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
Organoids missing the TSC2 gene form rogue astrocytes; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 28 September.
Organoids missing the TSC2 gene form rogue astrocytes; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 28 September.
Cerebellar neurons reorient brain activity to differentiate similar behaviors
The findings provide a new perspective on how granule cells help to generalize learning across tasks.
Cerebellar neurons reorient brain activity to differentiate similar behaviors
The findings provide a new perspective on how granule cells help to generalize learning across tasks.
Revisiting the neural correlates of consciousness
Life happens in real time, but experience may be composed in ragtime—like the music genre, full of offbeat notes and uneven rhythms. The assumption that waking life consists of a “stream” of conscious representations has inadvertently led consciousness science to its current impasse.
Revisiting the neural correlates of consciousness
Life happens in real time, but experience may be composed in ragtime—like the music genre, full of offbeat notes and uneven rhythms. The assumption that waking life consists of a “stream” of conscious representations has inadvertently led consciousness science to its current impasse.