arcanus

Conversely: in humans, intelligence is inversely correlated with crime.

It doesn't go to zero, however!

How can someone say "the world is in peril" and not be sounding the alarm? Shouldn't they be calling for action across society?!?

That's a surprisingly large overhead. I've not measured that large an impact on AMD, particularly for compute heavy.

Did you profile at all? And have you observed if it's not compute-bound? If it's memory or IO bound it can be due to other virtualization overheads, such as memory encryption.

The manufacturing cost is emphatically not only 1% of the total development cost. Particularly for GPUs, the high bandwidth memory and manufacturing costs are a significant portion of the product price.

I do not find her critique of argument #2 compelling [1]. Monetization of AI is key to economic growth. She's focused on the democratic aspects of AI, which frankly aren't pertinent. The real "race" in AI is between economic and financial forces, with huge infrastructure investments requiring a massive return on investment to justify the expense. From this perspective, increasing the customer base and revenue of the company is the objective. Without this success, investment in AI will drop, and with it, company valuations.

The essay attempted to mitigate this by noting OAI is nominally a non-profit. But it's clear the actions of the leadership are firmly aligned with traditional capitalism. That's perhaps the only interesting subtly of the issue, but the essay missed this entirely. The omission could not have been intentional, because it provides a complete motivation for item #2.

[1] #2 is 'The US is a democracy and China isn’t, so anything that helps the US “win” the AI “race” is good for democracy.'

> And when I reach the part where the AI, having copied itself all over the Internet and built robot factories, then invents and releases self-replicating nanotechnology that gobbles the surface of the earth in hours or days, a large part of me still screams out that there must be practical bottlenecks that haven’t been entirely accounted for here.

This is the crux of the issue. There's simply no clearly articulated doom scenarios that don't involve massive leaps in capabilities that are explained away by the 'singularity' being essentially magic. The entire approach is a doomed version of deus ex machina.

It also appears quite telling the traditional approach is focused on exotic technologies, such as nanotech, and not ICBMs. That's also magical thinking.

The overall funding for starting up a laboratory is much smaller in Europe than the USA.

It's that start up funding that will drive talent, more than anything else.

While FP64 is indeed important for supercomputers, the largest supercomputers have a great deal in common with AI infrastructure.

For example, high bandwidth, low latency interconnects, supporting GPU direct network messaging and IO, are important.

High memory bandwidth is also quite important.

Debugging and performance profiling at scale also commonly uses similar tools.

As these are related to national defense and nuclear security, I've heard they are largely safe.

Thanks! That's consistent with my impression.

> Amazon gets a lot of flak for totally bungling their internal AI model development, squandering massive amounts of internal compute resources on models that ultimately are not competitive, but the custom silicon is another matter

Juicy. Anyone have a link or context to this? I'd not heard of this reception to NOVA and related.

"You may think you know how much Intel is struggling, but the reality is worse."