Artificial neural networks
Recent articles
This paper changed my life: Appreciating John Hopfield’s brilliant neural network
In a 1982 paper, the Nobel laureate created his namesake recurrent neural network—work that taught Maria Geffen to always ground research questions in biology.
This paper changed my life: Appreciating John Hopfield’s brilliant neural network
In a 1982 paper, the Nobel laureate created his namesake recurrent neural network—work that taught Maria Geffen to always ground research questions in biology.
Kim Stachenfeld on the dance between neuroscience and artificial intelligence
As a researcher at both Google DeepMind and Columbia University, Stachenfeld offers cross-disciplinary insight into how to understand the brain.
Kim Stachenfeld on the dance between neuroscience and artificial intelligence
As a researcher at both Google DeepMind and Columbia University, Stachenfeld offers cross-disciplinary insight into how to understand the brain.
Explore more from The Transmitter
Links between tuberous sclerosis complex and autism, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 17 August.
Links between tuberous sclerosis complex and autism, and more
Here is a roundup of autism-related news and research spotted around the web for the week of 17 August.
The fun and flexibility of data science
Taylor Bolt spent his Ph.D. and postdoc digging through brain imaging data for clues to cognition. In industry, the datasets are different but the joy of answering questions with data remains.
The fun and flexibility of data science
Taylor Bolt spent his Ph.D. and postdoc digging through brain imaging data for clues to cognition. In industry, the datasets are different but the joy of answering questions with data remains.
Mind over metrics: How can we tell if two brains (or AI models) are alike?
The ability to record from large populations of neurons has triggered the development of myriad methods for comparing them. But we’re still grappling with how to convert measures of likeness into a better mechanistic understanding.
Mind over metrics: How can we tell if two brains (or AI models) are alike?
The ability to record from large populations of neurons has triggered the development of myriad methods for comparing them. But we’re still grappling with how to convert measures of likeness into a better mechanistic understanding.