Symbolica's models are "interpretable", meaning users can understand how the AI network reached a decision, increasing transparency and making them easier to monitor and debug. This is crucial for highly regulated industries where inaccuracies could have severe consequences, such as healthcare and finance. The company's first product, a coding assistant, is set to launch in early 2025 after the necessary model building and training.
Key takeaways:
- AI startup Symbolica AI launched with a unique approach to building generative AI models and has raised $33 million in total funding from a Series A and seed funding round.
- Symbolica AI is aiming to tackle the expensive mechanisms behind training and deploying large language models based on Transformer architecture.
- Symbolica approaches AI model building through structured models that manipulate symbols, which can run on less computational power and rely on less overall data than large, complex unstructured models.
- The company's first product will be a coding assistant, set to launch in early 2025, after the company builds and trains its model.