Today’s blog post is brought to you by Eva Lau. She will talk about one of our recent investments: Axiomatic AI.
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Congratulations to Axiomatic on their recent US$6M seed round led by Kleiner Perkins! Two Small Fish Ventures is thrilled to be an early investor since the company’s inception—and the only Canadian investor—in what promises to be a game-changer in solving fundamental problems in physics, electronics, and engineering.
Why is this important? Large Language Models (LLMs) excel at languages (as their name suggests) but struggle with logic. That’s why AI can write poetry but struggles with math, as LLMs mainly rely on ‘pattern-matching’ rather than ‘reasoning.’
This is where Axiomatic steps in. The company’s secret sauce is its new AI model called Automated Interpretable Reasoning (AIR), which combines advances in reinforcement learning, LLMs, and world models. Axiomatic’s mission is to create software and algorithms that not only automate processes but also provide clear, understandable insights to fuel innovation and research, ultimately solving real-world problems in engineering and other industrial applications.
The startup is the brainchild of world-renowned professors from MIT, the University of Toronto, and The Institute of Photonic Sciences (ICFO) in Barcelona. The team includes leading engineers, physicists, and computer science experts.
With its innovative models, the startup fits squarely within our fund’s focus: the next frontier of computing and its applications. As all TSF partners are engineers, product experts, and recent operators, we are uniquely positioned to understand the potential of Axiomatic and support the team.
Axiomatic’s new AIR model is well-positioned to accelerate engineering and scientific discovery, boosting productivity by orders of magnitude in the coming years, and ultimately make the world’s information intelligible.
P.S. This blog is licensed under a Creative Commons Attribution 4.0 International License. You are free to copy, redistribute, remix, transform, and build upon the material for any purpose, even commercially, as long as appropriate credit is given.
