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
Methodological flaw may upend network mapping tool
The lesion network mapping method, used to identify disease-specific brain networks for clinical stimulation, produces a nearly identical network map for any given condition, according to a new study.
Methodological flaw may upend network mapping tool
The lesion network mapping method, used to identify disease-specific brain networks for clinical stimulation, produces a nearly identical network map for any given condition, according to a new study.
Common and rare variants shape distinct genetic architecture of autism in African Americans
Certain gene variants may have greater weight in determining autism likelihood for some populations, a new study shows.
Common and rare variants shape distinct genetic architecture of autism in African Americans
Certain gene variants may have greater weight in determining autism likelihood for some populations, a new study shows.
Bringing African ancestry into cellular neuroscience
Two independent teams in Africa are developing stem cell lines and organoids from local populations to explore neurodevelopmental and neurodegenerative conditions.
Bringing African ancestry into cellular neuroscience
Two independent teams in Africa are developing stem cell lines and organoids from local populations to explore neurodevelopmental and neurodegenerative conditions.