Controlling Biology - Fabian Theis, Helmholtz Munich
- ID
- 43829
- Status
- summarized
- Published
- 06 Nov 2026, 11:10 PM
- Fetched
- 06 Nov 2026, 11:47 PM
- Provider
- Latent Space
- Category
- developer-ai
- Original URL
- https://latent.space/p/controlling-biology-fabian-theis-helmholtz-munich/
- Source URL
- https://www.latent.space/feed
Summary
- Score
- 3.5
- Created
- 06 Nov 2026, 11:47 PM
- Tags
- Audience
- ai_ml_learners
What happened
Latent Space interviews Fabian Theis of Helmholtz Munich about pushing biology from mapping and predicting toward controlling it, using multi-scale, multi-modal, time-varying 'multiomics' data. The episode contrasts heavy attention on protein/molecular design with quieter skepticism about Virtual Cell models, which still face questions about solving basic problems. It also cites a $1.8B Biohub/NIH/DOE/Google/Meta commitment tied to new imaging and measurement capabilities that generate large datasets for AI training.
Why it matters
There is no direct API, tooling, pricing, or Malaysia/SEA policy detail in the excerpt, so most builders should not change course from this alone. The actionable signal is for AI/ML learners tracking AI-bio: watch whether the $1.8B commitments actually release usable imaging/multiomics datasets and benchmarks, since the text says Virtual Cell models still face basic effectiveness questions.
Discussion angle
Ask whether the $1.8B data-generation push will produce usable benchmarks for Virtual Cell models, or whether protein and molecular design will keep drawing more builder attention; tie the discussion to what datasets the commitments actually release.