All-In E110: 2023 Bestie Predictions!
Episode 110 • 1/6/2023
Political Predictions
Political Winners
- Sacks predicted Asian American college applicants will be big winners due to likely Supreme Court decisions on affirmative action cases against Harvard and UNC
- Friedberg chose MBS/Saudi Arabia due to their growing leverage between US, Russia and China, especially around oil trade in yuan
- Chamath made a "spread trade" prediction: Long Nikki Haley, Short Ron DeSantis for GOP nomination
- Jason predicted Trump's trajectory in 2023: weight loss on Ozempic, indictment by Garland, but ultimately getting a Nixon-style pardon
Political Losers
- California/San Francisco (Sacks) due to major budget deficits
- IMF (Friedberg) as they deal with global debt market issues
- DeSantis (Chamath) for peaking too early
- White collar workers with no hard skills (Jason)
Business Predictions
Business Winners
- OpenAI (Friedberg) as AI capabilities expand dramatically
- US Natural Gas Industry (Sacks) due to Europe's shift away from Russian gas
- SpaceX/Relativity Space (Chamath) with major launch capabilities and contracts
- Laid off tech workers starting companies (Jason)
Business Losers
- Google Search (Chamath) due to AI competition
- Series B-D growth startups (Friedberg) facing funding challenges
- Consumer credit (Sacks) as debt loads become unsustainable
- Office real estate, especially in San Francisco (Jason)
Notable Predictions & Trends
Major Deals
- Starlink IPO prediction from Chamath at $75B+ valuation
- Russia-China potential trillion dollar deal (Sacks)
- Saudi-China petro yuan trade (Friedberg)
- Amazon expanding into healthcare as fourth pillar (Jason)
Key Trends
- Cell & gene therapy mainstreaming (Friedberg)
- Trump's waning GOP influence (Sacks)
- Persistent wage inflation (Chamath)
- Austerity measures across society (Jason)
The group also discussed anticipated media including Oppenheimer, Dune Part 2, and AI-generated content. The episode concluded with breaking news about OpenAI's reported $29B tender offer, leading to debate about AI training data rights and monetization challenges.