AI RESEARCHERS

RESEARCHERS

• Aidan GomezCo-wrote the Transformer paper, then tried to turn the architecture into an independent company with Cohere.
• Ajeya CotraTransformative-AI forecasts, METR, technical safety, and years spent trying to put numbers on loss-of-control risk.
• Andrej KarpathyHinton's classroom → OpenAI → Tesla → OpenAI again → teaching the internet how the machines work.
• Andrew NgGoogle Brain, Baidu, Coursera, DeepLearning.AI — one of the people who turned modern AI into a mass profession.
• Anil SethControlled hallucination, predictive processing, biological naturalism — and the argument that silicon may not get consciousness for free.
• Aravind SrinivasPerplexity wants to rebuild the web's front door around answers. Publisher fights came with the territory.
• Arthur MenschFrench math, DeepMind, Mistral, billions in Paris — and Europe's bid for its own frontier lab.
• Binyuan HuiQwen-Coder, OpenDevin, reasoning — pushing open models toward autonomous software engineering.
• Bowen YuThe job: turn raw Qwen into something that follows instructions, reasons, and behaves.
• Chris OlahNeural-network visualization → mechanistic interpretability: trying to see what giant models are doing inside.
• Dario AmodeiClaude in one hand, doom warnings in the other. Anthropic's CEO keeps turning safety into an industry power struggle.
• David SilverAlphaGo → AlphaZero → a new bet that machines should learn from experience.
• Daya GuoCode intelligence → DeepSeek-Coder → reasoning models. His road to the frontier started with software.
• Demis HassabisGemini, scientific breakthroughs, and AGI forecasts: DeepMind's research boss keeps moving between science fiction and science.
• Fei-Fei LiImageNet taught machines to see. Now Fei-Fei Li wants them to understand 3D space.
• Geoffrey HintonBuilt neural networks through the wilderness, won the Nobel, then started warning about what he helped unleash.
• Guillaume LampleUnsupervised translation, Meta AI, LLaMA — then out the door to co-found Mistral.
• Ilya SutskeverOpenAI history, superintelligence, safety, and enough research mystique to make every move look like a signal.
• Jeff DeanGoogle's infrastructure → Google Brain → Gemini: the engineer whose systems sit underneath modern AI.
• Jeremy HowardKaggle, fast.ai, ULMFiT — a career spent dragging deep learning out of elite labs and into ordinary hands.
• Jingren ZhouMicrosoft Research → Alibaba Cloud → Tongyi → Qwen: the executive-scientist linking China's cloud stack to its models.
• John JumperAlphaFold turned protein structure into a Nobel-winning AI problem.
• Junyang LinQwen hit billion-download scale. Then its technical leader walked away at the peak.
• Lex FridmanMIT, machine-learning research, and interviews long enough for the AI era to narrate itself in real time.
• Noam ShazeerTransformer, mixture-of-experts, Character.AI — then a 2026 jump from Google back into the OpenAI race.
• Stuart RussellWrote the standard AI textbook, then spent years arguing the textbook's machines need a better control problem.
• Thomas WolfTransformers, BLOOM, Hugging Face: the open-model infrastructure that made frontier AI feel downloadable.
• Timothée LacroixMath, recommenders, Meta AI, LLaMA — now the engineering operation behind Mistral.
• Yann LeCunConvolutional nets, FAIR, NYU — and a long-running insistence that chatbots are not the endgame.
• Yoshua BengioTuring Award, frontier-risk warnings, and a new lab built around making AI safer.