"I thought the alignment problem would turn out to be harder." Pretty wild thing for Sam Altman to say in light of Hugging Face and findings that Astra would totally hack and social engineer when accidentally given access to a (secretly simulated internet) from UK AISI. He caveats by saying it will probably get harder, but his answer suggests they have figured out how to align today's models, when that's clearly not true. Curious how many OpenAI researchers have seen this and what they think.

Bloomberg: "Early signs suggest that the credit market is approaching the limits of how much more debt it can absorb. One after another, yields are soaring into the double digits on bonds and loans funding the AI infrastructure buildout. Bankers are finding it more difficult to offload risk to insurers and other investors...With those jitters growing louder each week — and spurring, in turn, angst about the potential economic fallout — Citadel Securities is cautioning clients that even the biggest names in tech could get ensnared as they put their balance sheets behind scores of projects critical to their AI ambitions." Years ago, I was debating the implications of the COVID outbreak with a client at 13D and I was expressed concerns about debt sustainability when he told me: "Never underestimate how much money there is in the world." That's stuck with me since and puts into perspective the extraordinary scale of AI buildout ambitions, which are running into the limits of what capital markets can provide. As I warned in my September report on "The AI Trade" ( "In the first five months of this year, Alphabet, Amazon, Microsoft, Meta, and Oracle borrowed as much as they had in the five years prior. Morgan Stanely expects AI-related debt issuance to top $570 billion this year, more than double any previous record. Just for a bit more context about the scale of the borrowing binge, here’s an FT recap of Goldman analysis: 'The numbers are just bonkers. Goldman Sachs said in a note earlier this month that US dollar investment-grade issuance had already exceeded $1.5 trillion so far this year, which put 2026 on track to beat the previous record-breaking blowout from the pandemic era. The bank had previously penciled in a total of $2.1 trillion for the whole of this year but now it thinks that may be looking too cautious. The average deal size is $1.7 billion, the biggest in the post-crisis era. This includes at least 20 deals at $10 billion or more at announcement—a size it describes as “jumbo”. (I’m old enough to remember when “jumbo” transactions were $1 billion or more, so thank you Goldman for making me feel ancient.) In the whole of 2025, there were just 12 deals on this scale and from 2022 to 2024, there were 15 in total.' Market participants remain complacent about tech giants continuing to borrow at the rate they’re borrowing if borrowing costs keep rising. And if tech giants begin to pull back from the debt binge, it’ll ripple far beyond the bond market, through to everything from equities to consumer spending."

Hilariously, OpenAI’s galactic algorithm for resolving the Exponential Time Hypothesis runs an exponential-time subroutine if the number of variables is less than 10^10,000,000,000,000,000,000,000,000. That number is also known as infinity plus 1.

META may be new to the negative cash flow club, but not GOOGL: free cash flow was negative for a second straight quarter, -$9.1bn vs -$3.5bn consensus. Trailing-12-month FCF collapsed 73% to $19.7bn, from $73.6bn a year ago.

15/16 also, don't confuse exposure with failure. anthropic had $16.3b of first-half revenue; compute expense was 55% of sales versus 201% a year earlier. the core question is whether demand keeps outgrowing committed cost.