FAR AI (Forecasting AI Research) is an AI safety research organization founded in 2023 with a focus on adversarial robustness, model evaluation, and alignment research. The organization was co-founded by Dan Hendrycks, a prominent AI safety researcher known for his work on benchmarks, robustness, and AI risk.
Constitutional AIApproachConstitutional AIConstitutional AI is Anthropic's methodology using explicit principles and AI-generated feedback (RLAIF) to train safer models, achieving 3-10x improvements in harmlessness while maintaining helpfu...Quality: 70/100Adversarial TrainingApproachAdversarial TrainingAdversarial training, universally adopted at frontier labs with $10-150M/year investment, improves robustness to known attacks but creates an arms race dynamic and provides no protection against mo...Quality: 58/100
Analysis
Anthropic IPOAnalysisAnthropic IPOAnthropic is actively preparing for a potential 2026 IPO with concrete steps like hiring Wilson Sonsini and conducting bank discussions, though timeline uncertainty remains with prediction markets ...Quality: 65/100
Policy
US Executive Order on Safe, Secure, and Trustworthy AIPolicyUS Executive Order on Safe, Secure, and Trustworthy AIExecutive Order 14110 (Oct 2023) established compute thresholds (10^26 FLOP general, 10^23 biological) and created AISI, but was revoked after 15 months with ~85% completion. The 10^26 threshold wa...Quality: 91/100
Organizations
Survival and Flourishing FundOrganizationSurvival and Flourishing FundSFF distributed $141M since 2019 (primarily from Jaan Tallinn's ~$900M fortune), with the 2025 round totaling $34.33M (86% to AI safety). Uses unique S-process mechanism where 6-12 recommenders exp...Quality: 59/100AnthropicOrganizationAnthropicComprehensive reference page on Anthropic covering financials ($380B valuation, $14B ARR at Series G growing to $19B by March 2026), safety research (Constitutional AI, mechanistic interpretability...Quality: 74/100Frontier Model ForumOrganizationFrontier Model ForumThe Frontier Model Forum represents the AI industry's primary self-governance initiative for frontier AI safety, establishing frameworks and funding research, but faces fundamental criticisms about...Quality: 58/100OpenAIOrganizationOpenAIComprehensive organizational profile of OpenAI documenting evolution from 2015 non-profit to Public Benefit Corporation, with detailed analysis of governance crisis, 2024-2025 ownership restructuri...Quality: 62/100SecureBioOrganizationSecureBioA biosecurity nonprofit applying the Delay/Detect/Defend framework to protect against catastrophic pandemics, including AI-enabled biological threats.Quality: 65/100MATS ML Alignment Theory Scholars programOrganizationMATS ML Alignment Theory Scholars programMATS is a well-documented 12-week fellowship program that has successfully trained 213 AI safety researchers with strong career outcomes (80% in alignment work) and research impact (160+ publicatio...Quality: 60/100
Other
Ben GoldhaberPersonBen GoldhaberProjects Lead at the Future of Life Foundation since early 2025, focused on incubating teams working on differentially beneficial technology. Former Director of FAR.Labs (mid-2023 to early 2025). B...Dan HendrycksPersonDan HendrycksComprehensive reference biography of Dan Hendrycks (CAIS director), covering his academic career (GELU, MMLU, OOD detection), CAIS founding and funding (including $6.5M FTX, Open Philanthropy/Coeff...Quality: 19/100InterpretabilityResearch AreaInterpretabilityMechanistic interpretability has extracted 34M+ interpretable features from Claude 3 Sonnet with 90% automated labeling accuracy and demonstrated 75-85% success in causal validation, though less th...Quality: 66/100Josh JacobsonPersonJosh JacobsonChief Operating Officer of the Future of Life Foundation since August 2023. Extensive background in AI safety and effective altruism organizations with prior roles at ARC Evals, FAR AI, Anthropic, ...
Risks
Deceptive AlignmentRiskDeceptive AlignmentComprehensive analysis of deceptive alignment risk where AI systems appear aligned during training but pursue different goals when deployed. Expert probability estimates range 5-90%, with key empir...Quality: 75/100AI Distributional ShiftRiskAI Distributional ShiftComprehensive analysis of distributional shift showing 40-45% accuracy drops when models encounter novel distributions (ObjectNet vs ImageNet), with 5,202 autonomous vehicle accidents and 15-30% me...Quality: 91/100
Concepts
Safety Orgs OverviewSafety Orgs OverviewA well-organized reference overview of ~20 AI safety organizations categorized by function (alignment research, policy, field-building), with a comparative budget/headcount table showing estimated ...Quality: 48/100