Cassidy: Compute deals keep getting bigger—and AI has wandered into a risk category where you don’t get to ship a hotfix.
Bill: This is AI Daily Briefing.
Bill: A cloud bill, Amazon’s private AGI build, and a lab result that should make everyone sit up.
Cassidy: First up: who’s paying for all this compute—and what happens when the output can’t be recalled?
Bill: Tap follow so the next episode finds you.
Cassidy: From Rebecca Bellan at TechCrunch:
Quote: The deal is worth upward of $100 million, Mirendil’s co-founder and CEO, Behnam Neyshabur, told TechCrunch.
Quote: That’s roughly half of what Mirendil raised in seed funding at a $1 billion valuation in late June.
Quote: The deal gives the startup access to both Google’s TPUs and Nvidia GPUs
Quote: as well as managed training clusters with which Mirendil will work on its self-improving AI.
Bill: Mirendil raised about $200 million in June, and now it’s committing upward of $100 million to Google Cloud.
Bill: Half that seed round is effectively already spoken for by one vendor, before there’s a production system to price.
Cassidy: And Google gets to sell it TPUs, Nvidia GPUs, and managed training clusters—the whole stack.
Cassidy: At that point, the cloud provider isn’t just selling capacity; it’s part of the lab’s operating model.
Bill: Self-improving AI gets expensive fast when every iteration burns rented compute.
Bill: I’d love to see the unit economics for a system that’s supposed to improve itself while its cloud bill starts north of a hundred million
Bill: dollars.
Cassidy: Mirendil’s founders came from Anthropic, so the ambition is familiar: automate pieces of frontier research.
Cassidy: For now, though, Google Cloud has a very large claim on a seed-stage lab’s balance sheet.
Cassidy: The Economic Times writes:
Quote: Microsoft launched its largest India data center in Hyderabad on Thursday.
Quote: This new facility brings Microsoft's cloud regions in India to four.
Quote: Adani Group and HDFC Bank are among the early users of this new center.
Quote: Microsoft has committed $20.5 billion to expand its India operations.
Quote: Rivals Alphabet and Amazon are also investing in India's data center capacity.
Cassidy: Microsoft’s Hyderabad region is live: three availability zones, plus local residency for workloads banks can’t toss overseas.
Cassidy: Early users include Adani Group, Bajaj Finance, and HDFC Bank—regulated customers with very unglamorous reasons to care.
Bill: That’s a better sign than another capacity rendering.
Bill: HDFC Bank using a local region for continuity and compliance may not make a killer demo
Bill: but it’s how a $20.5 billion commitment starts finding a revenue path.
Cassidy: Four Indian cloud regions, plus two data centers with Jio, gives Microsoft a serious local footprint.
Cassidy: What matters is who can keep the data, the fine-tuning, and the serving stack inside the customer’s compliance boundary.
Bill: Sure—but I want the next update to be utilization, not another map pin.
Bill: Adani and HDFC are named customers; now show us what they’re running, what it costs, and whether those three Hyderabad zones stay busy.
Cassidy: Eugene Kim, writing in Business Insider:
Quote: Amazon is redesigning part of a massive AI data center campus in rural Indiana into a sprawling cluster of powerful computers to build its
Quote: next frontier AI models
Quote: Business Insider has exclusively learned.
Quote: Internal planning documents reviewed by Business Insider describe an effort to consolidate multiple data centers and deploy thousands of
Quote: Trainium-powered AI servers.
Quote: According to people familiar with the matter
Quote: the effort is part of a broader initiative called "AGI Pivot" supporting the company's AGI organization and its future in-house AI models.
Bill: Amazon is redesigning a rural Indiana campus mid-build around thousands of Trainium servers for an internal program literally called AGI
Bill: Pivot. AWS clearly doesn’t want its frontier-model future priced by Nvidia.
Cassidy: Business Insider’s internal documents show Amazon consolidating data centers for its own AGI organization.
Cassidy: It’s taking control of what runs, where it runs, and whose silicon it runs on.
Bill: Trainium can be a cost play and a supply-chain hedge at once.
Bill: Consolidating multiple facilities says Amazon thinks the scheduling and networking gains outweigh the pain of redesigning a giant campus.
Bill: That’s a serious architectural bet.
Cassidy: Mirendil just committed upward of $100 million to Google Cloud.
Cassidy: Amazon’s response: fine, we’ll be our own cloud customer.
Cassidy: Different balance sheet, same fight for control of the inference stack.
Cassidy: Scientific American, with Adam Kovac:
Quote: Scientists used artificial intelligence to generate new viruses.
Quote: The landmark first could lead to new antimicrobial drugs—and may pose immense danger to human health.
Quote: Scientists at Stanford University and the Arc Institute
Quote: a nonprofit AI and biology research organization
Quote: made the viruses using the actual genome of a bacteriophage—a type of virus that can kill bacteria—called ΦX174 (pronounced FYE-ex-174) as a
Quote: template.
Bill: Stanford and Arc used models trained on more than two million bacteriophage genomes
Bill: then produced viruses that kill antibiotic-resistant bacteria.
Bill: Once those viruses are produced, there’s no hotfix to pull them back.
Cassidy: And ΦX174 was the template here—a bacteriophage
Cassidy: not a human virus—but Scientific American is right to put the misuse concern in the headline.
Cassidy: Evo 2 can suggest entirely new genome designs.
Bill: The therapeutic upside is real; antibiotic-resistant infections need better tools.
Bill: But in software, we ask what happens when something works in the wrong context.
Bill: Here, the paper’s successful lab result is the warning label.
Cassidy: Congress already bundles model safety, misinformation, and biosecurity into one convenient fog bank.
Cassidy: Add AI-generated pathogens to that hearing-room soup, and watch them demand rules for three different problems with one slogan.
Cassidy: Here's Cha Min-ju at The Herald Business:
Quote: NHN Cloud is pushing into large-scale AI infrastructure with NHN Factory X Seoul
Quote: an AI data center in Yeongdeungpo-gu equipped with liquid cooling technology.
Quote: As AI adoption has made heat management in high-performance GPUs a central challenge
Quote: the company is betting its proven operational capabilities will help it win market share.
Bill: Seven thousand, six hundred fifty-six B200s in Seoul, with direct liquid cooling holding each server to 12.3 kilowatts.
Bill: Good—now we’re talking about the constraint that decides whether all those GPU promises actually run flat-out.
Cassidy: NHN is running its own stack, not renting someone else’s cloud logo.
Cassidy: Factory X is 5.7 times larger than its Gwangju site; this is a regional operator making a very specific bid for control.
Bill: Water cooling isn’t glamorous
Bill: but a B200 cluster that can sustain performance without turning the room into a jet engine is a better enterprise story than another glossy
Bill: model demo. The private-market push still has to earn its keep—but this is actual hardware, actually installed.
Cassidy: For more on AI policy and defense
Cassidy: try Anthropic Pentagon Watch
Cassidy: a daily briefing on Anthropic’s fight with the DoD over Claude
Cassidy: military AI use autonomous weapons
Cassidy: and AI procurement blacklisting.
Cassidy: Find it wherever you listen to podcasts.
Cassidy: Links to every story are in the show notes.
Cassidy: If one caught your attention, go read more when you have a minute.
Cassidy: That’s AI Daily Briefing for today.
Cassidy: This is a Lantern Podcast.