Uncovered this old photo from a SpaceX board meeting nearly 10 years ago with some of our crew. Grateful to my @DFJvc and @dfjgrowth partners @FutureJurvetson and @rglein for spearheading the investment into what’s potentially become the most important company in history. Proud to be an investor!

Porsche 911 driver orders Model Y Performance Convinced by FSD Supervised, ride quality & Grok SI integration

In celebration of us going back to having a brick and mortar compute trading floor, we at @parasail_io have buried $50B worth of Nvidia B300s throughout the foothills of the Sierra Nevadas and invite intrepid entrepreneurs to ignore all land rights and just start digging away.

Ok that was beyond insane. Beyond plaid. 0-60 in 0.8 seconds (thanks to thrusters and suction for tire grip) and top speed of Mach 0.5 Oh, and it can fly.

Fantastic sunset panel at #LATW with the great @WillBruey and @IanCinnamon, hosted by @moislamvc We tackled the big questions: 🚀 Is space overhyped? No. 🛰️ Datacenters in space? Likely. 🏭 Vertically integrate? Sometimes.
📈 Obsess over market size? You're creating the market!
🎤 Which VCs to work with? Those who aim to EARN your partnership vs. BUY it

Real life, baby

Turns out the future does have flying cars

Muse Spark Open -- weights releasing today -- runs great on new Mac Studios thanks to work with @johnternus and Apple.

For years, additive couldn’t make it past prototyping. The process wasn’t repeatable, the parts were hard to certify, and the economics never worked at volume. The new generation of 3D printing fixes those problems at the root, with smarter process control, more efficient throughput, and consistent production-grade parts. That’s why this is the moment. The technology finally matches the demand, and the government needs manufacturing capacity it can’t get from legacy supply chains. forbes.com/sites/zitaballing…?

Impressive — congratulations to all my friends at Anduril! The most valuable, private autonomy companies: 1) @Waymo ($126B) 2) @anduriltech ($90B) 3) @AppliedInt ($30B soon) Bullish on autonomous systems!

Come join us tomorrow!

Building what can't be built on Earth Orbital factories, satellite buses at scale, and a glimpse into the future they are accelerating Join us at this out-of-this-world event tomorrow where I have the pleasure of sharing the stage with greats @moislamvc @IanCinnamon and @WillBruey

Join us tomorrow for Building Beyond Earth 🚀 at #LATechWeek! Hear from @WillBruey (Varda), @IanCinnamon (Apex), @Farshchi (Lux Capital), and @moislamvc (Obvious) on what’s next for space. Capacity is limited. Request to join: partiful.com/e/YJc9nyWbJHEjv…

String theory is what happens when an intelligent system is starved of sensory input and starts hallucinating. Intelligence needs grounding. For this reason, intelligence is practically never the bottleneck to solving impactful problems. The bottleneck is iterated contact with reality.

Yeah, it's a peek into the future of how robots are going to seamlessly integrate into everyday life.

I always find it surprising when VCs in new tech waves get overly hung up on business quality / metrics (TAM, quality of revenue, margin, etc.). Disruptive tech always precedes figuring out the business model. Hell, we didn't monetize the Internet for years.

Technical moats are mostly over at this point. If you’re building something that is meant to be durable, the only moats now are: • Proprietary data • Network effects • A physical component

🇺🇸

Why are frontier physical AI labs like @DynaRobotics and @gs_ai_ building their own hardware? Dyna’s latest release, Dyna-2.1, offers some clues. Dyna has been doing stationary arms, with deployments like napkin folding at Din Tai Fung. They got really good at it, with a demo showing them folding napkins for 24 hours straight without a single failed fold. The problem was that humans still had to babysit the robots. It wasn't because they weren't reliable, but because they needed to clear napkin stacks, refill the bin, etc. Any process is only as fast as its slowest bottleneck, so if humans are waiting around for robots to do their task, or vice versa, it nerfs the ROI. So Dyna released Taku, their own semi-humanoid robot. It has a wheeled base, a folding lower body, and two arms with grippers. With Taku, Dyna can open the aperture for the tasks it can accomplish and remove more humans from the loop. In a laundry room, Takyu can do it all: load, unload, fold, and shelve laundry. Genesis' Eno is also a semi-humanoid robot. This has two benefits. First, it lets the robot learn from human data, which is still easier and cheaper to collect than robot demonstrations. It also takes out the most difficult part about building humanoids: the legs and the hands. With their own hardware, these labs can iterate faster. Dyna describes all motion, human or robot, in one shared format. When the hardware changes, Dyna retrains the low-level controller in simulation and keeps everything else. Data from every robot generation remains useful indefinitely. A workflow, like doing laundry, has many, many substasks. Dyna estimates a laundry cycle at about 79 steps. If each step is only 95% reliable, the whole cycle succeeds less than 2% of the time. The lesson that Dyna learned from deploying robots is one that others will soon learn too. Building useful robots means owning the entire stack and engineering reliability into every single part.

SpaceX has arrived.

America will establish a permanent presence on the moon. 🚀🌕