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
Finally, a new route for the magnetic-sense field
Researchers have dueled for years over how the magnetic sense works. New data from monarch butterflies could finally help settle the debate.
Finally, a new route for the magnetic-sense field
Researchers have dueled for years over how the magnetic sense works. New data from monarch butterflies could finally help settle the debate.
Sensory over-responsivity tied to autism, anxiety but not other conditions
Negative reactions to sensations track with certain neurodevelopmental traits in more than 15,000 children—pointing to shared neurobiological roots.
Sensory over-responsivity tied to autism, anxiety but not other conditions
Negative reactions to sensations track with certain neurodevelopmental traits in more than 15,000 children—pointing to shared neurobiological roots.
Neuromechanical models deepen our understanding of animal motor control
Thanks to recent progress in physics-based simulators and robotics, it has never been easier for neuroscientists to use neuromechanical modeling to test hypotheses about animal movement.
Neuromechanical models deepen our understanding of animal motor control
Thanks to recent progress in physics-based simulators and robotics, it has never been easier for neuroscientists to use neuromechanical modeling to test hypotheses about animal movement.