I'm joining @OpenAI to bring agents to everyone. @OpenClaw is becoming a foundation: open, independent, and just getting started.🦞
https://t.co/XOc7X4jOxq
Sergey Brin is still % owner of Google (or Alphabet) together with Larry Page
But more importantly together they own 87.4% of all Class-B voting shares which give them 51.4% total voting power
Imagine being a dev or product creator with Sergey by your side, whenever Google's bureaucracy (which they have a lot of) tries to get you stuck, you just message Sergey and he gives the go-ahead
You essentially have a free pass to make anything, ship anything and launch anything without much constraints
That makes Google operate like a small startup again and that's why they're winning again I think
HTTP - 1989
SQL - 1973
Unix - 1969
I fully get the amount of industrial equity built by all the above technologies.
But I must ask... is this it? Are we as an industry just going to build off of these things forever? Do we not dare imagine anything else?
We discovered faster way to compute product of matrix by its transpose!
This has profound implications for data analysis, chip design, wireless communication, and LLM training!
paper: https://t.co/6CMNliyW7j
The algorithm is based on the following discovery: we can compute XX^t for 4x4 matrix in just 34 multiplications, a huge save compared to compared to naive way (40 multiplications 🤯).
We can apply this algorithm to any m x n matrix X (with n, m >= 4) by dividing it into 16 blocks X_1, ..., X_16.
- Estimated energy save: 5-10% ✅
- Estimated time save: 5% ✅
The discovery was made by combining Machine Learning-based Search and Combinatorial Optimization. We used RL to sample bilinear expressions. We then used combinatorial solvers (Gurobi) to enumerate relations between these expressions and combine these expressions together into one algorithm for XX^t. One way think of it is modification of AlphaTensor approach - We reduced the action space by a factor of a million (x1000000) at the expense of relying on combinatorial solvers.
The matrix XX^t is used everywhere:
- Data Analysis: linear regression
- Finance: covariance matrix for asset returns
- LLM training: Muon, SOAP, Shampoo
- Wireless Communication: 5G, MIMO channel capacity
This operation is performed trillions of times every minute globally. Imagine if we can save 5% of energy used for these computations!
Coauthors: Yushun Zhang @ericzhang0410, Zhi-Quan Luo.