Transluce: Fund Scalable Democratic Oversight of AI

Evitable: a new public-facing AI risk non-profit

Our mission is to inform and organize the public to confront societal-scale risks of AI, and put an end to the reckless race to develop superintelligent AI.

SOTA Public Research Database + Search Tool

Unlocking the paradigm of agents + SQL + compositional vector search

Forethought

Research on how to navigate the transition to a world with superintelligent AI systems

Reducing Risk in AI Safety Through Expanding Capacity.

Shallow Review of AI Governance: Mapping the Technical–Policy Implementation Gap

Identifying operational bottlenecks and cruxes between alignment proposals and executable governance.

Making AI Safety Understandable to Everyday Audiences

Translating AI’s biggest threats into videos anyone can understand: AGI, misalignment, and job loss explained.

Building an Educational Universe Through Animals and Longtermist Storytelling

A global IP project reimagining ecology and future technology and institutions through character-driven narratives.

Formal Certification Technologies for AI Safety

Developing the software infrastructure to make AI systems safe, with formal guarantees

Building Frontier AI Governance Capacity in Africa (Pilot Phase)

A pilot to build policy and technical capacity for governing high-risk AI systems in Africa

Runway till January: Amplify's funding ask to market EA & AI Safety 

Help us solve the talent and funding bottleneck for EA and AIS.

From Nobel Signatures to Binding Red Lines: The 2026 Diplomatic Sprint

Leveraging 12 Nobel signatories to harmonize lab safety thresholds and secure an international agreement during the 2026 diplomatic window.

Alignment as epistemic system governance under compression

We reframe the alignment problem as the problem of governing meaning and intent when they cannot be fully expressed.

Retroactive: Presenting a poster at the ICML technical AI governance workshop

Boundary-Mediated Models of LLM Hallucination and Alignment

A mechanistic, testable framework explaining LLM failure modes via boundary writes and attractor dynamics

Protocol-Level Interaction Risk Assessment and Mitigation (UIVP)

A bounded protocol audit and implementation-ready mitigation for intent ambiguity and escalation in deployed LLM systems.

TimeAlign v2: contamination-aware evals for small models (16GB GPUs)

Reusable, low-compute benchmarking that detects data leakage, outputs “contamination cards,” and improves calibration reporting.

Operating Capital for AI Safety Evaluation Infrastructure

Enabling rapid deployment of specialized engineering teams for critical AI safety evaluation projects worldwide

Disentangling Political Bias from Epistemic Integrity in AI Systems

An Integrative Framework for Auditing Political Preferences and Truth-Seeking in AI Systems

Guaranteed Safe AI Seminars 2026

Seminars on quantitative/guaranteed AI safety (formal methods, verification, mech-interp), with recordings, debates, and the guaranteedsafe.ai community hub.