Symbolica AI

Company Overview

Symbolica AI is a startup company developing new state-of-the-art foundation models for structured reasoning in artificial intelligence. Founded in 2024 and headquartered in the San Francisco Bay Area with additional presence in London, Symbolica is building deep learning models that can manipulate structured data, learn algebraic structures, and perform reasoning with interpretability and verifiability.

Products Overview

Symbolica is developing machine learning models with several key capabilities:

1. Manipulation of structured data
2. Learning of algebraic structures in data
3. Interpretable and verifiable logic
4. Explicit episodic memory, unlike traditional large language models
5. Continuous interaction with validators, interpreters, and debuggers
6. Reduced hallucinations compared to existing models
7. Enhanced data privacy guarantees

The company’s approach aims to move beyond the limitations of current large language models by redesigning how machines learn and reason from the ground up. Their models are designed for complex formal language tasks like automated theorem proving and code synthesis.

Founding Team

The company was founded by George Morgan, a former Tesla autopilot engineer. Morgan serves as the CEO of Symbolica AI.

Other key team members include:

• Bruno Gavranović - Principal Scientist, focusing on categorical deep learning
• Falcon Dai - Machine learning researcher with a PhD in ML, RL, NLP, and CV
• Michael Swan - Software Engineer

Problem and Market Fit

Symbolica is addressing fundamental limitations of current state-of-the-art large language models like ChatGPT, Claude, and Gemini. These existing models are expensive to train, complex to deploy, difficult to validate, and prone to hallucination.

By developing new foundation models for structured reasoning, Symbolica aims to create AI systems that are more controllable, interpretable, reliable, and secure compared to existing solutions. This approach could potentially transform enterprise-scale AI applications across industries.

Business Model

While specific details of Symbolica’s business model are not provided, the company is likely to monetize its AI technology through:

1. Licensing of its AI models to enterprises
2. Cloud-based AI services
3. Custom AI solution development for specific industry applications
4. Partnerships with technology companies to integrate Symbolica’s models into existing products and services

Funding and Runway

Symbolica AI has raised a total of $33 million in funding. Their most recent round was a Series A of $33 million on May 9, 2024, led by Khosla Ventures. Other investors include Day One Ventures, General Catalyst, Abstract Ventures, and Buckley Ventures.

Competitive Landscape

Symbolica is positioning itself as an alternative to traditional deep learning approaches and large language models. While not direct competitors, companies working on advanced AI models that Symbolica may be measured against include:

1. OpenAI (ChatGPT)
2. Anthropic (Claude)
3. Google DeepMind (Gemini)
4. Other AI research companies and startups working on next-generation machine learning models

Symbolica’s differentiation lies in its focus on structured reasoning, interpretability, and explicit memory models, which sets it apart from the transformer-based architectures used by most current AI leaders.

Customers

As a newly launched startup, specific customer information for Symbolica AI is not publicly available. The company is likely in the process of engaging with potential enterprise customers and partners to pilot and deploy its technology.

Relevant News

• April 9, 2024: Symbolica AI announced its public launch and $33 million in total funding to build structured reasoning in machines.
• The company’s launch was covered in VentureBeat, highlighting Symbolica’s approach to transform AI beyond current deep learning paradigms.
• Vinod Khosla, an early investor in OpenAI, discussed his investment in Symbolica with Fortune, describing the company’s approach as “very innovative” for developing smaller, more efficient models that can reason more like humans.
• Symbolica is actively hiring for multiple roles, including machine learning scientists and engineers, with a particular interest in candidates with strong backgrounds in functional programming and category theory.