May 7, 2024 - 4:00 pm
Bio: Professor Bruno Olshausen is a Professor in the Helen Wills Neuroscience Institute, the School of Optometry, and has a below-the-line affiliated appointment in EECS. He holds B.S. and M.S. degrees in Electrical Engineering from Stanford University, and a Ph.D. in Computation and Neural Systems...
April 2, 2024 - 4:00 pm
Singleton Auditorium (46-3002)
Bio: Melanie Mitchell is a Professor at the Santa Fe Institute. Her current research focuses on conceptual abstraction, analogy-making, and visual recognition in artificial intelligence systems.
Melanie is the author or editor of six books and numerous scholarly papers in the fields of artificial...
Melanie is the author or editor of six books and numerous scholarly papers in the fields of artificial...
March 12, 2024 - 4:00 pm
Singleton Auditorium (46-3002)
Bio: I am interested in developing mathematical models of higher level cognition, and understanding the formal principles that underlie our ability to solve the computational problems we face in everyday life. My current focus is on inductive problems, such as probabilistic reasoning, learning...
February 6, 2024 - 4:00 pm
Singleton Auditorium (46-3002)
Research in the Niv lab focuses on the neural and computational processes underlying reinforcement learning and decision-making. We study the ongoing day-to-day processes by which animals and humans learn from trial and error, without explicit instructions, to predict future events and to act upon...
December 5, 2023 - 4:00 pm
Singleton Auditorium (46-3002)
Bio: Daniel Wolpert FMedSci FRS. Daniel qualified as a medical doctor in 1989. He worked with John Stein and Chris Miall in the Physiology Department of Oxford University where he received his D.Phil. in 1992. He worked as a postdoctoral fellow in the Department of Brain and Cognitive Sciences at ...
November 14, 2023 - 4:00 pm
Singleton Auditorium (46-3002)
Bio:
Peter Dayan studied mathematics at Cambridge University and received his doctorate from the University of Edinburgh. After postdoctoral research at the Salk Institute and the University of Toronto he moved to the Massachusetts Institute of Technology (MIT) in Boston as assistant professor in...
Peter Dayan studied mathematics at Cambridge University and received his doctorate from the University of Edinburgh. After postdoctoral research at the Salk Institute and the University of Toronto he moved to the Massachusetts Institute of Technology (MIT) in Boston as assistant professor in...
October 6, 2023 - 3:15 pm
MIT Campus
The dream of understanding the mind and the brain and replicating human intelligence in machines was at the core of several new fields created at MIT during the ‘50s and ‘60s, including information theory, cybernetics, and Artificial Intelligence. The same dream was at the core of the NSF-funded,...
September 26, 2023 - 4:00 pm
McGovern Reading Room (46-5165)
Moderator: Ila Fiete; Panelists: Akshay Rangamani, Tomer Galanti, Sugandha Sharma and Sarthak Chandra
Abstract:
This discussion will feature panelists from the Poggio and Fiete labs describing ongoing work on deep classifiers and hippocampal-inspired networks, respectively. Following brief presentations by each panelist, Ila Fiete will steer a discussion to explore strengths, limitations and...
This discussion will feature panelists from the Poggio and Fiete labs describing ongoing work on deep classifiers and hippocampal-inspired networks, respectively. Following brief presentations by each panelist, Ila Fiete will steer a discussion to explore strengths, limitations and...
September 19, 2023 - 4:00 pm
MIBR Reading Room 46-5165
Aran Nayebi, ICoN Postdoctoral Fellow at MIT
Abstract:
Deep neural networks trained on high-variation tasks ("goals”) have had immense success as predictive models of the human and non-human primate visual pathways. More specifically, a positive relationship has been observed between model performance on ImageNet categorization and neural...
Deep neural networks trained on high-variation tasks ("goals”) have had immense success as predictive models of the human and non-human primate visual pathways. More specifically, a positive relationship has been observed between model performance on ImageNet categorization and neural...
September 18, 2023 - 12:00 pm
Researchers use multiple AI models to collaborate, debate, and improve their reasoning abilities to advance the performance of LLMs while increasing accountability and factual accuracy.
Rachel Gordon | MIT CSAIL
An age-old adage, often introduced to us during our formative years, is designed to nudge us beyond our self-centered, nascent minds: "Two heads are better than one." This proverb encourages collaborative thinking and highlights the...
September 12, 2023 - 4:00 pm
Singleton Auditorium (46-3002)
Prof. Michael Hasselmo; Director, Center for Systems Neuroscience; Boston University
Abstract: Recordings of neurons in cortical structures in behaving rodents show responses to dimensions of space and time relevant to encoding and retrieval of spatiotemporal trajectories of behavior in episodic memory. This includes the coding of spatial location by grid cells in entorhinal cortex...
August 30, 2023 - 2:45 pm
With hopes and fears about this technology running wild, it's time to agree on what it can and can't do.
By Will Douglas Heaven
When Taylor Webb played around with GPT-3 in early 2022, he was blown away by what OpenAI’s large language model appeared to be able to do. Here was a neural network trained only to predict the next word in a block of text—a jumped-up autocomplete. And yet it gave correct answers to many of the abstract problems that...
August 17, 2023 - 12:00 pm
John Werner - Contributor [I am an MIT Senior Fellow, 5x-founder & VC investing in AI]
Get ready for a lot of math…!
We have sort of an intuitive understanding of a big need in artificial intelligence and machine learning, which has to do with making sure that systems converge well, and that data is oriented the right way. Also, that we understand what these tools are doing, that we can look under the hood.
A lot of us have already heard of...
August 16, 2023 - 12:15 pm
Three graduate students forged a path to the same Picower Institute lab through participating in the MIT Summer Research Program in Biology and Neuroscience.
David Orenstein | The Picower Institute for Learning and Memory
Doctoral studies at MIT aren’t a calling for everyone, but they can be for anyone who has had opportunities to discover that science and technology research is their passion and to build the experience and skills to succeed....
July 20, 2023 - 10:45 am
Pictures conjured by the mind’s eye lack detail, despite how vividly you picture them
By Simon Makin
Here were the simple instructions given by a Harvard University assistant professor to people participating in a recent cognitive science study:
“Imagine the following scene. Visualize it in your mind’s eye, as vividly as you can: a person walks into a room and knocks a ball off a table.”
The professor, Tomer Ullman, then asked those in the...