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
Highly cited autism paper earns expression of concern over data duplications
The notice, published in Nature last week, also addressed an image duplication identified by a prominent research-integrity sleuth.
Highly cited autism paper earns expression of concern over data duplications
The notice, published in Nature last week, also addressed an image duplication identified by a prominent research-integrity sleuth.
Govern neurodata by how it’s used, not where it’s from
New neurodata laws will shape how researchers gather, share and reuse brain data. A use-based governance protects basic researchers and those whose data are being used, without freezing science.
Govern neurodata by how it’s used, not where it’s from
New neurodata laws will shape how researchers gather, share and reuse brain data. A use-based governance protects basic researchers and those whose data are being used, without freezing science.
How new technologies can bring primatologists and systems neuroscientists together
The two groups study the same behavioral phenomena yet rarely interact or read each other's work—a mutual blind spot that weakens both fields. New technologies offer a chance to bring them together.
How new technologies can bring primatologists and systems neuroscientists together
The two groups study the same behavioral phenomena yet rarely interact or read each other's work—a mutual blind spot that weakens both fields. New technologies offer a chance to bring them together.