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Open source AI must win

opensourceaimustwin.com

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Re: Open source AI must win

#521

Post by kamaal »

jongjong wrote: post #357
kamaal wrote: post #255

Earlier quoted context omitted.

>>We just don't know what the maximum capability of AI is For all theory purposes there is no limit. Thats what the latest loop engineering trend is about, you are asking AI to find solutions to a problem going by listing steps, and if solution not found in those steps, to treat each step as a separate problem and repeat the process until the master solution to the master problem is found. Once a solution is found, o…

Yeah, the latest models are really good. For implementing leetcode-type solutions, Claude Opus is smarter than essentially all engineers I've ever worked with and smarter than me as well. The one area where I beat it hands-down is technical decision-making; it sucks at architecture, maintainability, performance and scalability. Agency seems to correlate with the ability to make good decisions. It's kind of surprising…

Agency is just to keep moving, like stop at nothing and keep moving, no matter what. Movement generates information, that can be used to make further decisions, even if you actually don't hit your goal at bulls eye accuracy you do end up getting a lot far and learn a lot.

So we are kind of there at runaway intelligence today.

Re: Open source AI must win

#526

Post by AshamedCaptain »

nl wrote: post #519
AshamedCaptain wrote: post #406

Earlier quoted context omitted.

The analogy falls apart very quickly. Without the training data, your modifications amount to virtually nothing compared to what these "versions" are, and the idea that you can maintain and improve on these models without the continual support of the company that owns the training data AND harnesses AND in general build instructions is not very credible. This is why it's not rare that they "dump" old versions as free…

> The analogy falls apart very quickly. Without the training data, your modifications amount to virtually nothing compared to what these "versions" are, and the idea that you can maintain and improve on these models without the continual support of the company that owns the training data AND harnesses AND in general build instructions is not very credible. This is completely wrong, and sort of shows why what you are…

> You can post-train any LLM very easily without access to the original training data.

Are you claiming this is e.g. what Alibaba spends their time doing?

My point is that the usefulness of this is limited _in comparison to the one provided by having their training data AND mechanisms_.

Re: Open source AI must win

#527

Post by AshamedCaptain »

cortesoft wrote: post #520
CharlesW wrote: post #475

Earlier quoted context omitted.

In case you're not just trolling, please learn how "the weights", which are analgous to a compiled executable, are made.

The weights are created through training. The 'source' would be the training data, which is going to be a massive amount of data, and is not something that could just be easily shared.

And?

Re: Open source AI must win

#528

Post by ux266478 »

sho wrote: post #238
ux266478 wrote: post #213

Earlier quoted context omitted.

AI hardware is for inference, not training. Training uses normal HPC crap. Superpods aren't really power efficient, it's kind of a meme, and it stems from limiting the power draw of other components by having less of them. It's more of a rounding error. > you'd end up consuming so much excess electricity it would be cheaper on net to simply take the money that would have gone to the power bill and spend it on your ow…

> AI hardware is for inference, not training Not sure what you are referring to, unless you don't think h100/h200/b200 are "AI hardware" > Superpods aren't really power efficient Maybe not compared to a specialized rig with multiple 4090s, but that is the best case for consumer hardware - the vast majority will be dramatically less efficient than that Anyway, I agree the interconnect is by far the biggest obstacle an…

I wouldn't consider those AI hardware, no. They're normal GPGPUs.

Re: Open source AI must win

#529

Post by ux266478 »

rurban wrote: post #336
ux266478 wrote: post #213

Earlier quoted context omitted.

AI hardware is for inference, not training. Training uses normal HPC crap. Superpods aren't really power efficient, it's kind of a meme, and it stems from limiting the power draw of other components by having less of them. It's more of a rounding error. > you'd end up consuming so much excess electricity it would be cheaper on net to simply take the money that would have gone to the power bill and spend it on your ow…

You got it wrong. Inference can use crap GPU's. Training needs the 100x more expensive big guns. Our training machine is 100x more expensive than our inference machine.

What I'm saying is those 100x more expensive big guns are just normal GP HPC howitzers. Systems that are exclusively designed for AI and nothing else are more or less all just edge inference TPUs.
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