Latest Interviews
Showing 1–3 of 3 transcripts.
Clear all filters- a16z21 min
AI is Industrializing Discovery
The speaker characterizes the current biotech era as an industrial revolution where AI is transforming drug discovery from a bespoke artisanal model into a scalable, engineering-driven process. By overcoming myths regarding biological complexity and data scarcity through techniques like graph convolutions and one-shot learning, companies are achieving accuracy rates of over 90% in biomarker discovery and predicting clinical outcomes with modest incremental gains. This strategic shift promises to slash manufacturing costs for protein therapeutics by up to 90% and reduce trial expenses, creating a critical opportunity for professionals to merge domain expertise with AI skills to industrialize discovery at unprecedented scale.
- a16z35 min
a16z Podcast | What Technology Wants, Needs, Does
Marc Andreessen, Frank Chen, Vijay Pande, Alex Rampell
This panel examined critical regulatory tensions in healthcare and fintech, analyzing how the shift to pay-for-value models and Dodd-Frank risk retention rules create new barriers for startups while enabling regulatory arbitrage. Experts further debated the ethical implications of AI in lending and medicine, highlighting the conflict between opaque deep learning algorithms and existing fair-lending laws alongside the potential for technology to render physical travel obsolete through high-fidelity telepresence. The discussion concluded by projecting how innovations in genomic risk scoring, autonomous logistics, and lab-grown organs will fundamentally reshape social determinants of health and long-term human longevity.
- a16z24 min
When Biology Moves to Engineering
Positioning biological evolution as a source of accumulated "technical debt," the event frames modern healthcare challenges as engineering problems solvable through AI-driven precision rather than traditional trial-and-error discovery. Key advancements in automated circuit design and behavioral digital therapeutics demonstrate how this shift enables predictable, high-accuracy solutions for complex conditions like cancer and diabetes. Ultimately, the approach seeks to transform medicine by engineering the reversal of aging and optimizing systemic care coordination to move from reactive sick care to proactive health maintenance.