Large language models
Recent articles
How artificial agents can help us understand social recognition
Neuroscience is chasing the complexity of social behavior, yet we have not answered the simplest question in the chain: How does a brain know “who is who”? Emerging multi-agent artificial intelligence may help accelerate our understanding of this fundamental computation.
How artificial agents can help us understand social recognition
Neuroscience is chasing the complexity of social behavior, yet we have not answered the simplest question in the chain: How does a brain know “who is who”? Emerging multi-agent artificial intelligence may help accelerate our understanding of this fundamental computation.
The BabyLM Challenge: In search of more efficient learning algorithms, researchers look to infants
A competition that trains language models on relatively small datasets of words, closer in size to what a child hears up to age 13, seeks solutions to some of the major challenges of today’s large language models.
The BabyLM Challenge: In search of more efficient learning algorithms, researchers look to infants
A competition that trains language models on relatively small datasets of words, closer in size to what a child hears up to age 13, seeks solutions to some of the major challenges of today’s large language models.
‘Digital humans’ in a virtual world
By combining large language models with modular cognitive control architecture, Robert Yang and his collaborators have built agents that are capable of grounded reasoning at a linguistic level. Striking collective behaviors have emerged.
‘Digital humans’ in a virtual world
By combining large language models with modular cognitive control architecture, Robert Yang and his collaborators have built agents that are capable of grounded reasoning at a linguistic level. Striking collective behaviors have emerged.
Are brains and AI converging?—an excerpt from ‘ChatGPT and the Future of AI: The Deep Language Revolution’
In his new book, to be published next week, computational neuroscience pioneer Terrence Sejnowski tackles debates about AI’s capacity to mirror cognitive processes.
Are brains and AI converging?—an excerpt from ‘ChatGPT and the Future of AI: The Deep Language Revolution’
In his new book, to be published next week, computational neuroscience pioneer Terrence Sejnowski tackles debates about AI’s capacity to mirror cognitive processes.
Explore more from The Transmitter
Future remains uncertain for U.S. federal funding of behavioral, cognitive science
The National Science Foundation did not include any solicitations for its social, behavioral and economic sciences directorate in its latest round of funding opportunities, nor replace any outgoing program officers—which poses an existential threat for the program, says nonprofit executive Wendy Naus.
Future remains uncertain for U.S. federal funding of behavioral, cognitive science
The National Science Foundation did not include any solicitations for its social, behavioral and economic sciences directorate in its latest round of funding opportunities, nor replace any outgoing program officers—which poses an existential threat for the program, says nonprofit executive Wendy Naus.
How energy determines where proteins are produced in neurons
Tatjana Tchumatchenko explains how mathematical modeling elucidates whether ion-channel proteins are produced locally in the soma or in the dendrites.
How energy determines where proteins are produced in neurons
Tatjana Tchumatchenko explains how mathematical modeling elucidates whether ion-channel proteins are produced locally in the soma or in the dendrites.
Wouldn’t you like to know? A mouse would
Mice seek information for curiosity’s sake—and their desire for knowledge versus a payout is represented distinctly in the brain, new findings suggest.
Wouldn’t you like to know? A mouse would
Mice seek information for curiosity’s sake—and their desire for knowledge versus a payout is represented distinctly in the brain, new findings suggest.