>
The Secret Campaign To Stop RFK Jr.
You Can't Grow Your Way Out: The GOP's Debt Delusion Exposed
Musk Sets Off Fireworks: Polls X Users on End of Two-Party 'Uniparty' System...
xAI Grok 3.5 Renamed Grok 4 and Has Specialized Coding Model
AI goes full HAL: Blackmail, espionage, and murder to avoid shutdown
BREAKING UPDATE Neuralink and Optimus
1900 Scientists Say 'Climate Change Not Caused By CO2' – The Real Environment Movement...
New molecule could create stamp-sized drives with 100x more storage
DARPA fast tracks flight tests for new military drones
ChatGPT May Be Eroding Critical Thinking Skills, According to a New MIT Study
How China Won the Thorium Nuclear Energy Race
Sunlight-Powered Catalyst Supercharges Green Hydrogen Production by 800%
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.