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
Cortical area remixes macaques’ knowledge blocks to solve new problems
When monkeys draw complex shapes, their neural activity reflects patterns of activation elicited by drawing simpler, component shapes.
Cortical area remixes macaques’ knowledge blocks to solve new problems
When monkeys draw complex shapes, their neural activity reflects patterns of activation elicited by drawing simpler, component shapes.
Getting grants feels good, but giving them is even better
As director of grants management at the Cure Alzheimer’s Fund, Kaela Singleton bets on bold science and shares in the joy of discovery.
Getting grants feels good, but giving them is even better
As director of grants management at the Cure Alzheimer’s Fund, Kaela Singleton bets on bold science and shares in the joy of discovery.
When autistic kids grow up, Chapter 3: Would there be data?
Tempest McDonald takes a postdoctoral position at Vanderbilt University. Researching her paper accusing the National Institutes of Health of discrimination threatens everything she has built.
When autistic kids grow up, Chapter 3: Would there be data?
Tempest McDonald takes a postdoctoral position at Vanderbilt University. Researching her paper accusing the National Institutes of Health of discrimination threatens everything she has built.