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
‘Push-pull’ recipe for neural wiring used in multiple brain regions
A versatile pair of proteins steers neurons toward their targets and helps establish the brain’s sensory maps, new studies suggest.
‘Push-pull’ recipe for neural wiring used in multiple brain regions
A versatile pair of proteins steers neurons toward their targets and helps establish the brain’s sensory maps, new studies suggest.
Reward-learning algorithm hardwired into dopamine circuit
The finding bolsters the canonical model of reward prediction error, which has come under scrutiny in recent years.
Reward-learning algorithm hardwired into dopamine circuit
The finding bolsters the canonical model of reward prediction error, which has come under scrutiny in recent years.
Exclusive: Brain and spinal cord institute halts research, citing funding problems
The Burke Neurological Institute, which calls itself “the only research institute in the U.S. dedicated to finding treatments to repair the brain and spinal cord,” ceased research operations on 22 May.
Exclusive: Brain and spinal cord institute halts research, citing funding problems
The Burke Neurological Institute, which calls itself “the only research institute in the U.S. dedicated to finding treatments to repair the brain and spinal cord,” ceased research operations on 22 May.