The EU has just hit pause on its own AI Act, and the entire compliance map for 2027 is now up in the air.

Before that, Google's Athletica just cracked math problems that no human had solved.

OpenEI's CFO is reportedly at war with Sam Altman over $660 billion in compute spending,

and Big Tech earnings week kicks off tomorrow.

So there's a whole bunch of questions that are going to be hanging around over AI and ROI that

we're going to be covering. Let's get into it. So first I wanted to talk about Google deep mind.

They've just dropped Athletica this week. This is an autonomous math agent. And it's actually just

built on top of Gemini

3 deep think and the results that it has been producing are really wild. So on the first

proof challenge, which is basically a benchmark of unsolved or really complex kind of novel

math problems, Athletica actually produced solutions that according to human expert

evaluators were graded as, quote, publishable after minor revisions, meaning like it basically got

it there. There might been a couple tweaks, but I mean, it solved these really complex math

things to a high level, which was basically ready to get published. And it actually did this on

six out of ten questions that it was given.

It also scored above 91.9% on the IMO proof benchmark. And J. Midha at A16Z called it the moment,

quote, AI math went from playing the game to writing the rules. I think that's kind of a fair

framing. Because up until this point with all of the

different AI models, proving these kind of novel theories is one of the hardest possible tests for

these AI agents. And Athletica just did it. Sony is also coming out swinging. So they have something

called Sony AI and they have a project called Ace and they just published on this their project that was

just published on the cover of nature, one of the, you know, top journals for science this month

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