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
Securing the academic pipeline amid uncertain U.S. funding climate
Finding creative ways to keep early-career researchers in academia—for example, through part-time roles—can help the field weather the storm.
Securing the academic pipeline amid uncertain U.S. funding climate
Finding creative ways to keep early-career researchers in academia—for example, through part-time roles—can help the field weather the storm.
Let’s teach neuroscientists how to be thoughtful and fair reviewers
Blanco-Suárez revamped the traditional journal club by developing a course in which students peer review preprints alongside the published papers that evolved from them.
Let’s teach neuroscientists how to be thoughtful and fair reviewers
Blanco-Suárez revamped the traditional journal club by developing a course in which students peer review preprints alongside the published papers that evolved from them.
New autism committee positions itself as science-backed alternative to government group
The Independent Autism Coordinating Committee plans to meet at the same time as the U.S. federal Interagency Autism Coordinating Committee later this month—and offer its own research agenda.
New autism committee positions itself as science-backed alternative to government group
The Independent Autism Coordinating Committee plans to meet at the same time as the U.S. federal Interagency Autism Coordinating Committee later this month—and offer its own research agenda.