Tech
Density of AI postings by metro area clusters
Sherwood News

Charted and mapped: Which American cities are the most ready for AI?

Just 30 top-performing metro areas capture two-thirds of all AI job postings.

Rani Molla

Tech companies are tripping over themselves to invest in artificial intelligence, but that wealth is not spreading evenly across the US.

A new analysis from nonprofit Brookings Metro, which is part of the Brookings Institution, looked at data from 195 of the largest US metropolitan areas to determine where they stood as far as AI talent (the availability of AI-capable workers and relevant degree programs), innovation (research programs, AI R&D spending, patents), and adoption (industry uptake, AI startups).

In doing so, Brookings came up with six different categories of AI readiness. Here’s how it categorizes the metro areas, from most ready to reap the benefits of AI development to least:

• “Superstars: The San Francisco and San Jose, Calif., metropolitan areas exhibit unmatched strength across all three AI pillars (talent, innovation, and adoption).

• Star Hubs: This group of 28 metro areas forms a second echelon of uniformly strong AI ecosystems, balancing top‑tier talent, research, and enterprise uptake.

• Emerging Centers: This group of 14 metro areas combines top performance in two pillars with one developing area.

• Focused Movers: These 29 metro areas excel in one pillar while maintaining foundations in the other two.

• Nascent Adopters: This group of 79 metro areas shows moderate performance across all three pillars.

• Others: A group of 43 metro areas that currently lags on multiple pillars.”

Brookings found that much of AI opportunity is concentrated among the usual suspects, with the Bay Area, where tech giants Google, Apple, and Meta have their headquarters, accounting for 13% of national job postings featuring AI skills. (San Francisco and San Jose are the only superstars on the list.) Combined with the Star Hubs, which includes places like Seattle, Washington, DC, and Austin, the 30 top-performing metro areas captured 67% of total AI job postings. 

However, there are signs of geographic diffusion beyond the known tech and coastal cities, in places like Pittsburgh; Detroit; Madison, Wisconsin; and Huntsville, Alabama, which rank in the top quartile in at least two pillars, which make them Emerging Centers.

“While the Bay Area’s dominance isn’t going down, we see other places rising up the ranks,” Shriya Methkupally, senior research assistant at Brookings Metro, told Sherwood News. She said the situation is much more spread out than it was the last time Brookings studied this topic in 2021.

Still, Brookings found that more than half of US metro areas were in the bottom two tiers, Nascent Adopters and Others, suggesting “significant shortfalls in talent pipelines, research infrastructure, and enterprise adoption.”

While the Superstars are only on the West Coast, Star Hubs and Emerging Centers are popping up in places around the country, including within the Sun Belt and the Rust Belt.

And here those metro areas are separated out by category and ranked by AI job postings per 100 people employed in the area:

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Jon Keegan

FT: Meta considering “tens of billions” in new capital to fund AI

Just days after Google announced a monster $85 billion upsized equity raise, the extremely profitable Meta is seeking to sell “tens of billions of dollars” in stock, according to a new report from the Financial Times.

Meta is planning on spending between $125 billion and $145 billion on AI capital expenditure this year alone.

Shares dropped more than 5% on the news.

Meta weighs big equity raising after blockbuster Google deal

Meta weighs big equity raising after blockbuster Google deal
Rani Molla
6/5/26
Meta is supercharging its subscription businesses

The free-app giant never really cared about recurring revenue. Now, it’s launching paid plans for all sorts of stuff.

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tech
Jon Keegan

FT: Anthropic staff helping the NSA use Mythos for offensive cyberattacks

Anthropic’s Mythos AI model was deemed too dangerous to release to the public, with the company citing its ability to orchestrate novel cyberattacks.

And that’s just what the National Security Agency is doing, with the help of Anthropic staff embedded at the agency, according to a report from the Financial Times.

Only a small number of companies and US allies have been given access to the advanced model, which means America’s adversaries have not had the chance to shore up their defenses against the AI model’s new offensive capabilities.

The arrangement is especially unusual as the Pentagon has deemed Anthropic’s AI a national security supply chain risk — effectively blacklisting it for defense work — in response to the company’s refusal to allow its technology to be used for any legal application, which could include autonomous killing or mass surveillance. Anthropic is currently suing the US government to fight the determination.

US National Security Agency using Anthropic’s Mythos for cyber attacks

US National Security Agency using Anthropic’s Mythos for cyber attacks

Only a small number of companies and US allies have been given access to the advanced model, which means America’s adversaries have not had the chance to shore up their defenses against the AI model’s new offensive capabilities.

The arrangement is especially unusual as the Pentagon has deemed Anthropic’s AI a national security supply chain risk — effectively blacklisting it for defense work — in response to the company’s refusal to allow its technology to be used for any legal application, which could include autonomous killing or mass surveillance. Anthropic is currently suing the US government to fight the determination.

tech
Rani Molla

Longtime Tesla bear JPMorgan upgraded Tesla and raised its price target to $475 from $145

For more than a decade, JPMorgan was Wall Street’s most stubborn Tesla skeptic, anchored by auto analyst Ryan Brinkman’s strict focus on traditional car fundamentals and near-term delivery numbers.

But JPM recently handed coverage of the stock to a new analyst, Rajat Gupta, who is throwing that playbook out the window. In a note Friday, the firm upgraded Tesla to “neutral” from “underweight” and raised its price target 228% to $475 from $145. (The analyst consensus on FactSet is $403.) Instead of focusing on the company’s struggling vehicle business, the new analyst is orienting himself more toward Tesla’s idea of the future, now modeling Tesla’s physical AI and robotaxi fleets all the way out to the year 2040.

Here are the main reasons for the capitulation:

  • Looking past the car lot: Gupta argues that Tesla “is at the forefront of physical AI, entering uncharted TAMs” and therefore “deserves the benefit of the doubt to be valued on LT earnings potential” rather than near-term speed bumps.

  • Unmatched vertical integration: Tesla’s control over everything from battery cells to custom silicon gives it a massive moat. JPM notes this starting point advantage is “unmatched at an industrial level scale” and “still somewhat under-appreciated and misunderstood.”

  • The AWS flywheel effect: Deploying Optimus robots inside its own factories “should not only lower COGS for the base automotive business, but more importantly, help validate the product at an industrial scale.” Gupta called it “a classic flywheel effect, somewhat analogous to AWS and Kiva at AMZN.”

For Tesla bulls who have argued for years that this is an AI company and not a carmaker, JPM’s sudden $3.9 trillion valuation model is the ultimate validation.

skynet terminator

Anthropic ponders self-improving AI

Anthropic says Claude already writes 80% of its code. A new post asks what happens when the models can improve themselves — and whether anyone could stop them.

Jon Keegan6/5/26

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