[
 {
  "id": "safety-interp",
  "name": "Safety and interpretability",
  "inside": [
   "llm"
  ],
  "text": "The second-largest research community after scaling, and almost entirely a program inside camp 1: it studies the models the scaling labs build. Mechanistic interpretability reverse-engineers circuits and features; alignment and control research asks how to keep a capable model doing what it was asked. A PhD applicant looking for this will not find it on the fault lines, because it does not disagree with camp 1 about how intelligence works, only about what to do with it.",
  "orgs": [
   {
    "name": "Anthropic interpretability team",
    "url": "https://transformer-circuits.pub",
    "lab": "anthropic",
    "note": "Circuits, features, 'mapping the mind' of Claude"
   },
   {
    "name": "Goodfire",
    "url": "https://www.goodfire.ai",
    "note": "Interpretability as a product"
   },
   {
    "name": "Transluce",
    "url": "https://transluce.org",
    "note": "Nonprofit; open tools for understanding model behavior"
   },
   {
    "name": "Redwood Research",
    "url": "https://www.redwoodresearch.org",
    "note": "AI control: safety that holds even if the model is scheming"
   },
   {
    "name": "UK AI Security Institute",
    "url": "https://www.aisi.gov.uk",
    "note": "State evaluator of frontier models"
   },
   {
    "name": "Center for Human-Compatible AI",
    "url": "https://en.wikipedia.org/wiki/Stuart_J._Russell",
    "note": "Russell's Berkeley center; assistance games"
   },
   {
    "name": "EleutherAI",
    "url": "https://www.eleuther.ai",
    "note": "Open models and interpretability research"
   }
  ],
  "sources": [
   {
    "url": "https://en.wikipedia.org/wiki/Mechanistic_interpretability",
    "date": "2026-09-05",
    "title": "Mechanistic interpretability",
    "publisher": "Wikipedia"
   },
   {
    "url": "https://www.anthropic.com/research/mapping-mind-language-model",
    "date": "2024-05-21",
    "title": "Mapping the Mind of a Large Language Model",
    "publisher": "Anthropic"
   },
   {
    "url": "https://en.wikipedia.org/wiki/AI_Security_Institute",
    "date": "2026-09-05",
    "title": "AI Security Institute",
    "publisher": "Wikipedia"
   }
  ]
 },
 {
  "id": "evals",
  "name": "Evaluations and forecasting",
  "inside": [
   "llm",
   "robot"
  ],
  "text": "Whoever measures the field shapes it. Benchmarks, arenas and forecasting shops decide which claims count, and their numbers are what the money watches. They sit across camps 1 and 5 because that is where the products are.",
  "orgs": [
   {
    "name": "METR",
    "url": "https://metr.org",
    "note": "Task-horizon measurements of autonomous agents"
   },
   {
    "name": "Epoch AI",
    "url": "https://epoch.ai",
    "note": "Compute, data and capability trends"
   },
   {
    "name": "LMArena",
    "url": "https://lmarena.ai",
    "note": "Crowd-sourced pairwise model rankings"
   },
   {
    "name": "Artificial Analysis",
    "url": "https://artificialanalysis.ai",
    "note": "Independent speed, price and quality benchmarks"
   },
   {
    "name": "ARC Prize",
    "url": "https://arcprize.org",
    "note": "The one benchmark built to resist scaling"
   },
   {
    "name": "SWE-bench",
    "url": "https://www.swebench.com",
    "note": "Real GitHub issues as the coding-agent yardstick"
   },
   {
    "name": "Apollo Research",
    "url": "https://www.apolloresearch.ai",
    "note": "Evaluations for deception and scheming"
   }
  ],
  "sources": [
   {
    "url": "https://en.wikipedia.org/wiki/METR",
    "date": "2026-09-05",
    "title": "METR",
    "publisher": "Wikipedia"
   },
   {
    "url": "https://en.wikipedia.org/wiki/LMArena",
    "date": "2026-09-05",
    "title": "LMArena",
    "publisher": "Wikipedia"
   }
  ]
 },
 {
  "id": "agents",
  "name": "Agents and scaffolding",
  "inside": [
   "llm"
  ],
  "text": "Tool use, memory, long-horizon planning and the harnesses that turn a model into a worker. Nearly all of it is engineering on top of camp 1 models rather than a new theory of intelligence, which is why the atlas does not list it as a camp. Camp 4 argues that real agency needs learning from the stream itself; this layer bets it can be scaffolded instead.",
  "orgs": [
   {
    "name": "Anthropic (Claude Code, computer use)",
    "url": "https://www.anthropic.com",
    "lab": "anthropic",
    "note": "Agentic coding and computer use"
   },
   {
    "name": "OpenAI (Operator, Codex)",
    "url": "https://openai.com",
    "lab": "openai",
    "note": "Browser and coding agents"
   },
   {
    "name": "Reflection AI",
    "url": "https://reflection.ai",
    "lab": "reflection-ai",
    "note": "Autonomous coding agents from AlphaGo alumni"
   },
   {
    "name": "Periodic Labs",
    "url": "https://periodic.com",
    "lab": "periodic-labs",
    "note": "Agents that run experiments"
   }
  ],
  "sources": [
   {
    "url": "https://en.wikipedia.org/wiki/Agentic_AI",
    "date": "2026-09-05",
    "title": "Agentic AI",
    "publisher": "Wikipedia"
   }
  ]
 },
 {
  "id": "inference",
  "name": "Inference hardware and serving",
  "inside": [
   "llm"
  ],
  "text": "The picks and shovels of camp 1 apart from NVIDIA: chips built for serving rather than training, and the clouds that rent them. Their bet is that the models are settled enough to build silicon around, which is itself a position in the scaling debate.",
  "orgs": [
   {
    "name": "Groq",
    "url": "https://groq.com",
    "note": "LPU inference chips"
   },
   {
    "name": "Cerebras",
    "url": "https://www.cerebras.ai",
    "note": "Wafer-scale chips; IPO filed"
   },
   {
    "name": "SambaNova",
    "url": "https://en.wikipedia.org/wiki/SambaNova_Systems",
    "note": "Dataflow chips for inference"
   },
   {
    "name": "Etched",
    "url": "https://en.wikipedia.org/wiki/Etched",
    "note": "Transformer-only ASIC; the purest bet that the architecture is final"
   },
   {
    "name": "Together AI",
    "url": "https://www.together.ai",
    "note": "Open-model serving cloud"
   },
   {
    "name": "Fireworks AI",
    "url": "https://en.wikipedia.org/wiki/Fireworks_AI",
    "note": "Inference platform"
   }
  ],
  "sources": [
   {
    "url": "https://en.wikipedia.org/wiki/Groq",
    "date": "2026-09-05",
    "title": "Groq",
    "publisher": "Wikipedia"
   },
   {
    "url": "https://en.wikipedia.org/wiki/Cerebras",
    "date": "2026-09-05",
    "title": "Cerebras",
    "publisher": "Wikipedia"
   }
  ]
 }
]