>
Israel Used Palantir Technology In Its 2024 Lebanon Pager Attack, Book Claims
NATO Is a Menace, Not a Benefit, to America
MyPillow CEO Mike Lindell To Run For Governor Of Minnesota
Charlie Kirk Murder Suspect Makes First Courtroom Appearance
Build a Greenhouse HEATER that Lasts 10-15 DAYS!
Look at the genius idea he came up with using this tank that nobody wanted
Latest Comet 3I Atlas Anomolies Like the Impossible 600,000 Mile Long Sunward Tail
Tesla Just Opened Its Biggest Supercharger Station Ever--And It's Powered By Solar And Batteries
Your body already knows how to regrow limbs. We just haven't figured out how to turn it on yet.
We've wiretapped the gut-brain hotline to decode signals driving disease
3D-printable concrete alternative hardens in three days, not four weeks
Could satellite-beaming planes and airships make SpaceX's Starlink obsolete?

There does not seem to be a limit for neural nets to utilize more resources to get better and faster results.
Tesla is motivated to develop bigger, faster computers that are precisely suited to their needs.
The Google TPU architecture has not evolved as much over the last 5 years. The Google TPU chip is designed for the problems that Google runs. They are not optimized for training AI.
Tesla has rethought the problem of AI training and designed the Dojo AI supercomputer to optimally solve their problems.
If Tesla commercializes the AI supercomputer that will help to get to lower costs and greater power with more economies of scale.
One of the reasons that TSMC overtook Intel was that TSMC was making most of the ARM chips for cellphones. TSMC having more volume let them learn faster and drive down costs and accelerate technology.
99% of what neural network nodes do are 8 by 8 matrix multiply and 1% that is more like a general computer. Tesla created a superscalar GPU to optimize for this compute load.