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
New projectome captures ‘complex beast’ of serotonin system in mice
The whole-brain map—the first of its kind in a vertebrate—identifies five distinct neuron groups.
New projectome captures ‘complex beast’ of serotonin system in mice
The whole-brain map—the first of its kind in a vertebrate—identifies five distinct neuron groups.
Silent, motion-resistant fMRI expands scans in behaving mice
The method, called SORDINO, captures brain images in animals while they move and interact.
Silent, motion-resistant fMRI expands scans in behaving mice
The method, called SORDINO, captures brain images in animals while they move and interact.
Autism-linked variants converge on two molecular patterns in mouse brains
Gene activity across 17 autism mouse models occurs in either of two opposing transcriptomic states, supporting the idea that diverse genetic changes may converge on a few recurring biological patterns.
Autism-linked variants converge on two molecular patterns in mouse brains
Gene activity across 17 autism mouse models occurs in either of two opposing transcriptomic states, supporting the idea that diverse genetic changes may converge on a few recurring biological patterns.