Erik Torenberg sat down with Seth Bannon, co-founder and general partner at Fifty Years, a pre-seed and seed focused VC firm. They discuss the challenges of commercializing academic research, the differences between biotech and tech bio companies, exploring recent advancements in bioengineering, genetic engineering, synthetic biology, and the significance of the "bio moment." They also cover the impact of AI and machine learning on biological research and examine alternative funding models transforming the scientific startup landscape. Control your company's spending and close your books 3x faster: visit rippling.com/spend for a free demo and one month free trial.

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LINKS:

Spinout Playbook: https://www.fiftyyears.com/spinout

Paul Graham’s How to Start a Startup: https://paulgraham.com/start.html

Solugen - https://solugen.com/

More on Fifty Years:

Website: https://www.fiftyyears.com/  

Seth Bannon on Twitter: https://twitter.com/sethbannon/status/1813633256128192617

The world needs 10x more scientist-founders. 5050 helps scientists and engineers become great founders and start indispensable companies. Apply / nominate! ➜ http://fiftyyears.com/5050 

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TIMESTAMPS:

(00:00) Intro

(00:53) Seth Bannon's background and inspiration

(03:38) Founding and mission of Fifty Years

(03:51) Defining deep tech and investment thesis

(04:34) Challenges in commercializing academic research

(10:14) The Spinout Playbook

(12:23) Sponsors: Rippling Spend | WorkOS

(14:38) Empowering PhDs to become entrepreneurs

(15:06) Building deep tech companies

(20:41) Biomoment in technology

(27:41) Rapid integration of large language models

(28:06) Startups leading the charge in pharma innovation

(28:46) The role of proprietary data in bioengineering

(29:31) Understanding spatial context in cell biology

(30:43) Getting into biology without formal training

(33:22) The beginner's mind investment philosophy

(34:14) The future of deep tech and network-driven VC

(36:33) Sponsor: Squad

(38:01) Tech bio vs biotech

(45:54) Alternative funding models for science

(49:41) Incentivizing failure in scientific research

(53:50) Wrap