aurareturn

This is a very pessimistic look at things.

There will be some growing pains for some, yes. But overall, I think it will ultimately create more jobs than ever. History is full of examples where people thought a new invention leads to catastrophic job loss, then the Earth had more jobs than ever.

We have enough jobs in 2026 to keep most of the 8.3 billion people employed somehow.

Human mathematicians also have to eat right, trained, etc.

If there is ever a conflict, US will seize assets of whatever country it is fighting with.

Just some quick math, the video says each rack contains 3 wafer scale chips. Each chip is 4 trillion transistors. In total, there are 12 trillion transistors for compute inside each rack.

A Vera Rubin rack contains 72 Rubin GPUs, containing 2 dies for each GPU, and have an estimated 24 trillion transistors for compute.

So a Vera Rubin rack has 2x more transistors for compute. Not only that but each Vera Rubin rack contains 36 Vera CPUs totaling 3,168 CPU cores and an additional 8 trillion transistors.

It seems like an Nvidia rack contains vastly more transistors - not counting memory chips.

In terms of intelligence per token per cost, OpenAI is really killing it.

Would like to see the math since the claim is made.

So why can't OpenAI/Anthropic also distill the good parts of free Chinese models? It's even better and easier for OpenAI and Anthropic. No poison pills as well.

Still looks like dial up era. When it's so fast that displaying the UI/clicks/navigation to humans is pointless, then it'll be broadband era.

How much advantage in costs? What % of labor is training cost?

Ultimately, that's what I need to be convinced. No one has put forth a good argument yet.

Clever architecture --> Ok but OpenAI/Anthropic can use these as well and they also have very smart people with their secret clever architectures

Distilling --> Ok but distilling means you will never be smarter than the original. Furthermore, reasoning is now hidden by private labs and they have poison pill answers for distilling if they can detect it. They will be able to detect distilling better and better.

Cheaper electricity --> Ok this is cancelled out by their chips being much less efficient due to not having ASML EUV machine access.

So I don't see why fundamentally their training costs are cheaper over the long term.

I'm looking for a no-moatist to convince me.

Arguably, Nvidia owning Hugging Face means they no longer need to care so much about platform profitability.

The more models they open source, and the more companies they can convince to open source, the higher the value of Nvidia chips become.

But fundamentally, why is their cost 1/20 and is it sustainable in the next 10 years of competition?

So in the movie WallE, everyone is fat and unfit. But it looks like the movie left out biotech to make humans not fat, more muscular, and more fit.

Why do you think Chinese models cost 1/20th to train?

  I think it mostly shows that there is no moat

You can argue that TSMC has no moat since Intel and Samsung are also able to eventually make a node as good as TSMC - just a few years later and at smaller scale.

And no one would say that about TSMC.

So there is clearly a moat there somewhere.

Why do you think we don't use our brains when we use Claude Code?

Arguably, my brain usage is higher when using Claude Code. It's just used in a different way.

Looks like a SpaceX issue then.

It goes down so often that I've advocated my company create enterprise Codex accounts as backup for devs.

Why do you think there is no one or nothing that is helping people who lose their jobs?

Reports are that he checked out of day to day work well before his reassignment.

Sometimes it is hard for a scientist by nature to build and iterate and lead revenue generating products.

Ed Zitron is a grifter. Period. I highly doubt he believes any of the stuff he writes himself. He plays a role in society which is the role that tells people AI is going to fail so those who don't participate in or benefit from AI feel better. They sign up to his subscriptions and pay him money to confirm their own bias.

If you look at the sub reddit r/betteroffline where these people gather and worship Zitron, most people there are economically motivated. Most of them want AI to collapse so they can invest in stocks when it's cheap or they hope AI doesn't take their jobs.

No I bought it over a year before this “marketing”.

I’ve found a new use for it which I’m assuming others have as well.

  Either they're running Claude Code with a local LLM (technically possible via dev tools albeit unsupported), or they genuinely have no idea why the Mac is good for AI and just bought it because they were told it was good for AI.

Neither. I use Claude Code subscription through my Mac Mini when I’m on the go.

They made a dedicated chip because miners were buying up all the GPUs from gamers.

They also nerfed GPU hash rates through software to prevent miners from buying them.

Two of those links were Macs. No surprise. Macbooks selling like hotcakes due to AI. Not just local LLMs but also just really efficient *nix machines that AI agents love to use for productivity.

They didn't make their GPUs for crypto. Crypto companies just bought a lot of their GPUs.

If they had a choice, they would have sold every GPU to gamers instead because a crypto boom was always followed by a crash which flooded the market with used GPUs and crashed Nvidia's stock price.

I develop using a Macbook primarily. Having a Mac Mini keeps the environment the same when I'm on the go. Plus, any home server would not be as efficient or fast as a Mini with an M4.

  I'm convinced that this is just guerilla marketing from Apple. 

I'm not. I have an M4 Mac Mini running 24/7 so I can use it as my Claude Code machine when I'm on the go.

Why would they do a guerilla marketing campaign now if their Macs are generally sold out despite nearly doubling the Mac Mini price in the last few months?

In the video.

Is this just propaganda to:

1. Create government regulation which will prevent new competitors

2. Make AI sound scary to the public so the government gets support to ban advanced Chinese models in order to help Anthropic and OpenAI