We are building solar battery power plants, off-grid to start. 100% renewable. 99.9% availability. Grateful to our early backer @dfjgrowth. Read more about Ambrosia from DFJ: dfjgrowth.com/story/ambrosia…

Ambrosia Energy’s mission is to deploy the fastest and lowest-cost, continuous, renewable energy in the US. We want to add lots of power to the US grid eventually, and are starting with off-grid solar battery power plants to power compute. Looking for many new hires in both Silicon Valley and Austin.

It’s time to America-maxx.

Three years since the first flight of Starship, the next generation is here. New ship. New booster. New engines. New pad and new test site. SpaceX engineers are working to solve one of the most difficult engineering challenges in history: developing a fully, rapidly reusable rocket

Announcing Terafab: the next step towards becoming a galactic civilization x.com/i/broadcasts/1yKAPMzlv…

Today, we are emerging from stealth and launching PrismML, an AI lab with Caltech origins that is centered on building the most concentrated form of intelligence. At PrismML, we believe that the next major leaps in AI will be driven by order-of-magnitude improvements in intelligence density, not just sheer parameter count. Our first proof point is the 1-bit Bonsai 8B, a 1-bit weight model that fits into 1.15 GBs of memory and delivers over 10x the intelligence density of its full-precision counterparts. It is 14x smaller, 8x faster, and 5x more energy efficient on edge hardware while remaining competitive with other models in its parameter-class. We are open-sourcing the model under Apache 2.0 license, along with Bonsai 4B and 1.7B models. When advanced models become small, fast, and efficient enough to run locally, the design space for AI changes immediately. We believe in a future of on-device agents, real-time robotics, offline intelligence and entirely new products that were previously impossible. We are excited to share our vision with you and keep working in the future to push the frontier of intelligence to the edge.

The real story is the 14x compression ratio and what it means if it scales up. Every single weight in this model is one bit. Zero or one. That's it. 8.2 billion parameters stored in 1.15 GB of memory. A standard 8B model at full precision takes 16 GB. Bonsai 8B fits on your phone with room left over for your photo library. The benchmarks are the part that shouldn't be possible. On standard evals, a model that's 1/14th the size of Qwen3 8B and Llama3 8B is trading punches with both of them. The intelligence density score, capability per GB, is 1.06/GB versus Qwen3 8B at 0.10/GB. That's a 10x gap in how much thinking you get per unit of storage. Now zoom out. Big Tech collectively spent over $320 billion on data center capex last year. Amazon alone dropped $85.8 billion, up 78% year over year. Google committed $75 billion for 2025. The US power grid is buckling under AI demand. Data centers now consume 4.4% of all US electricity. Virginia, where most of them sit, saw electricity prices spike 267% over five years. Residential customers in Ohio are watching their bills climb 60% because utilities are spending billions on transmission infrastructure to feed server farms. The entire AI scaling thesis runs on one assumption: intelligence requires massive compute. PrismML just published a proof point that the assumption might be wrong. Their CEO, Babak Hassibi, is a Caltech professor who spent years on the mathematical theory of neural network compression. The founding team is four Caltech PhDs. Khosla Ventures backed it. So did Cerberus, whose Amir Salek built the TPU program at Google. The 1.7B model runs at 130 tokens per second on an iPhone 17 Pro Max at 0.24 GB. The 4B hits 132 tokens per second on M4 Pro at 0.57 GB. These aren't research demos. They shipped llama.cpp forks with custom 1-bit kernels for CUDA and Metal. Apache 2.0 license. You can download and run it right now. The trillion-dollar question: what happens to the economics of a $75 billion data center budget when the same intelligence fits in 1/14th the space and runs on 1/5th the energy?

Proof on orbit means of deployment = the world's first commercial satellite navigation constellation Our $170M in Series C funding marks the start of scaled manufacturing for our in-house satellite at our new Burlingame facility to launch our entire constellation over the coming years.

Starlink Mobile is providing data for video, voice, and messaging services in areas where terrestrial service is unavailable Working with global mobile network operators, our satellite-to-mobile network has grown to 32 countries, home to 1.7B people → starlink.com/mobile