CMU MLD
@mldcmu.bsky.social
As the world's first machine learning academic department, CMU MLD leads the development of Machine Learning by performing leading research, developing and propagating a model academic curriculum for the field, and by helping society benefit from ML.
Reposted by CMU MLD
1/6 Recent discussions (e.g. Rich Sutton on @dwarkesh.bsky.social’s podcast) have highlighted why animals are a better target for intelligence — and why scaling alone isn’t enough.
In my recent @cmurobotics.bsky.social seminar talk, “Using Embodied Agents to Reverse-Engineer Natural Intelligence”,
In my recent @cmurobotics.bsky.social seminar talk, “Using Embodied Agents to Reverse-Engineer Natural Intelligence”,
September 29, 2025 at 2:02 PM
1/6 Recent discussions (e.g. Rich Sutton on @dwarkesh.bsky.social’s podcast) have highlighted why animals are a better target for intelligence — and why scaling alone isn’t enough.
In my recent @cmurobotics.bsky.social seminar talk, “Using Embodied Agents to Reverse-Engineer Natural Intelligence”,
In my recent @cmurobotics.bsky.social seminar talk, “Using Embodied Agents to Reverse-Engineer Natural Intelligence”,
A new guest post by MLD associate professor Nihar Shah on The Scholarly Kitchen explores how #AI is reshaping science and publishing.
The post calls for hybrid human-AI workflows, domain-specific benchmarks, and stronger standards for reproducibility.
scholarlykitchen.sspnet.org/2025/09/19/g...
The post calls for hybrid human-AI workflows, domain-specific benchmarks, and stronger standards for reproducibility.
scholarlykitchen.sspnet.org/2025/09/19/g...
Guest Post — May the AI Be With Science - The Scholarly Kitchen
AI has opened a new chapter in the saga of science and peer review. Today, guest author Prof. Nihar B. Shah explains how, if guided with integrity, AI can open galaxies of possibilities.
scholarlykitchen.sspnet.org
September 24, 2025 at 3:06 PM
A new guest post by MLD associate professor Nihar Shah on The Scholarly Kitchen explores how #AI is reshaping science and publishing.
The post calls for hybrid human-AI workflows, domain-specific benchmarks, and stronger standards for reproducibility.
scholarlykitchen.sspnet.org/2025/09/19/g...
The post calls for hybrid human-AI workflows, domain-specific benchmarks, and stronger standards for reproducibility.
scholarlykitchen.sspnet.org/2025/09/19/g...
Reposted by CMU MLD
Our first NeuroAgent! 🐟🧠
Excited to share new work led by the talented @reecedkeller.bsky.social, showing how autonomous behavior and whole-brain dynamics emerge naturally from intrinsic curiosity grounded in world models and memory.
Check it out here! 👇
Excited to share new work led by the talented @reecedkeller.bsky.social, showing how autonomous behavior and whole-brain dynamics emerge naturally from intrinsic curiosity grounded in world models and memory.
Check it out here! 👇
1/ I'm excited to share recent results from my first collaboration with the amazing @anayebi.bsky.social
and @leokoz8.bsky.social !
We show how autonomous behavior and whole-brain dynamics emerge in embodied agents with intrinsic motivation driven by world models.
and @leokoz8.bsky.social !
We show how autonomous behavior and whole-brain dynamics emerge in embodied agents with intrinsic motivation driven by world models.
June 5, 2025 at 8:14 PM
Our first NeuroAgent! 🐟🧠
Excited to share new work led by the talented @reecedkeller.bsky.social, showing how autonomous behavior and whole-brain dynamics emerge naturally from intrinsic curiosity grounded in world models and memory.
Check it out here! 👇
Excited to share new work led by the talented @reecedkeller.bsky.social, showing how autonomous behavior and whole-brain dynamics emerge naturally from intrinsic curiosity grounded in world models and memory.
Check it out here! 👇
MLD professor @anayebi.bsky.social and his team are working to make robots that process touch like human brains.
#robots #CMU #ML #brain #cortex #SSL
#robots #CMU #ML #brain #cortex #SSL
Check out our new work on making robots process touch more like brains!
Surprisingly, ConvRNNs best matched mouse cortex—passing the NeuroAI Turing Test. We also developed tactile-specific SSL augmentations and an Encoder-Attender-Decoder framework unifying ConvRNNs, SSMs & Transformers.
Surprisingly, ConvRNNs best matched mouse cortex—passing the NeuroAI Turing Test. We also developed tactile-specific SSL augmentations and an Encoder-Attender-Decoder framework unifying ConvRNNs, SSMs & Transformers.
1/ What if we make robots that process touch the way our brains do?
We found that Convolutional Recurrent Neural Networks (ConvRNNs) pass the NeuroAI Turing Test in currently available mouse somatosensory cortex data.
New paper by @Yuchen @Nathan @anayebi.bsky.social and me!
We found that Convolutional Recurrent Neural Networks (ConvRNNs) pass the NeuroAI Turing Test in currently available mouse somatosensory cortex data.
New paper by @Yuchen @Nathan @anayebi.bsky.social and me!
June 10, 2025 at 5:08 PM
Reposted by CMU MLD
As a long-time fan of Paul Middlebrooks' "Brain Inspired" podcast, it was an honor to be invited on to talk about NeuroAgents, our update to the Turing Test, and AI safety at the end.
Coincidentally recorded on my birthday, no less! Check it out here 👇
Coincidentally recorded on my birthday, no less! Check it out here 👇
In this “Brain Inspired” episode, @anayebi.bsky.social joins Paul Middlebrooks to discuss his reverse-engineering approach to build autonomous artificial-intelligence agents.
www.thetransmitter.org/brain-inspir...
www.thetransmitter.org/brain-inspir...
Aran Nayebi discusses a NeuroAI update to the Turing test
And he highlights the need to match neural representations across machines and organisms to build better autonomous agents.
www.thetransmitter.org
April 9, 2025 at 2:25 PM
As a long-time fan of Paul Middlebrooks' "Brain Inspired" podcast, it was an honor to be invited on to talk about NeuroAgents, our update to the Turing Test, and AI safety at the end.
Coincidentally recorded on my birthday, no less! Check it out here 👇
Coincidentally recorded on my birthday, no less! Check it out here 👇
Reposted by CMU MLD
What should count as a good model of intelligence?
AI is advancing rapidly, but how do we know if it captures intelligence in a scientifically meaningful way?
We propose the *NeuroAI Turing Test*—a benchmark that evaluates models based on both behavior and internal representations.
AI is advancing rapidly, but how do we know if it captures intelligence in a scientifically meaningful way?
We propose the *NeuroAI Turing Test*—a benchmark that evaluates models based on both behavior and internal representations.
February 25, 2025 at 4:11 PM
What should count as a good model of intelligence?
AI is advancing rapidly, but how do we know if it captures intelligence in a scientifically meaningful way?
We propose the *NeuroAI Turing Test*—a benchmark that evaluates models based on both behavior and internal representations.
AI is advancing rapidly, but how do we know if it captures intelligence in a scientifically meaningful way?
We propose the *NeuroAI Turing Test*—a benchmark that evaluates models based on both behavior and internal representations.