"Can a Machine Learn a Cell?"

Lossfunk Research Mixers are intimate, topic-first roundtables for people in Bengaluru with a real knack for research, whether they are researchers, engineers, writers, philosophers, artists, interdisciplinary thinkers, or independent tinkerers.

In this mixer, our exploration is inspired by Yuri Lazebnik's essay, Can a Biologist Fix a Radio?, which has reflections of the anxieties of working in an accelerating scientific field that many of us would resonate with today.Few fields are moving faster today than machine learning. The pace can feel almost absurd: years of progress compressed into months, sometimes weeks. In some, this inspires a hope for scientific acceleration and perhaps in many others an increasing level of anxiety.The unsettling question of what happens when our predictive abilities outpace our abilities to understand feels especially consequential in Biology.In this research mixer, we hope to discuss some of these epistemic questions:

  • Prediction vs Understanding: Can a sufficiently powerful model learn the behavior of a biological system without discovering its underlying mechanisms?

  • Are there laws of biology?

  • Is Biology learnable like Language?

  • Data or models: what is the real bottleneck?

  • Why do so many drugs fail, and can AI fix that and help us alleviate disease?

  • Are we asking the right questions of the tools we are building?

What to expect

  • A priming of the fundamental challenges in Biology today, a description of the tools and capabilities we currently have: 10-15 minutes.

  • Picking questions and discussing them in smaller groups: 30 minutes

  • Concluding with an open discussion for 30 minutes

With participants’ permission, we’ll collect contributions into a public document. These may also form the basis of a write-up on the Lossfunk Substack.

You should apply if

  • You’re interested in biology, AI, the changing educational and research paradigm, or some intersection of these

  • You have a perspective on how the boundaries between fields are evolving

  • You’re open-minded, willing to contribute, listen closely, and revise your thinking

We welcome researchers, students, engineers, founders, and people taking unconventional paths. We’ll curate a mix of backgrounds and disciplines to make the discussion fruitful. Founders are welcome to participate; this is not a pitching event.

We believe great researchers can come from anywhere. We especially encourage students, early-career professionals, motivated women, and people taking unconventional paths to apply.

Presented by Chaitra Agrahar

Organized by Lossfunk, a lab for the deeply curious.