Zander Steele

Helping data centers get built faster. If you're building data centers and need powered land/shells, email me zander at kratos dot ai.

[Zander Steele @zander__steele]

Honest question - how many CA Billionaires does Ro expect to leave?

How many of the companies that they run does he expect to incorporate elsewhere?

It will be a non-trivial number and it’s foolish to expect anything else.

[Ro Khanna @RoKhanna]

My district is $18 trillion, nearly 1/3 of US stock market in a 50 mile radius. We have 5 companies with a market cap over a trillion dollar companies. If I can stand up for a billionaire tax, this is not a hard position for 434 other members or 100 Senators.

Those saying that we wouldn't have a future NVIDIA in the Bay if this tax goes into effect are glossing over Silicon Valley history. Jensen was at LSI Logic and his co-founders at Sun. He started NVIDIA in my district because of the semiconductor talent, Stanford, innovation networks, and venture funding. We have 37 times the VC money as Austin given the innovation ecosystem & Florida isn't even on the map. Jensen wasn't thinking I won't start this company because I may have to one day pay a 1 percent tax on my billions. He built here because the talent is here.

AI was created with our tax dollars. ImageNet was created by Fei-Fei Li at Stanford using NSF money. This was a visual database. Hinton presented at an ImageNet conference his famous paper. The seminal innovation in tech is done by thousands often with public funds. NSF, DARPA, Stanford, Berkley, San Jose State, Santa Clara and the UCs are the foundation for what has made Silicon Valley a powerhouse. It's why we won 5 Nobel Prizes this year in the UC system.

Yes, we need entrepreneurs to commercialize disruptive innovation. Stanford blazed a trail in licensing technology & partnering with the private sector. The university enabled companies like Google which began as a research project called BackRub, looking at back links to rank pages. And entrepreneurs like Brin & Page reap huge rewards when they succeed. But the idea that they would not start companies to make billions, or take advantage of an innovation cluster, if there is a 1-2 percent tax on their staggering wealth defies common sense and economic theory @paulkrugman @DAcemogluMIT @baselinescene.

We cannot have a nation with extreme concentration of wealth in a few places but where 70 percent of Americans believe the American dream is dead and healthcare, childcare, housing, education is unaffordable. What will stifle American innovation, what will make us fall behind China, is if we see further political dysfunction and social unrest, if we fail to cultivate the talent in every American and in every city and town.

The industrial revolution saw soaring inequality in Britain for nearly 60 years. On the continent, it lead to revolutions in France with worker uprisings (1848) and contributed to one in Russia (1917). America's central challenge is to make sure the AI revolution works for all of us, not just tech billionaires.

So yes a billionaire tax is good for American innovation which depends on a strong and thriving American democracy.

[Zander Steele @zander__steele]

My read = we're still early. Excited to see NVIDIA earnings later today and the first models trained on Blackwell to validate the thinking.

[Zander Steele @zander__steele]

Really good analysis. Things that excite me from this:

1. Gemini 3 is really good. Both in anecdotal reviews & on benchmarks. It was trained on significant compute. As blackwell (latest Nvidia chipset) comes online, we should expect models to keep getting a lot better.

[Gavin Baker @GavinSBaker]

https://t.co/boFKQfPb3G

[Zander Steele @zander__steele]

4. More validation that GPU depreciation cycles might even be LONGER than 6 years. This would lead to lower financing costs + more financing $$ available.

[Zander Steele @zander__steele]

Semianalysis expects 60% CAGR for AI data centers through 2029. McKinsey expects 51% CAGR.

Absurd numbers.

[Jukan @jukan05]

Institutional forecasts for AI data center power capacity.

Semianalysis is the most bullish.

[Zander Steele @zander__steele]

Bad: CoreWeave tempered expectations for Q4 revenue due to a delay in construction from one of their data center partners.

Turns out land, power, electrical infrastructure, permitting, and actually getting large DCs live is hard.

[Zander Steele @zander__steele]

2 highlights from $CRWV earnings yesterday, one great and one not so great.

Great: Their entire supply of A100s are sold out. These chips were released 5.5 years ago.

[Zander Steele @zander__steele]

Folks skeptical about the depreciation cycle of GPUs in shambles.

Layer this with $GOOG saying their 8 year old TPUs are still fully utilized as well = GREAT sign that AI chips will be useful longer than we expected.

[Zander Steele @zander__steele]

Not sure if this was planned to test the waters or just a faux pas but the administration had a quick and resolute response: federal backing is off the table.

[Zander Steele @zander__steele]

Market did not like this.

[David Sacks @DavidSacks]

There will be no federal bailout for AI. The U.S. has at least 5 major frontier model companies. If one fails, others will take its place.

[Zander Steele @zander__steele]

Given the $1.4T of commitments OpenAI has in next 8 years, it goes without saying this would have huge ripple effects. For comparison, Anthropic has ~$200B of commitments and xAI has ~$100B.

[Zander Steele @zander__steele]

If log C = I: 200× compute → ~1.5× smarter models.

If log C = log I (I ∝ Cᵏ): 500× compute → 1.6–4× smarter (k ≈ 0.1–0.3).

Something to watch closely as more superclusters get completed & used to train new models.

[Zander Steele @zander__steele]

@sama on the recent BG2 pod (with @altcap & @satyanadella):

“log of compute is the log of intelligence.”

That’s a big shift from V1 of this scaling law: intelligence ≈ log compute.

[Zander Steele @zander__steele]

Some reports state Grok 4 used ~250k H100 equivalents.

xAI is targeting ~50M H100-equivalents by 2030.

That’s 200x more compute.

[Zander Steele @zander__steele]

Minnesota: <20MW - no study required

Wisconsin: $50k, 60 days.

Oklahoma: Initial $1k, 90 days. Final $500k, 120 days.

Tennessee: Initial $0, 60 days. Final $20k, 4-6 months

North Carolina: $250k, 24 months

[Zander Steele @zander__steele]

Federal transmission study regulation can't come fast enough.

A few examples from different geographies we're exploring: