Equity

Andreessen Horowitz has two partners sitting on the boards of companies that now compete with each other: Ben Horowitz at Databricks and Martin Casado at Fivetran. Nothing too scandalous on the surface, except the Department of Justice has reportedly been investigating the arrangement for almost a year, dusting off a 112-year-old antitrust law that's rarely used against VCs.

Board conflicts aren't exactly new, and these companies weren't necessarily direct competitors when a16z first invested in them. But as portfolio companies expand into each other's markets, the DOJ's scrutiny raises a much bigger question for venture firms: How do you manage board seats when the boundaries between your portfolio companies keep moving? On this episode of TechCrunch's Equity podcast, Kirsten Korosec, Anthony Ha, and Sean O'Kane dig into the a16z probe, what it could mean for VCs, and more of the week’s headlines.

Listen to the full episode to hear more about:

Why Stripe paid $7.5 billion for AI model router OpenRouter, and why the “singularity” isn't the real reason

What happens to the AI companies caught in the middle as OpenAI, Anthropic, and Nvidia pull further ahead

Why Rivian spinout Also just raised $150 million to make a bigger bet on autonomous vehicles

Uber’s newest delivery partnership with drone company Zipline, and what it means for the other autonomous startups betting their futures on Uber

Whether we've reached peak valuation for AI dictation apps after Wispr's $280 million raise at a $2 billion valuation

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

1:02 TechCrunch Disrupt and the Startup Battlefield 200

3:17 The DOJ is investigating a16z over board seats

14:47 Why Stripe just paid $7.5B for “the Stripe for AI”

18:18 The mid-tier AI scramble: gateways, pivots, and acquihires

23:17 Anthropic's revenue surges while OpenAI's losses deepen

27:08 Also raises $150M and drops the “micro mobility” label

32:30 Uber teams up with Zipline for drone delivery

37:19 Wispr hits a $2B valuation

38:26 Outro
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The AI buildout shows no signs of slowing. And with hundreds of billions of dollars a year going into data centers and GPUs, compute has become the single biggest cost for anyone building AI products. But for all that spending, there still isn’t a straightforward way to put a price on compute — or for firms to hedge their exposure when the price changes.

Silicon Data just closed a $30 million Series A to change that. The startup aims to become the reference price for GPU rental and an index that a Wall Street futures contract would settle against. The company plans to launch its compute futures trading on the CME October 5th, pending regulatory approval. On this episode of TechCrunch's Equity podcast, Rebecca Bellan is joined by Steve Hou, head of research at Silicon Data, to discuss the health of the AI buildout, and why the data is telling a different story than the doom and gloom headlines about depreciating chips and stalled data centers.

Listen to the full episode to hear more about:

What happens if OpenAI or Anthropic can’t make good on the massive compute commitments they’ve already promised, and whether “compute default” becomes a risk.

Why rental demand for older A100 chips is holding up, even as newer and more powerful GPUs hit the market.

If compute futures could make it easier for neo-clouds to finance expensive data centers by locking in future rental revenue.

What rising GPU rental rates across every contract length since March say about AI demand.

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

0:59 Futures contracts explained

4:01 Can GPU compute actually be a commodity?

7:10 Who's really trading these: hyperscalers, AI labs, and market makers

14:32 Locking in prices to make data center debt easier to swallow

18:21 Inside the pricing data

20:25 The A100 mystery: why an old chip is still in high demand

22:56 Do GPUs depreciate as fast as everyone thinks?

23:20 Making sense of the Texas and New York data center pauses

25:40 What the futures curve says about where prices are headed

28:01 Silicon Data's $30M Series A and what's next

30:36 Outro
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Meta released Glimmer this week, an open-weight AI model anyone can download and run on their own hardware — a contrast to Muse Spark, the company’s more powerful model that stays locked behind its own APIs. The release landed alongside a letter from Mark Zuckerberg arguing AI should be “for everyone” rather than controlled by a handful of labs, but as Equity’s hosts point out, the vision comes with some asterisks.



On this episode of TechCrunch's Equity podcast, Kirsten Korosec, Anthony Ha, and Rebecca Bellan take a look at Glimmer, Zuckerberg’s 6,500-word manifesto, and more of the week’s headlines, from the true cost of the AI industry’s energy needs to a $250M acquisition gone very wrong.



Listen to the full episode to hear more about:



Who’s on the market for a $300 cocktail robot?

Why Anthropic is adding watermarks to its generated text, and users are not happy.

The potential cost Amazon’s planned data center in Texas and the startups racing to fix the grid, including Form Energy’s $750M raise for 100-hour batteries, Reservoir’s $8M bet on smarter water heaters, and Discovered Materials’ hunt for cooler chips.

Why Joby Aviation’s $500M acquisition of a defense contractor reminds Kirsten of its Blade deal last year — and what the 2028 LA Olympics have to do with it.

How a $250M deal between video-clipping startup VideoVerse and sports publisher Minute Media collapsed amidst allegedly forged documents, multiple lawsuits, and a CEO nobody can reach.

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



00:00 Intro

1:20 Would you buy a $300 cocktail robot?

3:08 Meta's Glimmer and the “AI for everyone” pitch

8:03 Anthropic starts watermarking its writing, and users have thoughts

14:34 Amazon's data center and its natural gas problem

16:37 The startups racing to keep the grid from melting down: Form Energy, Reservoir, and Discovered Materials

23:28 Joby Aviation buys into defense with Resonant Sciences

28:24 The $250M VideoVerse-Minute Media deal, a missing CEO, and a mess of lawsuits

32:37 Outro
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AI notetaking hardware has taken off over the past couple of years, with credit-card-sized devices, pendants, pins, and even transcribing earbuds all promising to capture your meetings and turn them into summaries and action items. Now, a whole wave of wearables — rings especially — are betting people want to capture stray thoughts and ideas the same way.



One of the companies chasing that bet is Sandbar, the startup behind the private voice ring Stream, which has raised $36 million to date, including a $23 million Series A led by Adjacent and Kindred Ventures.



On this episode of TechCrunch's Equity podcast, Rebecca Bellan talks with Sandbar co-founder and CEO Mina Fahmi about why he thinks so many voice hardware devices before Stream struggled to break through, and why he's betting that keeping the human firmly in control is what it'll take to get wearable tech right.



Listen to the full episode to hear more about:

Why Fahmi designed Stream to be push-to-talk instead of always-on, and what he thinks “social acceptability” means for wearable AI.

How Fahmi's time at CTRL-labs, the neural interface startup Meta acquired in 2019, shaped his thinking on human-driven input.

Why Sandbar chose the “gruelingly painful” path of building fully custom hardware instead of reskinning an off-the-shelf device.

What Fahmi thinks it'll take for voice wearables to break out of tech-enthusiast circles and into the mainstream.

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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Historian Jill Lepore has a theory about why tech companies often use soaring language to describe their products — almost as if they're forming a new government. And whether you're thinking of Twitter's old “town hall in your pocket” or Anthropic's Claude constitution, it's a theory that doesn't paint Silicon Valley in a very flattering light.

In Lepore's upcoming book, The Rise and Fall of the Artificial State, the Pulitzer Prize-winning Harvard historian and New Yorker writer argues that tech companies are gradually taking on the functions of democratic government — whether that’s Twitter giving a distorted picture of the electorate or Facebook displacing local news. In her view, these leaders often mistake technological advancement for political progress, all while outright declaring their intention to replace the nation-state.



On this episode of TechCrunch's Equity podcast, Anthony Ha talks with Lepore about her book and why she thinks today's AI leaders — who promise a future where AI makes government more efficient, more responsive, and maybe even unnecessary — are selling an old fantasy in new packaging.



Listen to the full episode to hear more about:

Why Lepore sees a straight line from the classic 1984 Macintosh ad to Anthropic's AI constitution and Sam Altman's comments about an “AI president”

How E.M. Forster’s 1909 sci-fi story “The Machine Stops” provides a blueprint for the artificial state, and why Lepore says it now reads like “the diary of a very unhappy YouTuber”

Why Lepore believes the artificial state is ultimately unsustainable, and what she thinks it would take to rein it in

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

0:49 Defining the “artificial state”

2:17 Why corporations quietly took over state functions

4:43 Could the internet have gone another way?

9:01 From the 1984 Macintosh ad to Anthropic's constitution

10:20 The Twitter “town hall” myth

13:36 Structuring the book: history meets science fiction

17:46 The Machine Stops, and other bad manuals for the future

19:16 Musk, Heinlein, and misreading sci-fi

19:41 Why Lepore thinks the artificial state is “doomed”

21:51 Data centers, local politics, and the death of local news

24:44 Revisiting disruptive innovation, ten years later

26:54 Outro
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