The Tenstorrent ISA is documented btw https://github.com/tenstorrent/tt-isa-documentation, I wonder if one could do the verification end-to-end with the hardware.

https://github.com/aws-neuron/torch-neuronx

Also I guess this is the final nail in the coffin of Tensorflow.

Since HW specifics live mostly in the kernel layer (Pallas or CUDA), I imagine the Jax vs PyTorch question is more of a style preference now?

"No, but I have seen the house that the project built, and it is terrific." ~ some Google director

Is a pretty successful open source NVR that used corals when it launched (and many people still use them with it)

"OpenTPU: Open-Source Reimplementation of Google Tensor Processing Unit (TPU)" https://news.ycombinator.com/item?id=44111452

From https://news.ycombinator.com/item?id=45848676 :

> How does Cerebras WSE-3 with 44GB of 'L2' on-chip SRAM compare to Google's TPUs, Tesla's TPUs, NorthPole, Groq LPU, Tenstorrent's, and AMD's NPU designs?

There are TPUs made out of silicon carbide with standard fab.

There is in-flight tensor processing with photons, but that's not quite a TPU.

There will be an abundance of shovels. Nebius already crashed by almost half from its hype peak.

either AI achieves hyper-efficiency and triggers systematic economic demand destruction due to unemployment, or it underperforms and sparks a massive tech-sector asset bubble burst

If AI is as good as valuations - it crashes. If AI isn’t as good, it crashes. all eggs in one basket economy.

Every future leads to a massive financial shitstorm

AI is priced in as a technology to end all markets. The last bull market you will ever see.

It’s a miracle markets didn’t notice this “damned if you succeed damned if you don’t” type of inevitable checkmate

I have been building a bunker

They learned from 2008 that Too Big Too Fail(tm) means the government bails you out.

This was the problem with not OBLITERATING the banks in 2008. Had the US government taken over the banks and wiped the investors, there would be more pushback right now.

It's currently larger than the 1880s railroad boom.

"Overbuilding and speculative debt ultimately culminated in the Panic of 1893, plunging the nation into a severe economic depression."

"During the 1880s, private railroad enterprises represented over 60% of the total capitalization of the entire U.S. stock market, peaking at 63% in 1881 and 1885."

But as a % of total GDP, you are correct.

In terms of infra spending as a percent of GDP, 1880s railroads were at 5-6% at peak while AI is estimated to reach 3+% in a year or two.

Every time I ask Claude to do something, it does it just fine. I never have to wait in any sort of queue that would be common in other kinds of shortages.

The hyperscalers are all so oversubscribed that they require commits from enterprises so if you only have a transient need you might be out of luck [from your vendor of choice]. Additionally, not all GPU service providers are equal. Semi Analysis has some great articles explaining why.

Pricing -- exactly where shortages show up in a free market economy.

what I'm wondering: is there a shortage of compute in the current installed base? Why isn't the installed base of compute increasing drastically in price, and/or forcing me to wait in a queue to use it?

Have you looked at RAM prices lately?

Installed base is existing computers that already have RAM. Why aren't VM rental prices going way up?

No, rationing is what you get in command/centralized economies like the USSR. In free market economies you get price explosion, like we're seeing right now with DRAM wafers.

like, I can rent a VM from AWS for the same price as 5 years ago...

Is this somehow Google's answer to today's best DeepSeek open-sourcing inferencing engine?

Personally the question is if they are "saving" other projects or news so they can be released in case a competitor makes a move? Who knows if this was ready days or weeks ago and were waiting on someone to drop some news, so they can shadow those news.

In that sense AMD is still better positioned to give NVidia a run for their money but given the family connection and AMD's underdog status I am not very hopeful that we'll see meaningful competition in inference hardware any time soon.

NVidia is a much harder nut to crack than OpenAI or Anthropic. They are easily a decade ahead of viable competition. Check out the GB300 if you don't believe that.

High bandwidth flash will be here soon, I bet someone makes an economical competitor thats not quite as fast but much cheaper.