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
A brief history of precision self-scanning
When a researcher solved a logistical problem by going rogue, the idea proved remarkably infectious.
A brief history of precision self-scanning
When a researcher solved a logistical problem by going rogue, the idea proved remarkably infectious.
Sensory profiles in autism, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 19 January.
Sensory profiles in autism, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 19 January.
Frameshift: At a biotech firm, Ubadah Sabbagh embraces the expansive world outside academia
As chief of staff at Arcadia, Ubadah Sabbagh gets to do science while also pushing the boundaries of how science gets done.
Frameshift: At a biotech firm, Ubadah Sabbagh embraces the expansive world outside academia
As chief of staff at Arcadia, Ubadah Sabbagh gets to do science while also pushing the boundaries of how science gets done.