Probably raises $9M to build a more reliable kind of AI
Key takeaways
- As LLMs have grown more powerful, hallucinations have proven stubbornly difficult to avoid.
- Probably, which just raised $9 million in seed funding from Andreessen Horowitz, is trying to build a more rigorous way to catch those errors.
- As it turns out, bringing LLMs to that level of accuracy requires rethinking many of the basic assumptions of AI engineering.
Why this matters: a development in AI with implications for how people work, create, and decide.
As LLMs have grown more powerful, hallucinations have proven stubbornly difficult to avoid. Errors pop up in even the smartest models, and while there are ways to catch those errors, the industry is still figuring out the best way to do it.
Probably, which just raised $9 million in seed funding from Andreessen Horowitz, is trying to build a more rigorous way to catch those errors.
As founder Peter Elias (pictured above) puts it, the company s goal is to prevent hallucinations and simple factual errors from ever reaching the user, and achieve the kind of 99.99% accuracy that’s common in deterministic systems but much more difficult to reach with AI. As it turns out, bringing LLMs to that level of accuracy requires rethinking many of the basic assumptions of AI engineering.