Japan’s startup scene grows up

Japan’s startup market shows its new weight

A pair of deals just rewired the mood in Tokyo’s tech scene.

General Atlantic dropped $96 million into Smart HR, its first growth bet in Japan, and the move let Coral Capital return an old fund six times over while still holding stock. That kind of exit, the biggest secondary sale from a single seller in Japan, is rare in a market long dominated by corporate giants.

Sakana AI then raised $128 million at a $2.6 billion valuation, nearly doubling its price from 2024 and setting a record for a private Japanese startup. The round included names like Nvidia and NEA, a signal that global money is treating Japan less like a side quest and more like a center lane.

Momentum tends to attract more momentum, and other startups like Turing are pulling in nine figure checks as investors hunt for the next breakout. The ecosystem finally feels noisy in a good way, like a train platform just before the last Shinkansen of the night.

Something bigger is starting to hum.

AI pushes higher ed into a new corner

Students moved fast.

Three years after ChatGPT’s debut, its glow fills lecture halls, dorm rooms, and late night labs where keyboards tap past midnight. Colleges now face a tool that works as study partner, research engine, and yes, a shortcut that can slip past old guardrails.

The shift is messy and it is testing assumptions about what learning looks like when a model can produce a clean outline in under ten seconds. Some faculty see opportunity in that speed, while others feel the floor tilt under them as they try to redesign assignments that once felt sturdy.

Policies are spreading across campuses, and the first wave of AI centered courses is arriving with uneven confidence. The ripple is cultural too, because students who grew up with auto save and shared docs now expect AI to act as infrastructure rather than exception.

Still, one late night question lingers for teachers staring at a half graded PDF. What comes next when the ground keeps moving

AI’s market run rests on real numbers

Investors keep asking the same question. Bubble or not.

Tech stocks trade around 30 times forward earnings, which is lofty but nowhere near the 55 times peak before the dot-com crash, and today’s leaders are flush with cash and funding their AI buildout from their own balance sheets. That matters because global data center demand is climbing fast, roughly 19 to 22 percent a year through 2030, and Q2 data showed AI spending adding more than a full point to U.S. GDP.

Most investors are still cautious, pulling about $45 billion from equity funds this year while tech funds saw a mild $14 billion of inflows. That restraint shows up in advisor portfolios too, where average tech exposure sits at 25.5 percent, well below the S&P 500’s weight.

The gap creates room for strategies like BAI or DYNF to slot in, especially for clients who want AI upside without swinging their entire portfolio. You can almost hear the hum of servers rising as the next capital cycle builds.

Something in this expansion still feels unfinished.

Prohuman team

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