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
How does a control theorist explain cognition?
Maxim Raginsky draws on control theory, engineering and philosophy to explore what makes biological brains intelligent, what artificial intelligence is missing, and what principles underlie biological autonomy.
How does a control theorist explain cognition?
Maxim Raginsky draws on control theory, engineering and philosophy to explore what makes biological brains intelligent, what artificial intelligence is missing, and what principles underlie biological autonomy.
Holographic mesoscope reads, writes from different cortical regions simultaneously
The tool could help reveal how information transmission between areas relates to perception, cognition and behavior.
Holographic mesoscope reads, writes from different cortical regions simultaneously
The tool could help reveal how information transmission between areas relates to perception, cognition and behavior.
Susana Carmona on the neurobiology of pregnancy
In a Q&A about her new book, “A Mother’s Brain,” Carmona shares key moments in her career that led her to study the neuroscience of motherhood and discusses some of the major questions the field still needs to address.
Susana Carmona on the neurobiology of pregnancy
In a Q&A about her new book, “A Mother’s Brain,” Carmona shares key moments in her career that led her to study the neuroscience of motherhood and discusses some of the major questions the field still needs to address.