# AI Infrastructure Shifts: Memory Hardware, Capital, and Platform Pivots

**Podcast:** TechCrunch Daily Crunch
**Published:** 2026-05-30

## Transcript

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A chip startup just raised $135 million on a bet.
that AI's biggest bottleneck isn't a compute problem.
I'm Imran Sheik and your weekend edition of The Daily Crunch starts right now.
Anthropic has snagged $165 billion in funding at a $965 billion post-money valuation in its latest funding round, marking what could be the AI startup's last private fundraising before debuting on the public markets.
The Series 8 round was co-led by Altimeter Capital, Dragoneer, Green Oaks, Sequoia Capital, Capital Group, KOTU, D1 Capital Partners, and others.
Institutional investors including Bailey Gifford, Blackstone, Brookfield, D.E.
Shaw Ventures, DST Global, and Fidelity Management and Research participated in the round.
Strategic infrastructure partners including Samsung, SK Hynix, and Micron also joined the round.
A portion of the round, $15 billion, is also made up of previously committed investments from hyperscalers, including five billion billion from Amazon announced in April.
The hits just keep coming.
There's more AI news, folks.
Asana has acquired the workflow automation company Stack AI for $75 million, part of a larger effort to position itself as an AI-native workplace platform.
Stack AI's founders, Tony Rosenall and Bernard Essaytuno, will join Asana as part of the acquisition.
Asana framed the acquisition as part of its broader AI pivot, in which it seeks to build its platform into the operating system for human agent teams.
The announcement was made...
And finally, Did you know that every time you ask ChatGPT a question, your request triggers a data relay race?
Information leaves memory, passes through a CPU for pre-processing, travels to a GPU for heavy computation, and then makes its way back.
And that entire journey repeats for every single word the AI generates.
The bottleneck is structural.
It means routing through some of the most expensive and power-intensive chips in the industry on every single request.
That inefficiency is exactly what Exena, a startup with offices in South Korea and the U.S., is trying to solve.
The four-year-old startup has designed a chip that places compute capabilities much closer to DRAM, the fast, short-term memory chips that store data a processor is actively using, allowing routine data operations to be handled near memory without the costly round trips between CPUs, GPUs, and memory.
If it works at scale, the implications for AI infrastructure costs could be significant, which largely explains investor enthusiasm around the country.
Exena just raised $135 million in a Series B at a valuation of $570 million, bringing its total raised to $185 million.
Exena is betting its business on the thesis that inference isn't just a compute problem, it's increasingly a memory scaling problem.
And folks, that's your Daily Crunch.
Today's stories were reported by Kate Park, Rebecca Belon, and more awesome TechCrunch journalists.
We'll see you here next week, and until then, find us at TechCrunch.com.
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