job, lol.
I think believing in our corporate AI overlords is even overshadowed by believing those same corporations would pass the productivity gains on to their employees.
But I feel like that will just lead to more training with the same (or more) hardware with a more efficient model. Bitcoin mining didn’t slow down only because it got harder. However I don’t know enough about the training process. I assume more efficient use of the hardware would allow for larger models to be trained on the same hardware and training data?
They’ll probably do that, but that’s assuming we aren’t past the point of diminishing returns.
The current LLM’s are pretty basic in how they work, and it could be that with the current training we’re near what they’ll ever be capable of. They’ll of course invest a billion in training a new generation, but if it’s only marginally better than the current one, they won’t keep investing billions into it if it doesn’t really improve the results.