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
Scientists decry conference’s use of hidden prompts to snare AI peer reviews
The invisible messages, which instruct large language models to use telltale phrases in a peer-review report, are effective in catching artificial-intelligence misuse but also erode trust, some say.
Scientists decry conference’s use of hidden prompts to snare AI peer reviews
The invisible messages, which instruct large language models to use telltale phrases in a peer-review report, are effective in catching artificial-intelligence misuse but also erode trust, some say.
Johannes Jaeger explains why we should care that brains and AI are not the same
From single cells to whole organisms, living beings must continuously regenerate themselves and judge what's important to continue living. Artificial intelligence does not and cannot.
Johannes Jaeger explains why we should care that brains and AI are not the same
From single cells to whole organisms, living beings must continuously regenerate themselves and judge what's important to continue living. Artificial intelligence does not and cannot.
What mosquitos lay bare about proprioception
By comparing the proprioceptive systems of mosquitos and fruit flies, Sweta Agrawal aims to uncover fundamental features of the ability to sense self-movement.
What mosquitos lay bare about proprioception
By comparing the proprioceptive systems of mosquitos and fruit flies, Sweta Agrawal aims to uncover fundamental features of the ability to sense self-movement.