Discovery Engines
Discovery Engines
Podcast Description
Featuring the people and platforms accelerating scientific discovery.
Podcast Insights
Content Themes
The podcast covers a variety of topics related to scientific innovation, technology in research, and the deep tech startup ecosystem. Specific episodes explore themes such as the ethics and advancements in animal testing, the cultural shifts in lab automation, and the role of AI in life sciences, with examples including conversations around the founding of Olden Labs and the business structure of Bay Area Lab Automators.
Featuring the people and platforms accelerating scientific discovery. Hosted by Nabil Laoudji. Our newsletter: www.discoveryengines.co
Alishba Imran is a deep learning researcher at UC Berkeley’s BAIR AI Lab, a Research Fellow at the Arc Institute, a former Research Intern at the Chan Zuckerberg Biohub, co-founder of battery tech startup Voltx, and co-author of “AI for Robotics: Toward Embodied and General Intelligence in the Physical World”
See below for episode links, chapters, and our socials. Hosted by Nabil Laoudji.
Support the podcast! Subscribe to our newsletter: www.discoveryengines.co. Thanks for watching 🙏🤙
Episode Links:
- Alishba’s LinkedIn
- Alishba’s Twitter
- “AI for Robotics” book
- Arc Institute
- UC Berkeley BAIR AI Lab
- Chan Zuckerberg Biohub
- DynaCLR Paper
- Biopunk Lab
Chapters:
- (00:00) – Preview & Introduction
- (05:02) – Why AI for Science?
- (10:34) – Bootstrapping Your Own Learning
- (16:02) – Why Battery Testing Matters: Launching Voltx
- (20:19) – Batteries, Raw Earth Minerals: Incremental vs Transformative Chemistries
- (23:54) – The Business Side of Deep Tech Entrepreneurship
- (29:14) – The State of Battery Tech Today
- (30:50) – Working with Chan Zuckerberg Biohub
- (33:37) – DynaCLR For Contrastive Learning of Cell State Dynamics
- (36:21) – Why Self-Supervised + Contrastive Learning
- (41:06) – Generalizing to Different Cells Contexts With Embeddings
- (42:06) – Microscopy or ML Advancements for Unlocking Progress
- (43:54) – Managing Terabytes of Data
- (46:51) – Arc Institute: Collecting Largest Single Cell Dataset
- (48:40) – Role of Tech-Founder Funded Institute To Advance Foundational Work
- (50:41) – Book Launch! Merging Classical Robotics Methods With Cutting-Edge Deep Learning
- (53:42) – Robotics Progress: Hype vs Reality
- (57:09) – Robotics for Science
- (58:54) – Future Trends: Automation, Foundational Single Cell Models, Protein and Genome Language Models, Transcriptomics
- (01:00:41) – Pivoting into AI for Science Early, Mid, or Late Career
- (01:02:49) – Exchanging Ideas; DynaCLR Paper; AI for Robotics Book
Connect With Us:
Platforms:
Disclaimer
This podcast’s information is provided for general reference and was obtained from publicly accessible sources. The Podcast Collaborative neither produces nor verifies the content, accuracy, or suitability of this podcast. Views and opinions belong solely to the podcast creators and guests.
For a complete disclaimer, please see our Full Disclaimer on the archive page. The Podcast Collaborative bears no responsibility for the podcast’s themes, language, or overall content. Listener discretion is advised. Read our Terms of Use and Privacy Policy for more details.