6 min
New ‘Liquid’ AI Has Neuroplasticity Like the Human Brain Short & Sweet AI
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- Technology
What is Liquid AI, and could it prove more effective than other types of AI?
New research into neural nets and algorithms has revealed what some call “Liquid AI,” a more fluid and adaptable version of artificial intelligence.
In my previous episode, I discussed the basics of AI and the limitations that hold it back. It looks like Liquid AI could provide the very solutions that the AI community has been searching for.
In this episode of Short and Sweet AI, I explore the new research behind Liquid AI, how it works, and what it does better than other types of AI.
In this episode find out:
The limitations of traditional neural networks in AIHow researchers created Liquid AIHow Liquid AI differs from other typesHow Liquid AI solves the limitations of computing power with smaller neural netsWhy Liquid AI is more transparent and easier to analyze
Important Links & Mentions
A Simple Explanation of AIAlphaFold & The Protein Folding ProblemWhat is DALL·E?
Resources:
SingularityHub: New ‘Liquid’ AI Learns Continuously from Its Experience of the WorldAnalytics Insight: Why is a ‘Liquid’ Neural Network from MIT a Revolutionary Innovation?TechCrunch: MIT researchers develop a new ‘liquid’ neural network that’s better at adapting to new info
Episode Transcript:
Hello to you who are curious about AI, I’m Dr. Peper. Machine learning algorithms are getting an overhaul from a very unlikely source. It’s a fascinating story.
Neural Nets have Traditional Limitations
Neural nets are the powerhouse of machine learning. They have the ability to translate whole books within seconds with Google Translate, change written text into images with DALLE, and discover the 3D structure of a protein in hours with AlphaFold. But researchers have struggled with neural networks because of their limitations.
Neural nets cannot do anything other than what they’re trained for. They’re programed with parameters set to give the most accurate results. But that makes them brittle which means they can break when given new information they weren’t trained on. Today the deep learning neural nets used in autonomous driving have millions of parameters. And the newest neural nets are so complex, with hundreds of layers and billions of parameters, they require very powerful supercomputers to run the algorithms.
A Neuroplastic Neural Net based on a Nematode
Now researchers from MIT and Austria’s Science Institute have created a new, adaptive neural network they’re describing as “liquid” AI. The algorithm’s based on the nervous system of a simple worm, C. elegans. And elegant it truly is. This worm has only three hundred and two neurons but it’s very responsive with a variety of behaviors. The teams were able to mathematically model the worm’s neurons and build them into a neural network. I’ve explained neural networks in my previous episode called A Simple Explanation of...
What is Liquid AI, and could it prove more effective than other types of AI?
New research into neural nets and algorithms has revealed what some call “Liquid AI,” a more fluid and adaptable version of artificial intelligence.
In my previous episode, I discussed the basics of AI and the limitations that hold it back. It looks like Liquid AI could provide the very solutions that the AI community has been searching for.
In this episode of Short and Sweet AI, I explore the new research behind Liquid AI, how it works, and what it does better than other types of AI.
In this episode find out:
The limitations of traditional neural networks in AIHow researchers created Liquid AIHow Liquid AI differs from other typesHow Liquid AI solves the limitations of computing power with smaller neural netsWhy Liquid AI is more transparent and easier to analyze
Important Links & Mentions
A Simple Explanation of AIAlphaFold & The Protein Folding ProblemWhat is DALL·E?
Resources:
SingularityHub: New ‘Liquid’ AI Learns Continuously from Its Experience of the WorldAnalytics Insight: Why is a ‘Liquid’ Neural Network from MIT a Revolutionary Innovation?TechCrunch: MIT researchers develop a new ‘liquid’ neural network that’s better at adapting to new info
Episode Transcript:
Hello to you who are curious about AI, I’m Dr. Peper. Machine learning algorithms are getting an overhaul from a very unlikely source. It’s a fascinating story.
Neural Nets have Traditional Limitations
Neural nets are the powerhouse of machine learning. They have the ability to translate whole books within seconds with Google Translate, change written text into images with DALLE, and discover the 3D structure of a protein in hours with AlphaFold. But researchers have struggled with neural networks because of their limitations.
Neural nets cannot do anything other than what they’re trained for. They’re programed with parameters set to give the most accurate results. But that makes them brittle which means they can break when given new information they weren’t trained on. Today the deep learning neural nets used in autonomous driving have millions of parameters. And the newest neural nets are so complex, with hundreds of layers and billions of parameters, they require very powerful supercomputers to run the algorithms.
A Neuroplastic Neural Net based on a Nematode
Now researchers from MIT and Austria’s Science Institute have created a new, adaptive neural network they’re describing as “liquid” AI. The algorithm’s based on the nervous system of a simple worm, C. elegans. And elegant it truly is. This worm has only three hundred and two neurons but it’s very responsive with a variety of behaviors. The teams were able to mathematically model the worm’s neurons and build them into a neural network. I’ve explained neural networks in my previous episode called A Simple Explanation of...
6 min