Latest Interviews
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Clear all filters- a16z47 min
Why Scale Will Not Solve AGI | Vishal Misra - The a16z Show
Researchers have mathematically validated that Large Language Models function as "Bayesian wind tunnels," where in-context learning precisely updates token probability distributions in real-time rather than relying solely on statistical correlation. Despite demonstrating this capability through the open-sourced "TokenProbe" tool and reproducing results across transformer architectures, current models remain fundamentally limited by their frozen weights and inability to perform causal reasoning or discard established axioms. Bridging the gap toward Artificial General Intelligence therefore requires a new architectural approach to implement true continual learning and move from association to simulation, as identified in recent work comparing LLM behavior to Judea Pearl's causal hierarchy.
- a16z1h 45m
Beyond Leaderboards: LMArena’s Mission to Make AI Reliable
Anjney Midha, Anastasios N. Angelopoulos, Wei-Lin Chiang, Ion Stoica
LM Arena has transformed from a static benchmark into a dynamic "humanity's exam" that evaluates over 280 AI models through real-time feedback from one million monthly users, effectively eliminating data contamination through fresh prompt generation. By treating evaluation as Reinforcement Learning rather than Supervised Learning, the platform utilizes techniques like "style control" and the open-sourced "Prompt-to-Leaderboard" router to achieve twice the performance-per-cost while maintaining academic neutrality. Looking forward, the organization plans to expand into private industry-specific Arenas and multi-modal agent testing while remaining committed to open-sourcing all data and research to preserve ecosystem trust.
- a16z1h 53m
Oppenheimer & the Catastrophe of Communism
Speakers Ben Thompson and associates draw a historical parallel between the Cold War atomic standoff and the current geopolitical tension over AI, arguing that similar ideological purges and anti-technology movements threaten to decelerate essential innovation. The discussion re-evaluates Cold War figures like Oppenheimer and McCarthy, asserting that the Manhattan Project's success relied on American industrial capacity and that Soviet espionage, rather than the bomb itself, prolonged a more devastating global conflict. Ultimately, the event warns that modern "anti-AI" regulations and cancel culture mirror the flawed moral frameworks of the past, urging a shift toward decentralized market-based solutions to avoid repeating historical errors.