Thomas Sachson, JD

In just a year, these robots went from machine-like to almost human A 2025 vs 2026 comparison at the Chinese Spring Festival Gala shows unbelievable progress.

This was a 2 line prompt in seedance 2. If the hollywood is cooked guys are right maybe the hollywood is cooked guys are cooked too idk.

Jensen Huang just BROKE the most important rule in the industry. And it explains why Nvidia controls 95% of the AI chip market. Last night at CES, he unveiled Vera Rubin - the new AI supercomputer that's shipping right now. Full production started weeks ago. But here's the part that made every semiconductor engineer in the room go crazy: Reuben GPU is 5x faster than Blackwell. But only has 1.6x the transistors. That should be physically impossible. Moore's Law says you get maybe 25% more performance per transistor generation. Jensen just delivered 300%. How? He BROKE the most sacred rule in chip design. The rule every company follows: "Never redesign more than 1-2 chips per generation." Nvidia redesigned all six chips simultaneously. Vera CPU. Reuben GPU. Connect X9 networking. Bluefield 4 DPU. MVLink switches. Spectrum X Ethernet. Every. Single. Component. From scratch. He calls it "extreme co-design." The industry calls it insane. One rack now moves 240 terabytes per second. That's TWICE the entire global internet bandwidth. In a single rack. And it runs on 45°C water - no chillers needed. Which saves 6% of global data center power. But the real story isn't the hardware... It's what they're doing with it. Nvidia just open-sourced Alpha Mayo. The world's first reasoning autonomous vehicle AI. Mercedes-Benz CLA launches with it in Q1. Europe Q2. Asia by year-end. Not a concept car. Not a limited release. Full production vehicles. And the AI will even explain its reasoning out loud. "I'm slowing down because the truck ahead is braking and there's a cyclist merging." It thinks. Then tells you what it's thinking. Then executes. Jensen drove it through San Francisco for an hour yesterday. No hands. No interventions. Through heavy Sunday traffic. The whole thing is open source now. Every line of training code. Every data source. The entire stack. But why would Nvidia give this away? Because they learned something from the last year: Open models activated the entire world. DeepSeek R1 proved open source can hit the frontier. Downloads exploded. Every country, every startup, every researcher can now build AI. And they all need Nvidia hardware to train it. That's the strategy. Give away the recipes. Sell the kitchen. The partnerships tell you where this is going: Siemens is integrating Nvidia into every industrial design tool. Cadence and Synopsys are rebuilding chip design around Nvidia. Palantir, ServiceNow, Snowflake - their entire platforms now run on Nvidia's agentic AI stack. This isn't just selling chips anymore. Nvidia is rebuilding the entire computing stack. From design to manufacturing to deployment. Every layer of the trillion-dollar AI infrastructure buildout runs through them. And now they're 18 months ahead of everyone else. Again. The competition is still trying to match Blackwell. Nvidia's already shipping the thing that makes Blackwell look slow. What do you think - is anyone catching them? The only company capable of this might be Google.

Jensen Huang just BROKE the most important rule in the industry. And it explains why Nvidia controls 95% of the AI chip market. Last night at CES, he unveiled Vera Rubin - the new AI supercomputer that's shipping right now. Full production started weeks ago. But here's the part that made every semiconductor engineer in the room go crazy: Reuben GPU is 5x faster than Blackwell. But only has 1.6x the transistors. That should be physically impossible. Moore's Law says you get maybe 25% more performance per transistor generation. Jensen just delivered 300%. How? He BROKE the most sacred rule in chip design. The rule every company follows: "Never redesign more than 1-2 chips per generation." Nvidia redesigned all six chips simultaneously. Vera CPU. Reuben GPU. Connect X9 networking. Bluefield 4 DPU. MVLink switches. Spectrum X Ethernet. Every. Single. Component. From scratch. He calls it "extreme co-design." The industry calls it insane. One rack now moves 240 terabytes per second. That's TWICE the entire global internet bandwidth. In a single rack. And it runs on 45°C water - no chillers needed. Which saves 6% of global data center power. But the real story isn't the hardware... It's what they're doing with it. Nvidia just open-sourced Alpha Mayo. The world's first reasoning autonomous vehicle AI. Mercedes-Benz CLA launches with it in Q1. Europe Q2. Asia by year-end. Not a concept car. Not a limited release. Full production vehicles. And the AI will even explain its reasoning out loud. "I'm slowing down because the truck ahead is braking and there's a cyclist merging." It thinks. Then tells you what it's thinking. Then executes. Jensen drove it through San Francisco for an hour yesterday. No hands. No interventions. Through heavy Sunday traffic. The whole thing is open source now. Every line of training code. Every data source. The entire stack. But why would Nvidia give this away? Because they learned something from the last year: Open models activated the entire world. DeepSeek R1 proved open source can hit the frontier. Downloads exploded. Every country, every startup, every researcher can now build AI. And they all need Nvidia hardware to train it. That's the strategy. Give away the recipes. Sell the kitchen. The partnerships tell you where this is going: Siemens is integrating Nvidia into every industrial design tool. Cadence and Synopsys are rebuilding chip design around Nvidia. Palantir, ServiceNow, Snowflake - their entire platforms now run on Nvidia's agentic AI stack. This isn't just selling chips anymore. Nvidia is rebuilding the entire computing stack. From design to manufacturing to deployment. Every layer of the trillion-dollar AI infrastructure buildout runs through them. And now they're 18 months ahead of everyone else. Again. The competition is still trying to match Blackwell. Nvidia's already shipping the thing that makes Blackwell look slow. What do you think - is anyone catching them? The only company capable of this might be Google.

This was only two months ago. I suggest going back and listening to it again, I just did myself.

Created an off-axis projection demo using mediapipe for face tracking, threejs and a 3D scanned shoe. Try it out yourself…

Children's drawings brought to life by AI [✏️ thingsihavedrawn]