Speaker 1: AI daily briefing. I made sharp thanks for joining me
Speaker 1: today the four hundred and twelve billion dollars AI bubble
Speaker 1: when mega rounds hired a smaller market, four hundred and
Speaker 1: twelve billion dollars flowed into US South venture capital in
Speaker 1: the first half of this year. That number sounds like
Speaker 1: a boon. The reality underneath it is more complicated. Eighty
Speaker 1: six percent of that capital, roughly three hundred and fifty
Speaker 1: six billion dollars went to AI. But strip away the
Speaker 1: mega rounds and the picture shifts fast. Deals below one
Speaker 1: hundred million dollars now account for just twelve and a
Speaker 1: half percent of total venture value. Two years ago, that
Speaker 1: figure was forty three point eight percent. The market hasn't
Speaker 1: expanded broadly. It's concentrated sharply. A small number of very
Speaker 1: large bets are inflating the headline number, while the broader
Speaker 1: startup ecosystem quietly shrinks as a share of deployed capital.
Speaker 1: That's the signal here, not the total the distribution. The
Speaker 1: clearest example of that concentration sits at the top of
Speaker 1: the frontier lab race. Anthropic just closed a sixty five
Speaker 1: billion dollar funding round at a post money valuation of
Speaker 1: nine hundred and sixty five billion dollars three months ago,
Speaker 1: its pre money valuation was three hundred and fifty billion.
Speaker 1: That's one hundred and fifty seven percent step up in
Speaker 1: a quarter. The important distinction is that this now puts
Speaker 1: Anthipic ahead of Open AI by valuation. Both companies have
Speaker 1: filed confidentially to go public. What that means in practice
Speaker 1: is that the race to a trillion dollar AI lab
Speaker 1: valuation isn't herpathetical anymore. It's a matter of timing. The
Speaker 1: unresolved question is whether the underlying revenue justifies these numbers,
Speaker 1: or whether the valuation is pricing in AGI outcomes that
Speaker 1: haven't materialized yet. While capital concentrates in the US, South
Speaker 1: Europe is tightening the rules on how that capital gets deployed.
Speaker 1: On July eighth, the EU Data Protection Board adopted Guidelines
Speaker 1: zero three slash twenty twenty six. These aren't voluntary commitments,
Speaker 1: they're an enforceable pan EU framework, requiring legal US view
Speaker 1: before any scraping begins, data minimization at the point of collection,
Speaker 1: and special handling for sensitive category DTA in training sets.
Speaker 1: The catch that matters most the guidelines don't grandfather existing
Speaker 1: data sets. Developers who collected training data between twenty twenty
Speaker 1: three and twenty twenty five now face retroactive scrutiny under
Speaker 1: the current balancing test. Most large language models weren't built
Speaker 1: with that standard in mind. Compliance teams at Frontier Lapse
Speaker 1: are now working backwards through data sets that were never
Speaker 1: designed to be audited this way. That's not a theoretical risk,
Speaker 1: it's an immediate operational burden. Here's the thing. The geographic
Speaker 1: story of AI is also shifting. More than thirty founding
Speaker 1: teams have relocated from Asia to the US South via
Speaker 1: Antler since twenty twenty five. Asia's share of global venture
Speaker 1: capital dropped to nine point six percent in the first
Speaker 1: quarter of this year. The US self holds eighty percent.
Speaker 1: Southeast Asian funding has collapsed from ten point one billion
Speaker 1: dollars in twenty twenty two to two point two billion
Speaker 1: in twenty twenty four. That's an eighty percent decline. The
Speaker 1: incentive structure is straightforward, fragmented regulatory environments, limited exit opportunities,
Speaker 1: and a customer base that doesn't scale the way Silicon
Speaker 1: Valley does. Founders are voting with their feet. The visa
Speaker 1: picture adds friction, but a court block in July ruled
Speaker 1: unauthorized the recent fee hike that had pushed h one
Speaker 1: B costs toward one hundred thousand dollars. Mercor, the ar
Speaker 1: unicorn that hit two billion dollars in annual recurring revenue
Speaker 1: in June, acquired simulation platform depect Tune. The strategic logic
Speaker 1: is direct. The merkll brings five million domain experts. Depectune
Speaker 1: brings enterprise software environments where AI agents can train on
Speaker 1: tools like Salesforce, Slack, and Excel before touching production systems. Together,
Speaker 1: its full stack reinforcement learning infrastructure for frontier labs building agents.
Speaker 1: Mercor doubled its arr in twelve months. The d chap
Speaker 1: to acquisition is a bet that agent training infrastructure becomes
Speaker 1: the next critical layer. The final thread worth tracking is infrastructure.
Speaker 1: Asian investors are pivoting away from growth at all costs
Speaker 1: AI toward what they're calling resilient AI. Capitalists flow into
Speaker 1: liquid coaling, small modular reactors, and edge computing. The power
Speaker 1: and thermal constraints of running large AI systems are no
Speaker 1: longer secondary concerns. They're becoming the primary bottlemech. This isn't
Speaker 1: just an Asian story. It's an early signal of where
Speaker 1: the global infrastructure conversation is heading. Consider this. The near
Speaker 1: term watch points are clear. Watch whether anthropics valuation holds
Speaker 1: as public market scrutiny approaches. Watch how EU regulators begin
Speaker 1: enforcing the new scraping guidelines against non compliant training data sets.
Speaker 1: And watch whether the concentration in venture funding accelerates further
Speaker 1: or triggers the correction that some analysts are already modeling.
Speaker 1: The headline number is four hundred and twelve billion. The
Speaker 1: real story is who's capturing it and who isn't. Thanks
Speaker 1: for listening. This podcast was built using AI technology, a
Speaker 1: Yes We production