0:00 Alibaba just released the weights for a 2.4 trillion parameter model.0:03 It’s now one of the largest open models on the planet, and it changes the game for what you can build without asking a lab for permission.0:11 In episode 138, we saw Meta’s Muse Glimmer escalate the race for capable local models.0:15 Today, a Chinese tech giant just reset the board on sheer scale.0:19 That’s the lead.0:20 Here are the other signals moving the market.0:22 First, Google’s Gemini AI assistant just crossed one billion monthly active users.0:26 Sundar Pichai called it their "fastest growing product ever." That makes Gemini the fourteenth product at Google to hit the billion-user mark, and it did it faster than any of the others.0:36 The adoption curve here is vertical.0:38 Second, the money is still moving.0:40 A Swedish AI coding startup called Lovable just raised four hundred million dollars in a Series C, pushing its valuation to thirteen-point-three billion dollars.0:49 For context, they are doing five hundred million in annualized revenue.0:53 This isn’t a bet on future tech.0:54 It’s a bet on a real, scaling business.0:56 Third, a different kind of money move.0:58 A firm called Thrive Holdings just raised two billion dollars specifically to acquire AI-focused service firms.1:04 This is the first major signal of consolidation in the services layer—the consultants and integrators who actually get AI working inside big companies.1:13 And finally, two strategic moves from the big labs.1:15 Anthropic just locked in a TWENTY-year compute deal with Riot Platforms.1:19 That’s a nine-point-one billion dollar commitment for one hundred ninety-one megawatts of power through 2048.1:25 They are securing their ability to train models for decades.1:28 And Google just reorganized DeepMind, moving Demis Hassabis up to Chief Scientist of Alphabet to focus squarely on AGI, while promoting Koray Kavukcuoglu to run the Gemini model teams.1:38 Okay, let's go back to that Alibaba model.1:40 It's called Qwen3.8-2.4T-A95B.1:42 The name is a mouthful, but the number that matters is 2.4 trillion.1:46 That’s the number of parameters.1:47 Releasing the weights means anyone with enough hardware can now download, inspect, and run a model of that scale.1:53 This isn't just another seventy-billion parameter model you can fine-tune.1:57 This is a direct shot across the bow at the closed, proprietary frontier models from the major US labs.2:03 Alibaba is claiming performance that rivals models like Fable 5.2:06 Now, here's the catch.2:08 These claims are from Alibaba.2:09 The model's actual performance and its adoption outside of China are still completely unverified.2:14 We don't know how it truly stacks up on independent benchmarks.2:18 But that almost doesn't matter.2:19 The signal is what's important.2:21 A top-tier Chinese technology company has decided that its strategic advantage lies in arming the open-source community with a frontier-scale model.2:29 This move is designed to build an entire ecosystem around their architecture, creating a powerful alternative to the Western AI stack.2:36 The era of US-only dominance in open-weight models is OVER.2:39 Now let's follow the money, because it tells the other half of the story.2:43 That four-hundred-million-dollar check for Lovable is more than just a big number.2:48 It's validation of a very specific strategy.2:50 Lovable isn't trying to build a general-purpose AI.2:53 It's an AI coding assistant, and it's absolutely dominating its niche.2:57 The company hosts sixty million projects.2:59 It attracts nine hundred million visitors a month.3:02 And as of June, it was booking half a billion dollars in annualized revenue.3:06 Here’s what’s different: Lovable built its own proprietary AI model but also lets users access other frontier models through its platform.3:13 They have deep technical sophistication AND a massive user base.3:16 This is the blueprint for a successful vertical AI company.3:20 They solved a specific, high-value problem and built a product so good that developers are willing to pay for it at scale.3:26 Then you have Thrive Holdings raising two billion dollars.3:29 They aren't building a product at all.3:31 They're buying the companies that build AI solutions for everyone else.3:35 This is the classic pick-and-shovel play.3:37 As every company on Earth scrambles to implement AI, a huge market emerges for the service firms that can do the complex integration work.3:45 Thrive is betting that this services layer is about to consolidate, and they've raised a war chest to be the one doing the consolidating.3:52 So you have two massive flows of capital.3:54 One is going to hyper-focused, high-growth products like Lovable.3:58 The other is going to the infrastructure and services layer that supports the entire ecosystem.4:03 The easy money for building general foundation models is gone.4:06 The smart money is now moving downstream.4:08 The entire landscape is bifurcating.4:10 On one side, you have massive, state-backed models like Qwen being released into the open, aiming to create a global standard.4:17 On the other, you have hyper-focused, capital-intensive private companies like Lovable capturing immense value in specific markets.4:24 The question is no longer just about who has the biggest model.4:28 It's about which ecosystem wins—the open, distributed network or the closed, profitable product.4:33 Today, both of those camps just got a lot stronger.
