Machine learning
Recent articles
Commentary: Citation graphs may underestimate neuroscience’s influence on AI
An alternative, albeit less quantitative, way to trace this history is through the people who carried ideas between the fields.
Commentary: Citation graphs may underestimate neuroscience’s influence on AI
An alternative, albeit less quantitative, way to trace this history is through the people who carried ideas between the fields.
Commentary: The rising absolute number of neuro-inspired AI papers represents a substantial footprint
Many of the design choices present in the current generation of artificial-intelligence tools parallel purported properties of the brain.
Commentary: The rising absolute number of neuro-inspired AI papers represents a substantial footprint
Many of the design choices present in the current generation of artificial-intelligence tools parallel purported properties of the brain.
Examining the bridge between neuroscience and AI
A citation analysis reveals that the connection between the two fields is real and gaining momentum. But it’s also narrow and tool-heavy; we need to find ways to widen it.
Examining the bridge between neuroscience and AI
A citation analysis reveals that the connection between the two fields is real and gaining momentum. But it’s also narrow and tool-heavy; we need to find ways to widen it.
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.
What AI can learn from hunger
To enhance AI safety, take a lesson from biological brains; a small set of wants maintains durable control over a much larger cognitive system.
What AI can learn from hunger
To enhance AI safety, take a lesson from biological brains; a small set of wants maintains durable control over a much larger cognitive system.
How, when and why to use agentic AI in our neuroscience labs
With agentic AI’s rapid infiltration into science, researchers need to develop AI use policies and practices.
How, when and why to use agentic AI in our neuroscience labs
With agentic AI’s rapid infiltration into science, researchers need to develop AI use policies and practices.
Mass-produced science is coming. What happens to scientists?
Artificial intelligence may soon enable researchers to generate high-quality science at a previously unimaginable speed. For science consumers—the public, medical patients, technology users—the likely effects will be positive. For scientists, the effects will be as disruptive as industrial mass production was for artisan manufacturers.
Mass-produced science is coming. What happens to scientists?
Artificial intelligence may soon enable researchers to generate high-quality science at a previously unimaginable speed. For science consumers—the public, medical patients, technology users—the likely effects will be positive. For scientists, the effects will be as disruptive as industrial mass production was for artisan manufacturers.
How to use artificial intelligence to strengthen scientific processes and scholarly output
As AI-driven systems are integrated into all aspects of science, we need to make sure that they read and write to a shared data and knowledge space.
How to use artificial intelligence to strengthen scientific processes and scholarly output
As AI-driven systems are integrated into all aspects of science, we need to make sure that they read and write to a shared data and knowledge space.
Transforming AI models into useful model organisms
These systems were not built to explain the brain. But treating them as model organisms that we can perturb and evolve will move us closer to that goal.
Transforming AI models into useful model organisms
These systems were not built to explain the brain. But treating them as model organisms that we can perturb and evolve will move us closer to that goal.
Models at the speed of thought: How AI coding is reshaping theoretical neuroscience
Agentic coding makes it possible to specify a neuroscience model in hours instead of months. Seven neuroscientists weigh in on what that tectonic change may bring to the field.
Models at the speed of thought: How AI coding is reshaping theoretical neuroscience
Agentic coding makes it possible to specify a neuroscience model in hours instead of months. Seven neuroscientists weigh in on what that tectonic change may bring to the field.
Explore more from The Transmitter
Remembering Barbara Finlay, ‘maverick’ of evolutionary neuroscience
Finlay, who died on 12 September, championed the idea that developmental constraints dictate how evolution sculpts brains, a concept she used to model the timing of hundreds of events and align them across mammalian species.
Remembering Barbara Finlay, ‘maverick’ of evolutionary neuroscience
Finlay, who died on 12 September, championed the idea that developmental constraints dictate how evolution sculpts brains, a concept she used to model the timing of hundreds of events and align them across mammalian species.
Crows have brains ‘in the fast lane’
The birds accurately complete decision-making tasks twice as fast as primates, although their endbrains look considerably different.
Crows have brains ‘in the fast lane’
The birds accurately complete decision-making tasks twice as fast as primates, although their endbrains look considerably different.
Prevalence of profound autism declines with new definition
The updated, more precise definition used in a CDC study includes adaptive scores.
Prevalence of profound autism declines with new definition
The updated, more precise definition used in a CDC study includes adaptive scores.