If the gap closes, we do zero austerity, and interest rates are high, I cannot see a way out of a major economic crisis, even if we do start to see dramatic productivity wins.
More on-topic (and maybe more positive?), but this model feels a bit more expensive than I would have expected!
OpenAI/Anthropic remind me of Silcon Graphics. Sure, lots of people bought those workstations before MP3 / MPEG video were a thing, and before Voodoo came out with the first cheap 3D accelerators. All the tech trends (software and hardware) back in the 1990's were against them, but their valuation stayed high for a bit longer than rational.
Unless there's some second step function change in AI, LLMs comparable to today's state of the art are going to be running on $1-2K machines in a few years, and they'll be doing it fast and with low wattage. There are already a dozen companies that know how to build that, including in the US, Europe and China.
Unlike SGI: Hopefully, given all the political corruption and fraud in this space, we'll see jail time for the guilty parties.
This is a huge claim. What makes you think this will be the case?
Seems like he's just drawing that line into the future. Which seems sensible enough.
But yeah, I assume that when the economy gets back to normal-ish, in 2024-equivalent dollars, we'll be at 500B-1T for < $2000. That'll be 3-4 Moore's Law doublings since computer prices were sane. 125B * 2 ^ 4 = 2T.
But AI labs are datacenter businesses now with the AI part being the driver. Pivoting to selling AI weights for on-premises hardware is a much bigger change. Given the money tied up in data centers, this will be very tough times.
The only thing worse for the economy than failure would be success.
Ant/OAI/Google are way ahead when it comes to the smartest, largest-scale and most compute-intensive models. By Jevons' paradox, if you make inference for leaner models cheaper (as the Chinese models do, being broadly comparable to GPT Terra or Claude Sonnet; barely approaching Opus/Sol at their very best) that only increases demand for the complementary service of very smart inference.
You have to look at the effect in the aggregate, not just what any single actor is doing. This is the core of Jevons' paradox: it's based on surfacing additional demand for the same product (here, expensive model inference) that wasn't previously viable.
On the other side, I am still shocked at how good Qwen 3.8 Flash Next is on my GB10 Spark-like, even if it is only 45 tk/s decode!
Jevons Paradox is not a rule its just a sometimes observed phenomenon
It says nothing one way or the other whether that would happen or not
If any important bank fails because of this, nationalize it and let their customers exit using money from the federal reserve. Then try and recover as much of that as possible using the banks investment portfolio. Costs a lot less than bailouts.
Modern financial system is less „finite amount of money you can move around in a logical way“ and more confidence based definitely totally not a ponzi scheme
What money are you expecting to get int hat scenario? If I had to guess it wouldn't be a fraction of the cost.
> buy out stakes of pension and index funds
Index funds are part of the reason the top companies stock gets so bloated compared to those just outsid of their frame.
>If any important bank fails because of this, nationalize it and let their customers exit using money from the federal reserve. Then try and recover as much of that as possible using the banks investment portfolio. Costs a lot less than bailouts.
I agree. It worked here in Belgium tho they did spin off toxic elements of the bank in a not so great way prior to doing this.(some regular people still got shafted)
I’ve said it for a while now both here and to friends - by Christmas next year, US AI labs will be trying to catch up with Chinese open models.
… and I think once Qwen’s latest open model beats every US labs, it’s over.
If there is an economic boost, it will come from broad productivity improvements and deflation of costs for services. If OpenAI or Anthropic can capitalize on that or not is a separate question.
From biggest to smallest, the top three:
AIG controlled $1.05T and market cap crashed from $180B to $3.8B
Wachovia controlled $782B and market cap crashed from $110B to $1.8B
Lehman Brothers controlled $639B and market cap crashed from $60B to $200M.
Massive companies accounting for lots of money in people's retirment accounts. The companies made mistakes leading to what would have resulted or did result in defaulting on their debts. Suddenly billions of dollars vanished from retirement accounts.
We could very easily see a similar cascade of corrections if we get a few more "Alphabet missed earnings" news calls.
... What on earth. Please go outside for awhile.