TEEs aren’t as secure as they seem.
Like Christmas, but with more AI chips.
And novel hardware architectures are well-suited to cryptography.
Are d-Matrix’s performance numbers too good to be true?
LLMs don’t make chips better. Good engineers do.
A new use-case for approximate computing.
Part 1: Diode, and connecting language models to the physical world.
And should you consider investing if they do?
Especially if you want to be an electrical engineer.
Part 1: Primitive Instruments, and hardware at the speed of software.
How do we stop this from happening again?
Also: co-working in NYC, and Normal Computing is hiring!
The Count of Monte Carlo
Building chip companies could be so much easier.
And why does Anduril have so many products?
Could AI revive an architecture from the 1950s?
If you raise $120M, at least try to write an honest press release.