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
Liset de la Prida explains how neuron subtypes may control the activity of large neural populations, from manifolds to ripples
De la Prida's work analyzing the varieties of sharp wave ripples in the hippocampus led to her discovery that specific types of neurons control the properties of neural manifolds.
Liset de la Prida explains how neuron subtypes may control the activity of large neural populations, from manifolds to ripples
De la Prida's work analyzing the varieties of sharp wave ripples in the hippocampus led to her discovery that specific types of neurons control the properties of neural manifolds.
At 25, INSAR needs to bring autism scientists together more than ever
As the International Society for Autism Research’s annual meeting in Prague this week celebrates its quarter-century anniversary, its president reflects on the field’s past successes, current challenges and needs for the future
At 25, INSAR needs to bring autism scientists together more than ever
As the International Society for Autism Research’s annual meeting in Prague this week celebrates its quarter-century anniversary, its president reflects on the field’s past successes, current challenges and needs for the future
Autism experts venture to set the narrative for INSAR, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 20 April.
Autism experts venture to set the narrative for INSAR, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 20 April.