Fundamental

The hardest part of data science is figuring out what problem to solve. Gael Varoquaux says the real work is figuring out what the data is, what question you're asking, and what an answer is worth. In science it's called framing the problem. In business, he says, it's the same job.

What if we could more accurately predict what comes next? That's the question that started Fundamental. A couple of years later, it’s changing what AI can do.

Proud to see Kevin Scaman present ‘What LLMs Learn (and Don't) from Tables’ at the [ICML] Int'l Conference on Machine Learning The work shows that general-purpose LLMs rely heavily on memorization when reasoning over tabular data, with performance deteriorating as table complexity grows. Progress on tabular AI won't come from simply scaling language models. Structured data presents a different set of challenges, and solving them requires purpose-built architectures. If this sounds interesting, come join our research team

Japan's largest bank is betting on Fundamental. Today, MUFG, one of the world's largest financial institutions, announced a strategic partnership with Fundamental 🤝 Full blog in the comments

Many advances in AI are really part of the same story: finding ways to make deeper models work. Sander Dieleman discusses this in his latest conversation with Marta Garnelo. Full interview coming soon

Our Founding Advisor Gael Varoquaux has spent decades helping shape modern data science as cofounder of scikit-learn and a leading researcher in machine learning. In this conversation with Fundamental Head of Applied AI Alexandre Gerbeaux, Gaël shares his perspective on some of the most important questions facing the field today: • Why LTMs represent a major opportunity for researchers and builders • Why problem framing matters more than model optimization • The overlooked importance of tabular data in enterprise AI • Why different AI systems will continue to have different strengths • How data science can create meaningful impact in business and society Watch the full interview and explore the ideas shaping the next generation of AI. https://lnkd.in/dBQk7-WU