Josh Tenenbaum – Computational Cognitive Science
Professor Department of Brain and Cognitive Sciences Massachusetts Institute of Technology Home Page Email: jbt AT mit DOT edu Phone: 617-452-2010 (office), 617-253-8335 (fax) Mail: Building 46-4015, 77 Massachusetts Avenue, Cambridge, MA 02139 Curriculum Vitae (as of June 2020) My colleagues and I in the Computational Cognitive Science group study one of the most basic and distinctively human aspects of cognition: the ability to learn so much about the world, rapidly and flexibly. Given just a few relevant experiences, even young children can infer the meaning of a new word, the hidden properties of an object or substance, or the existence of a new causal relation or social rule. These inferences go far beyond the data given: after seeing three or four examples of “horses”, a two-year-old will confidently judge whether any new entity is a horse or not, and she will be mostly correct, except for the occasional donkey or camel. We want to understand these everyday inductive leaps in com
Josh Tenenbaum – Computational Cognitive Science Lab Skip to content Josh Tenenbaum Professor Department of Brain and Cognitive Sciences Massachusetts Institute of Technology Email: jbt AT mit DOT edu Phone: 617-452-2010 (office), 617-253-8335 (fax) Mail: Building 46-4015, 77 Massachusetts Avenue, Cambridge, MA 02139 Curriculum Vitae (as of April 2026) Research interests My colleagues and I in the Computational Cognitive Science group study one of the most basic and distinctively human aspects of cognition: the ability to learn so much about the world, rapidly and flexibly. Given just a
Explore this link on the map →related reading
- Intuitive statistics - Wikipediaen.wikipedia.org
- Building machines that learn and think like people | Behavioral and Brain Sciences | Cambridge Corecambridge.org
- Scaling in the service of reasoning & model-based ML | Yoshua Bengioyoshuabengio.org
- Andrej Karpathy — AGI is still a decade awaydwarkesh.com
- To Understand Language is to Understand Generalization | Eric Jangevjang.com
- General intelligence — LessWrongarbital.com
- Building a Reasoning Machine - Ph.D. thesis | Edward Huedwardjhu.com
- 9 Open Problems and Directions about Intelligencema-lab-berkeley.github.io
- Intelligence as efficient model building | Alex’s blogatelfo.github.io
- Deep learning as program synthesis — LessWronglesswrong.com
- Human-like Neural Nets by Catapulting · Gwern.netgwern.net
- LLMs and World Models, Part 1 - by Melanie Mitchellaiguide.substack.com