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
Grant review needs reform. How about we add an element of chance?
A process that uses a lottery system saves time, reduces strategic resubmission and accepts that, above a quality threshold, luck has always played a part in science funding.
Grant review needs reform. How about we add an element of chance?
A process that uses a lottery system saves time, reduces strategic resubmission and accepts that, above a quality threshold, luck has always played a part in science funding.
Fly neurons carry molecular signatures of their origins
The pattern of transcription factors a Drosophila neuron expresses offers clues to its lineage and birth order—and ultimately how neural circuits emerge.
Fly neurons carry molecular signatures of their origins
The pattern of transcription factors a Drosophila neuron expresses offers clues to its lineage and birth order—and ultimately how neural circuits emerge.
Polarized cortical organoids mimic the brain’s regional organization
The organoids show region-specific gene-expression changes that match those observed during fetal development.
Polarized cortical organoids mimic the brain’s regional organization
The organoids show region-specific gene-expression changes that match those observed during fetal development.