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People have the AI bubble all wrong. It's not a technology bubble. It's a real estate bubble that rhymes more with the subprime mortgage crisis in 2008 than the dot-com boom. That's the takeaway from a post by Groundbreaker.

The gist:

"The market is pricing AI as a technology cycle when its actual anatomy is that of a credit-driven real estate cycle - which is precisely why the 2008 mechanics apply - and the two break for entirely different reasons.

Technology cycles are driven by innovation and adoption; their risks are obsolescence and competition; they live or die on whether the product is wanted, and they can de-rate slowly as the future is repriced.

Real estate cycles are mechanical: leverage, hard assets, occupancy - debt-financed construction at scale, commercial leases disguised as take-or-pay contracts, and long construction lags that guarantee supply arrives after demand has turned. Walk down the AI build-out and every feature is a property development in disguise: a data center on entitled land, financed with debt against the structure and leased to tenants on take-or-pay terms."

Hat tip to Wall Street money manager George Noble for flagging the Groundbreaker post.


Anthropic posted interesting research on J-space, a set of neutral patterns in Claude that reveals internal thoughts. J-space wasn't programmed, but has emerged.

"We present evidence that a similar distinction has emerged in modern language models like Claude. We find that Claude has developed a small collection of internal neural patterns that, compared to all its other internal processing, play a special role...

We call the collection of these patterns the J-space—named after the technique we used to find them, involving a mathematical concept called the Jacobian. Each J-space pattern is linked to a particular word. But when one of these patterns lights up, it doesn’t mean the model is saying that word—just that the word is on its mind. If you've heard of language models having a "scratchpad" or “chain of thought”—text they write to themselves while reasoning—the J-space is something different. It operates silently, in the model’s internal neural activations, allowing the model to think about a concept without writing it down. Notably, the J-space wasn’t designed or programmed by us, but instead emerged on its own during Claude’s training process."

Netflix is reportedly studying data to see why viewers quit shows after the first season. Some shows see a 30% to 70% drop. I'll save Netflix some time on the data crunching.

1. There aren't a lot of shows that necessitate a long-term investment. Netflix is way mediocre.
2. The CX is terrible and if you can avoid Netflix you will.
3. Why is the CX so terrible? It's one thing to have to tell your credit card company when you're traveling. It's another to tell Netflix. The hurdles, CX loops and general pain with explaining how you may have a second home that shouldn't require a second subscription is getting to be a bit much.
4. Netflix raises its prices regularly so expectations have gone past the algorithmic slop the streaming provider offers.

So go ahead and study the data, the but the short answer for Netflix is it kinda sucks.

Microsoft said it is launching the Microsoft Frontier Company, a unit that will deliver AI transformation. The company said it is investing $2.5 billion in the new unit and embedding 6,000 industry and engineering experts.

In a statement, Microsoft said:

"This goes beyond what has been labeled as Forward Deployed Engineering (FDE) and will be the largest, most capable, outcome-driven engineering organization in the industry."

Microsoft's move comes after AWS launched a forward deployed engineering effort.