Ex-Google Researchers Launch Generative AI ‘Swarm’ Startup Sakana AI

Two former top Google AI researchers, including one of the co-creators of the revolutionary “transformer” architecture, have launched a new startup called Sakana AI based in Tokyo. Sakana was founded by David Ha and Llion Jones, though financial details have not been disclosed. Jones was the fifth author on Google’s seminal 2017 “Attention Is All You Need” paper that introduced transformers, which became the backbone of major models like ChatGPT, while Ha previously led the Google Brain research group in Japan and was head of research at Stability AI.

Sakana AI

Ha and Jones were instrumental in the current generative AI explosion,  but Sakana is tackling the field from a different direction. Instead of focusing on scaling up transformer models, Sakana is focusing on new architectures rather than sheer size. Sakana’s approach emphasizes balancing capabilities with efficiency and avoiding wasteful, brute-force approaches. The company is working on melding generative AI with ‘evolutionary computation’ that mimics natural selection for optimal neural network performance.

“We’re on a quest to create a new kind of foundation model based on nature-inspired intelligence!” Ha wrote in a tweet announcing the new company. “The name Sakana is derived from the word さかな (sa-ka-na) which means fish in Japanese. Our logo is meant to invoke the idea of a school of (logic gate-shaped) fish coming together and forming a coherent entity from simple rules as we want to make use of ideas from nature such as evolution and collective intelligence in our research. The red ‘rebel’ fish swimming away represents our desire not to do what everyone else is doing and truly work on what’s coming next!”

Ha said the company is looking for people to join the company, suggesting you reach out if “you love fish, and you’re excited about developing collective intelligence, evolutionary computing, ALIFE, or neuro-inspired methods to advance the state of foundation models beyond the current AI paradigm.”


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