Elon Musk: “Path to Petawatts is Mass drivers on Moon”
SpaceX’s Lunar Mass Driver is a planned electromagnetic launch system on the Moon, similar to a giant coilgun-style catapult, designed to launch solar-powered AI compute satellites into orbit or deep space at extremely low cost
Terafab will be built in Grimes County, Texas
In April, we broke ground on our research fab on the North Campus of Giga Texas – the precursor to Terafab.
Both Tesla & SpaceX will need far more chips than current & future global production can supply.
This is why we're building the largest chip manufacturing facility ever, with the goal of producing over 1 terawatt of compute per year
The future is built in Texas
We tried using Meta's new Muse Code agent, but it has a bug that doesn't let it sign in from a docker container.
So we did a fun experiment: Meta claims Muse Spark 1.2 was co-trained with their Muse agent harness. So we extracted instructions from their system prompt and added them to the Cline harness.
TL;DR of this special prompting:
- Trust source code over the user prompt, so read every call site and existing tests before starting the task
- Weigh edge and error cases as heavily as the happy path
- Always reproduce the bug before fixing
- Don't trust the first passing test suite, and verify suspicious looking half-baked tests
- Never stop at just editing, keep working until the change is verified complete.
We then asked this modified harness to fix a real bug from our repo, and compared the results to the original Cline agent harness.
Results:
- Used 2.7x fewer tokens (19.7M → 7.2M)
- Finished 2x faster (49min → 24min)
- Cost 2.4x less ($7.69 → $3.25)
Same Muse Spark 1.2 model, same task, only the prompting changed. Incredible how much of a performance gain Meta was able to achieve training it on these special instructions!