Symbolica AI
Building structured cognition in machines
- 1-20 employees
- B2B
- Artificial Intelligence
- Deep Tech
- Machine Learning
- SaaS
- Science
- SoMa, San Francisco, CA
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Company mission
To bridge the gap between theoretical mathematics and cutting-edge AI, creating symbolic reasoning models that think like humans - precise, logical, and interpretable.
Our take
Right now, most AI works by crunching massive amounts of data using increasingly massive computers. But experts say we're hitting a wall, with bigger models costing more, using more energy, and quite frankly, plateauing in quality.
That's where Symbolica AI steps in. Instead of building AI that just mimics patterns, Symbolica is creating models that reason (think logic, math, and structure over brute force guesswork). Using advanced math called category theory (it's as brainy as it sounds), it's building smaller, smarter AI that can explain answers and make decisions you can actually understand. It's pretty much a mix of old-school symbolic AI and new neural networks.
It's still early days for the company, but it is making waves, with serious funding and a dream team from Tesla and Neuralink. And its first product, a code-generating AI, is set to be released very soon. Of course, it's battling AI giants with deep pockets and tons of data, but if Symbolica's gamble on structure over scale pays off, it might just be the blueprint for AI's next big leap.
Freddie
Company Specialist at Welcome to the Jungle
Leadership
George Morgan
(Co-Founder & CEO)Previously spent 4 years at Tesla as an Autopilot Software Engineer. Prior to that, they founded Flipper Engineering where they served as the Lead Developer for over 4 years.
Jonathan Frydman
(CPO)Jonathan graduated from The University of British Columbia with a BASc in Mechanical Engineering. Previously spent 3 years at Tesla as a Product Design Engineer and Senior Software Product Manager.