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Percy Liang

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Influence report · generated from Percy Liang's indicators

Percy Liang, full AI read

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.

Role
Professor, Stanford; Director, Center for Research on Foundation Models (CRFM)
Country
United States
Category
AI researcher/lab
Net worth / capital
$0bn
Controls
Foundation-model benchmarking (HELM); coined 'foundation models'; trustworthy/transparent AI; co-founder Together AI

Dimension read

DimensionValueStandingWhat a high vs low value means, and where Percy Liang sits
PII Power & Influence (PII)44.4Moderate · #412/635Mid-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 power40.0Developing · #539/635Low here, limited economic control.
▲ high: controls vast wealth and companies  ·  ▼ low: limited economic control
Political power Political power34.0Developing · #505/635Low here, little formal political power.
▲ high: commands states, law or policy  ·  ▼ low: little formal political power
AI power AI power62.0Strong · #181/635High 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 reach52.0Moderate · #281/635Mid-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 control60.0Developing · #423/635Low here, limited institutional control.
▲ high: controls pivotal institutions and capital  ·  ▼ low: limited institutional control
Entrenchment / tenure Entrenchment / tenure64.0Moderate · #296/635Mid-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.
These are model outputs and scenarios, not forecasts of actual outcomes. This platform measures access to, utilization of, and leverage from cognitive infrastructure, not intelligence. No causality or certainty is claimed.

AI worldview

Contingent / balancedconfidence 0.7

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.

DystopianContingentUtopian
An AI-generated synthesis of the public record (statements, essays, interviews, papers), not statements by the person; positions evolve and the model's knowledge has a cutoff.