Percy Liang
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Percy Liang, Professor, Stanford; Director, Center for Research on Foundation Models (CRFM) (United States), ranks #412/500 on the Power & Influence Index (44.4). Greatest lever: AI power (62.0, Strong). Entrenchment 64/100; net worth $0bn.
Dimension read
| Dimension | Value | Standing | What a high vs low value means, and where Percy Liang sits |
|---|---|---|---|
| PII Power & Influence (PII) | 44.4 | Moderate · #412/635 | Mid-pack. High would mean near the apex of civilizational influence; low would mean lower relative influence within this elite set. ▲ high: near the apex of civilizational influence · ▼ low: lower relative influence within this elite set |
| Economic power Economic power | 40.0 | Developing · #539/635 | Low here, limited economic control. ▲ high: controls vast wealth and companies · ▼ low: limited economic control |
| Political power Political power | 34.0 | Developing · #505/635 | Low here, little formal political power. ▲ high: commands states, law or policy · ▼ low: little formal political power |
| AI power AI power | 62.0 | Strong · #181/635 | High here, shapes or controls the trajectory of AI. ▲ high: shapes or controls the trajectory of AI · ▼ low: limited sway over AI's direction |
| Platform reach Platform reach | 52.0 | Moderate · #281/635 | Mid-pack. High would mean commands a vast audience or network; low would mean limited direct reach. ▲ high: commands a vast audience or network · ▼ low: limited direct reach |
| Institutional control Institutional control | 60.0 | Developing · #423/635 | Low here, limited institutional control. ▲ high: controls pivotal institutions and capital · ▼ low: limited institutional control |
| Entrenchment / tenure Entrenchment / tenure | 64.0 | Moderate · #296/635 | Mid-pack. High would mean power is locked in (indefinite or controlling stake); low would mean power is contingent, term-limited or contestable. ▲ high: power is locked in (indefinite or controlling stake) · ▼ low: power is contingent, term-limited or contestable |
Strengths
- AI power (62.0, Strong), shapes or controls the trajectory of AI.
Risk factors
- Significant but balanced influence with no single dominant lever.
AI worldview
Ideas & positions
Percy Liang is a leading figure in the development and study of foundation models, which he defines as large-scale machine learning models that can be adapted to a wide range of tasks. He emphasizes the importance of transparency and trustworthiness in AI systems, advocating for rigorous benchmarking and evaluation through tools like HELM. Liang has also been involved in the creation of Together AI, a platform aimed at making AI more accessible and collaborative. While he does not explicitly take a strong stance on existential risk, his work suggests a focus on ensuring that AI systems are reliable and beneficial. He has not made significant public statements on open vs closed models or regulation, but his emphasis on transparency implies a preference for openness and accountability.
What shapes the view
Liang's academic background in computer science and his experience at Stanford have shaped his technical approach to AI. His work on foundation models and benchmarking reflects a commitment to scientific rigor and the practical application of AI research. His involvement in Together AI indicates a belief in the democratization of AI technology and the importance of collaboration among researchers and developers.
The AI-powered future they see
Liang envisions a future where AI systems are more transparent, reliable, and accessible. He promotes the idea that foundation models can serve as versatile tools for a wide range of applications, from natural language processing to computer vision. His work suggests a future where AI is integrated into various domains, enhancing efficiency and solving complex problems, while maintaining a focus on ethical considerations and user trust.