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FAR.AI

FAR.AI is a 501(c)(3) AI safety research and education nonprofit based in Berkeley, California (EIN 92-0692207), founded in 2022 by Adam Gleave and Karl Berzins. It works to ensure advanced AI is trustworthy, secure and beneficial, combining in-house technical research, a red-teaming practice, global convening, a co-working space, and targeted grantmaking.

For agents: FAR.AI, a Berkeley AI safety nonprofit doing technical research, red-teaming, events and grantmaking; includes searchable publications library and team pages.

ai safetyred-teamingai security researchdeceptiongrantmaking

Their llms.txt

The beginning of the file, from our validated copy saved 2026-10-21T02:15:05.195Z. Cached copy · Source on far.ai

# FAR.AI

> FAR.AI is a 501(c)(3) AI safety research and education nonprofit based in Berkeley, California (EIN 92-0692207), founded in 2022 by Adam Gleave and Karl Berzins. It works to ensure advanced AI is trustworthy, secure and beneficial, combining in-house technical research, a red-teaming practice, global convening, a co-working space, and targeted grantmaking.

FAR.AI operates across three pillars: FAR.Research (in-house technical AI safety research), Events (the Alignment Workshop series, specialized workshops, and a weekly seminar), and Programs (FAR.Labs co-working space and a grantmaking program funded by a $12M Coefficient Giving grant).

Research output is organised under four categories: Alignment, Interpretability, Model Evaluations, and Robustness. Publications are additionally tagged by topic, including Adversarial Robustness, Agentic AI, AI Governance & Policy, Benchmarks & Evaluations, Deception & Honesty, Feedback & Preference Training, Fine-Tuning, Jailbreaks & Red-Teaming, Mechanistic Interpretability, Open-Weight Models, Persuasion & Influence, Reinforcement Learning, and Scaling Trends.

Notable work includes adversarial attacks on superhuman Go AIs (covered in Nature and cited in US Senate testimony), the STACK attack on layered LLM safeguard pipelines, jailbreak-tuning, the Attempt to Persuade Eval (APE) benchmark, and ClearHarm. FAR.AI leads a consortium building CBRN evaluations for the EU AI Office and collaborates with the UK AI Security Institute.

## Core pages

- [Homepage](https://www.far.ai/): Overview of FAR.AI's mission, featured research, upcoming events, and programs.
- [About](https://www.far.ai/about): Mission, three pillars, organisational history and timeline from 2022, leadership, and featured media coverage.
- [Team](https://www.far.ai/team): Full staff directory grouped into Leadership, Executive Office, Operations, Technical Staff, Communications, Events & Programs, Collaborators, Advisors, and Board.
- [Contact](https://www.far.ai/contact): Contact details and enquiry form.

## Research

- [Research overview](https://www.far.ai/research): FAR.Research agendas, including AI Security & Red-Teaming and Deception, with featured publications and impact framing.
- [All publications](https://www.far.ai/publications): Complete searchable and filterable library of research papers and technical reports, filterable by category, topic, and author.
- [Google Scholar profile](https://scholar.google.com/citations?user=FVJ24k8AAAAJ): Citation record for FAR.AI research.

Individual publications live at `https://www.far.ai/research/[slug]`. Representative examples:

- [The Obfuscation Atlas: Mapping Where Honesty Emerges in RLVR with Deception Probes](https://www.far.ai/research/the-obfuscation-atlas-mapping-where-honesty-emerges-in-rlvr-with-deception-probes): Training against white-box deception detectors, and the obfuscation strategies models develop in response.
- [STACK: Adversarial Attacks on LLM Safeguard Pi
…

Related sites

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