I would like a workstation with 900k cores. lmk when these things are on ebay.
Just need that 20kW connection to your energy provider.
a man can dream
100x defect tolerance: How we solved the yield problem
181–186 of 186 posts
Re: 100x defect tolerance: How we solved the yield problem
#182Earlier quoted context omitted.
>It's very different from crypto, the main use case for which appears to be money laundering. Which has substantial economic value (for certain groups of people).
According to this random estimate, black market economy alone in just the US is worth ~ $2 trillion/yr. [ https://www.investopedia.com/terms/u/underground-economy.asp ] Roughly 11-12% of GDP. In many countries, black+grey market is larger than the ‘white’ market. The US is notoriously ‘clean’ compared to most (probably top 10). Even in the US, if you suddenly stopped 10-12% of GDP we’re talking ‘great depression’ lev…
>Honestly, the only reason Crypto isn’t bigger IMO is because there is such a large and established set of folks doing laundering in the ‘normal’ system, and those work well enough there is not nearly as much demand as you’d expect.
Correct me if I'm wrong. Doesn't the public ledger make it really bad for this purpose when enough is known about some of the actors interacting on the chain here? It's basically an exact recording that everybody can see, of who interacted with whom, based on pseudonyms, right?
Re: 100x defect tolerance: How we solved the yield problem
#183Earlier quoted context omitted.
According to this random estimate, black market economy alone in just the US is worth ~ $2 trillion/yr. [ https://www.investopedia.com/terms/u/underground-economy.asp ] Roughly 11-12% of GDP. In many countries, black+grey market is larger than the ‘white’ market. The US is notoriously ‘clean’ compared to most (probably top 10). Even in the US, if you suddenly stopped 10-12% of GDP we’re talking ‘great depression’ lev…
>Honestly, the only reason Crypto isn’t bigger IMO is because there is such a large and established set of folks doing laundering in the ‘normal’ system, and those work well enough there is not nearly as much demand as you’d expect. Correct me if I'm wrong. Doesn't the public ledger make it really bad for this purpose when enough is known about some of the actors interacting on the chain here? It's basically an exact…
You are not wrong.
Cash is superior in the ability to have intermediate transactions hidden. However it has similar issues in that bills are serialized, and I believe scanned/tracked - or at least there is the capability to do so. So in theory, when moving it out of and back into the system, it can be tied to real identities not just pseudonyms too.
Though frankly, it seems like no one really cares most of the time.
Re: 100x defect tolerance: How we solved the yield problem
#184Earlier quoted context omitted.
> Evolution selects for efficiency. I think this is a poor argument here. From an evolutionary point of view, our brains are optimized to: - Provide fine-motor control to craft weapons and tools (enhancing adaptibility and enabling us to hunt way outside our weight class) - Communicate/coordinate effectively in small groups - Do sensor processing and the above with a low energy budget Our brains are *not* selected to…
Just because there are some parts of our brains that are not needed for an AGI... Doesn't mean that there aren't some part of our brains that are needed for an AGI, and are not present in the current crop of LLM.
I think it means that AGIs trained in different ways will have different strengths, just like people.
Re: 100x defect tolerance: How we solved the yield problem
#185The AMD comparison may not be accurate. The 96 core AMD CPU takes multiple such dies (eight if I remember correctly) and separate IO chiplets. The total surface area listed should be much larger.
Re: 100x defect tolerance: How we solved the yield problem
#186Earlier quoted context omitted.
Right. And any particular question people think AIs are bad at also has a comments section of people who have run better crafted prompts that do the job just fine. The consensus is heading more towards "well damn, actually LLMs might be all we need" rather than "LLMs are just a stepping stone" - but either way, that's fine, cuz plenty of more advanced architecture uses are on their way (especially error correction /…
“Crafting a better prompt” is often simply spinning an RNG again and again until you end up with an answer that happens to be good enough. In the real world if you know the correct answer you don’t need to ask the question. A self driving car that needs you to pay attention isn’t self driving. Any system can get canned response, the value of AI is completely in its ability to handle novelty without hand holding. And…
Any time prompt crafting matters is just when demonstrating the current edge of capabilities - next iteration, you can get away with a much more general/primitive prompt. Those are just people countering the "gotcha" arguments people try to levy against LLMs, showing that even now those tasks can be done with a good prompt. Anytime it's a practical concern though - just wait a little longer for the next model to smooth that out.
You don't have to pay attention, that's the point. You can code without reading code now. Sure you gotta tell it what the app looks like with each iteration - but again, that's temporary til the next model comes out with good enough vision to assess that itself. None of this is permanently planning on requiring human interaction - it's just early days and these are progressing through mediums one at a time.
They're not canned responses either. They're bespoke mixtures of all the various elements of the current environment/context translated to an answer. It certainly handles novelty - that's the whole point. They certainly handle plenty of novelty - like entire mediums of text and images - to expert levels. I think you're just being greedy for more, here.
As for consistency and avoiding error? There are benchmarks for that. There are error checking methods. Those are all steadily improving too, and are already well-consistent on easier topics/mediums. It would be foolish to think that's innately impossible from AI for remaining ones.