The gap between AI insiders and everyone else is widening, and the spending, suspicion, and even new vocabulary are starting to show it. While OpenAI is busy buying up everything from finance apps to talk shows, a certain shoe company just rebranded as an AI infrastructure play, and Anthropic unveiled a model it says is too powerful to release publicly ...but apparently not too powerful to demo to Federal Reserve Chair Jerome Powell. 

On this episode of TechCrunch's Equity podcast, Kirsten Korosec, Anthony Ha, and Sean O'Kane dig into what's actually being built in AI infrastructure, who's winning the enterprise battle between OpenAI and Anthropic, and more of the week's headlines. 

Listen to the full episode to hear about: 

Why chipmakers AMD, Arm, and Qualcomm just piled $60M into UK self-driving startup Wayve, and what Uber's $300M milestone bid says about who's winning the AV race 

How data center startup Fluidstack is positioning itself for the frontier labs, including a reported $50B agreement with Anthropic 

What Claude Code's moment at the HumanX conference reveals about where the OpenAI vs. Anthropic rivalry is actually playing out 

Why tokenmaxxing, and Meta's leaked internal leaderboard, might say more about optics than actual productivity 

Subscribe to Equity on YouTube, Apple Podcasts, Overcast, Spotify and all the casts. You also can follow Equity on X and Threads, at @EquityPod. 

Chapters: 

00:00 Intro 

00:25 Allbirds is now an AI company, apparently 

04:48 Why chipmakers are betting on Wayve 

12:01 Fluidstack wants $1B to build AI data centers 

16:24 OpenAI buys a finance app and a talk show 

21:27 Anthropic vs. OpenAI in enterprise 

24:15 The Anthropic model they won't release to the public 

26:47 Why AI feels so distant to everyone else 

30:47 What even is tokenmaxxing? 

34:49 Parasail's $32M bet on cheaper AI inference 

36:39 Outro 

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When Grammy-nominated singer-songwriter Aloe Blacc got COVID despite being vaccinated and boosted, he tried to fund research for a better solution. What he quickly found out? You can't just write a check in biotech. Regulators require a commercialization plan, and philanthropy doesn't move science through clinical trials or get you a license on university IP. Now, he's bootstrapping a cancer drug platform targeting pancreatic cancer, a disease that kills 90% of its patients, and intentionally waiting to raise from his network until peer-reviewed papers can make his case. 

On this episode of TechCrunch's Equity podcast, Rebecca Bellan sits down with Aloe Blacc to talk about what happens when a creator decides to build instead of just invest, how Aloe is watching AI reshape both the biotech and music industries in real time, and his thoughts on who actually wins. 

Listen to the full episode to hear: 

How he’s navigating a world where credibility is earned in data, not fame 

How a University of Houston molecule discovery platform could cut years off drug development timelines 

Why he thinks record labels, not artists or AI companies, will ultimately control the economics of AI-generated music 

What Suno taught him about prototyping, and why his next album will still be recorded with live musicians 

Subscribe to Equity on YouTube, Apple Podcasts, Overcast, Spotify and all the casts. You also can follow Equity on X and Threads, at @EquityPod. 

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LLMs may have kicked off this AI boom, but the ceiling is closer than the hype suggests. As models run out of text data to train on, the companies and investors paying attention are already moving on. The next wave isn't better chatbots; it's machines that can understand the physical world. Luma AI, the Bay Area lab that raised over $1.4 billion from a16z, Nvidia, and Amazon, is betting on exactly that. 

On episode of TechCrunch's Equity podcast, we’re bringing you a conversation Rebecca Bellan sat down with Amit Jain, co-founder and CEO of Luma AI, at Web Summit Qatar. Together, the pair dug into where the next trillion-dollar AI opportunity actually gets built, and whether the companies chasing it even know what they're building yet. 

Listen to the full episode to hear about: 

Why video, audio, and images are the real frontier for AI training data, not text 

What an "intelligent world model" actually is, and why Jain thinks most companies building them are getting it completely wrong 

The case for why AI won't kill creative jobs, and why Jain thinks studio heads are the real problem 

How the path from video generation to robotics to AGI is simpler than anyone's making it sound 

Subscribe to Equity on YouTube, Apple Podcasts, Overcast, Spotify and all the casts. You also can follow Equity on X and Threads, at @EquityPod. 

Chapters: 

00:00 Intro 

01:13 Why LLMs are hitting a ceiling 

02:43 The data problem & what comes after LLMs 

04:30 What actually makes a world model a world model 

06:05 Why 3D data is a dead end 

07:39 What Luma is building next 

09:08 How much humans stay in the loop 

10:00 Near-term use cases for agentic video 

11:22 Will AI kill jobs in film & production? 

13:30 Why the entertainment industry is already dying 

15:27 Why we actually need more content, not less 

17:46 Luma's roadmap: generation, understanding, and robotics 

19:54 Outro 

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Snowflake is betting that the future of AI isn’t just analyzing data, it’s acting on it. That means a shift away from chatbots and toward autonomous agents that can actually get work done. And Snowflake is reorganizing fast to keep up, from shipping hundreds of AI features to restructuring teams along the way.
On this episode of TechCrunch’s Equity podcast, Rebecca Bellan sits down with Snowflake CEO Sridhar Ramaswamy to unpack the company’s transformation and what it signals about where AI is headed next.

Listen to the full episode to hear:

Subscribe to Equity on ⁠YouTube⁠,⁠ Apple Podcasts⁠,⁠ Overcast⁠,⁠ Spotify⁠ and all the casts. You also can follow Equity on⁠ X⁠ and⁠ Threads⁠, at @EquityPod. 

Chapters:

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Tech companies are racing to build data centers in space, pitching orbital compute as the next frontier for AI infrastructure, even as the technical and economic realities remain far from clear. Add in OpenAI’s massive $122 billion round and Bluesky’s latest AI backlash, and the message is clear: The future of AI is being shaped as much by ambition and hype as it is by real-world constraints. 

On this episode of TechCrunch’s Equity podcast, Kirsten Korosec, Anthony Ha, and Sean O’Kane unpack these massive capital bets, user backlash, and off-world compute plans along with Whoop’s major valuation and the literal downfall of robot Olaf.  

Listen to the full episode to hear about: 

OpenAI’s $122 billion fundraise and what its near-trillion-dollar valuation says about expectations for AI.  

Whoop’s $575 million raise and the shift toward “wearables 2.0” (and what happens to all that data).  

Bluesky’s AI-powered feed builder and why it triggered a major user backlash.  

The rise of data centers in space and whether they are financially or physically feasible.  

Subscribe to Equity on YouTube, Apple Podcasts, Overcast, Spotify, and all the casts. You also can follow Equity on X and Threads, at @EquityPod. 

Chapters: 
00:00 Intro 
00:20 A humanoid Olaf robot collapses at Disneyland Paris 
03:30 OpenAI raises $122B at an $852B valuation 
11:30 Whoop lands $575M and bets big on wearable data 

18:50 The risks (and value) of personal health data 
23:00 Bluesky’s AI feed builder sparks backlash 
30:00 Can Bluesky keep growing — and compete with X? 
36:30 The race to build data centers in space 
44:30 SpaceX, Starlink, and the business of orbital compute 
49:30 Outro 

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The VC middleman is getting cut out faster than anyone expected. Family offices and private wealth firms are going direct: writing checks, taking board seats, even incubating companies from scratch. And more founders are starting to notice. In February alone, family offices made 41 direct investments, including one Midwest-based firm that led a $230 million Series B into an AI chip startup. 

On this episode of TechCrunch's Equity podcast, Rebecca Bellan caught up with Mitch Stein and Ari Schottenstein, founder and head of alternatives at ARENA Private Wealth, to find out what this shift means for founders, cap tables, and the future of AI investment. 

Listen to the full episode to hear: 

How Arena landed the lead on Positron's $230 million Series B, and why the CEO specifically wanted them on his cap table 

How Arena does due diligence on technical companies 

What "tourist capital" actually looks like, and the red flags founders should watch for as family offices flood into AI deals 

Why some VCs are quietly unhappy about this trend (and why Arena thinks that's their problem) 

Subscribe to Equity on YouTube, Apple Podcasts, Overcast, Spotify and all the casts. You also can follow Equity on X and Threads, at @EquityPod. 

Chapters: 

00:00 Intro  

03:13 Why family offices are going direct now 

06:03 The gen 2 & gen 3 family office shift 

07:22 Is this strategic or just AI FOMO? 

10:17 How Arena got into the Positron deal 

14:30 Why founders want private wealth on their cap table 

18:31 Due diligence on technical companies 

21:56 Red flags founders should watch for 

25:04 Are VCs threatened by this trend? 

27:47 Taking board seats & level of involvement 

34:17 Outro 

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When an 82-year-old Kentucky woman was offered $26 million from an AI company that wanted to build a data center on her land, she said no. Sure, that same company can try to rezone 2,000 acres nearby anyway, but as AI infrastructure stretches further into the real world, the real world is starting to push back. 

That tension is everywhere this week, from OpenAI shutting down its Sora app to courts finally starting to hold social platforms accountable. On this episode of TechCrunch's Equity podcast, Kirsten Korosec, Anthony Ha, and Sean O'Kane dig into what it looks like when the AI hype cycle meets reality. 

Listen to the full episode to hear about: 

Why rival prediction market CEOs of Kalshi and Polymarket are co-investing in a $35M VC fund 

How drone startups like Zipline, Lucid Bots, and Brinc are finding real traction where other robotics plays have stalled 

What Kleiner Perkins' $3.5B raise says about where the biggest VC firms think the next AI wave is going 

Why two separate court verdicts against Meta in the same week could be the “tobacco moment” for social media 

Subscribe to Equity on YouTube, Apple Podcasts, Overcast, Spotify and all the casts. You also can follow Equity on X and Threads, at @EquityPod. 

Chapters: 

00:00 Intro 

00:30 Would you turn down $26M for your farm? 

03:56 Rivals Kalshi & Polymarket CEOs are investing together 

10:28 Deals for drones: Zipline, Brinc & Lucid Bots 

18:17 Kleiner Perkins goes all-in on AI with $3.5B raise 

22:52 OpenAI shuts down Sora 

28:04 Meta gets hit with dual verdicts 

34:56 Outro 

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Over the past few years, a new category of mobile apps has quietly exploded into a multi-billion dollar business. They're called “micro dramas” — short-form, mobile-first scripted shows designed to be watched vertically on your phone. Think soap opera meets TikTok, complete with secret billionaire romances, disapproving werewolf mothers-in-law, and cliffhangers engineered to keep users tapping. The leading app, ReelShort, made $1.2 billion in consumer spending last year alone.  

On this episode of TechCrunch's Equity podcast, Rebecca Bellan and TechCrunch senior reporter Amanda Silberling sit down with Henry Soong, founder of Watch Club, who thinks the micro drama industry is still "in its MySpace era." He has a vision for what the Facebook moment could look like. 
 
Listen to the full episode to hear: 

Why micro dramas took off in China while Quibi burned through $2 billion and failed in the U.S., and what that gap reveals about content, product, and business model. 

How Watch Club is targeting a completely different audience than ReelShort and Drama Box. 

The tension between building an intentional social experience and optimizing for engagement the way TikTok does. 

Whether AI is coming for the werewolf billionaire romance script. Amanda has thoughts.  

Subscribe to Equity on YouTube, Apple Podcasts, Overcast, Spotify and all the casts. You also can follow Equity on X and Threads, at @EquityPod. 

Chapters: 

00:00 Intro 

01:11 Why micro dramas, and why now? 

04:25 What makes Watch Club different 

07:29 The monetization model problem 

18:52 Optimizing for intentionality, not engagement 

24:23 Why Quibby failed (content, product & business model) 

28:22 Defensibility: tech company or studio? 

31:36 AI, the WGA, and the future of storytelling 

33:44 Outro 

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Jensen Huang took the stage at Nvidia's GTC conference this week in his signature leather jacket to deliver a two-and-a-half-hour keynote, projecting $1 trillion in AI chip sales through 2027, declaring that every company needs an “OpenClaw strategy,” and closing with a rambling Olaf robot that had to get its mic cut. The message was hard to miss: Nvidia wants to be foundational to everything, from AI training to autonomous vehicles to Disney parks. 

On this episode of TechCrunch's Equity podcast, Kirsten Korosec, Anthony Ha, and Sean O'Kane break down what Nvidia's growing web of AI infrastructure partnerships actually means for startups, and more of the week's headlines. 

Listen to the full episode to hear about: 

Travis Kalanick’s return building a "wheelbase for robots" with his new startup Atoms, and the crew has questions about Kalanick’s acquisitions along the way 

Rivian’s partnership with Uber to build robotaxi versions of its R2 in a deal worth up to $1.25 billion, while pushing back its EBITDA target to do it 

Frore landing a $1.64 billion valuation for its AI chip cooling systems 

xAI rebooting, again, with only two of its original eleven co-founders still standing 

Garry Tan's Claude Code setup went viral at SXSW (Spoiler: the crew is not impressed). 

Subscribe to Equity on YouTube, Apple Podcasts, Overcast, Spotify and all the casts. You also can follow Equity on X and Threads, at @EquityPod. 

Chapters: 

00:00 Intro 

00:20 Garry Tan's Claude Code setup goes viral at SXSW 

03:37 Travis Kalanick is back with a new startup 

12:51 Uber and Rivian's $1.25B RoboTaxi deal 

20:54 Chip cooling startup Frore becomes a unicorn 

22:56 Nvidia GTC recap: $1 trillion in sales projections 

31:42 Elon Musk is rebooting xAI...again 

36:37 Outro 

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Artificial intelligence models are multiplying fast, and competition is stiff. With so many players crowding the space, which one will be the best — and who decides that? Arena, formerly LM Arena, has emerged as the de facto public leaderboard for frontier LLMs, influencing funding, launches, and PR cycles. In just seven months, the startup went from a UC Berkeley PhD research project to being valued at $1.7 billion. 

On this episode of TechCrunch's Equity podcast, Rebecca Bellan catches up with Arena co-founders Anastasios Angelopoulos and Wei-Lin Chiang to determine how a team like theirs can build a neutral benchmark when the companies they’re ranking are also their backers. 

Listen to the full episode to hear: 

How Arena actually works, and why its founders say you can't game it the way you mighta static benchmark. 

What "structural neutrality" actually means, and whether taking money from OpenAI, Google, and Anthropic is a conflict of interest. 

How Arena is moving beyond chat to benchmark agents, coding, and real-world tasks with a new enterprise product. 

Why Claude is currently winning the expert leaderboard for legal and medical use cases. 

Arena's bet on what comes after LLMs, and why agents are next on the leaderboard. 

Subscribe to Equity on YouTube, Apple Podcasts, Overcast, Spotify and all the casts. You also can follow Equity on X and Threads, at @EquityPod. 

Chapters: 

00:00 Intro 

03:00 How Arena's leaderboard works, and why it's different from static benchmarks 

07:00 Reproducibility concerns and how to scale 

08:45 Can Arena stay independent while taking money from the labs it ranks? 

11:15 Diversity, fraud prevention, and abuse mitigation 

18:15 Arena's "data moat" 

19:20 Agent benchmarking and expert leaderboards 

21:40 Open sourcing data 

22:45 How do Arena's rankings shape AI development? 

24:15 Outro 

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