The Quest To Explain Intelligence
A Brain Inspired Course
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Enrollment for the course and free video series has closed for this round…
Neuro-AI: The Quest To Explain Intelligence is a self-paced, online course designed to educate you about the emerging field of Neuro-AI: the exciting merger of Neuroscience and Artificial Intelligence.
Insights from neuroscience research have the potential to inspire better AI by adding biological details essential to our own intelligence.
Insights and models in AI continue to improve our understanding of our own brains, reveal what makes us intelligent, and potentially help solve how our brains underly our rich mental experiences.
Neuroscience and artificial intelligence are both gigantic fields.
Both include many subfields that each require their own set of background knowledge and skills.
People spend years trying to master the knowledge and skills needed to understand, and contribute to, any one subfield alone.
Neuro-AI is especially demanding because it combines the disciplines of neuroscience and AI, which have traditionally progressed independently.
I’d Like To Help
I’m Paul Middlebrooks. A cognitive computational neuroscientist and the founder and host of the Brain Inspired podcast.
As the host of the brain inspired podcast, I have a unique vantage point on the convergence of neuroscience and AI.
I’ve seen where the fields overlap, possibilities for future research, and the potential for innovation.
I’ve created this course to help researchers and interested individuals understand this rich and exciting area of study.
Neuro-AI: The Quest To Explain Intelligence
The Neuro-AI Course is a self-paced, online course that provides a high-level overview of the concepts, methods, history, and modern examples of neuro-AI research.
In the Neuro-AI course, through efficient lessons, you’ll learn:
Fundamental concepts in modern AI, especially deep learning, and key historical ideas that brought us here.
How modern AI is providing insight into how our brains underly our cognitive functions.
What’s missing in AI, and how to move forward to build better, more generally intelligent machines and robots.
What neuroscience currently does and doesn’t understand about how our brains function and underlie our minds and cognition.
How advances in computing, modeling, and technologies are opening new frontiers and ways for outside fields to contribute.
How emerging knowledge about brain function may inform AI.
Modern and historical examples of Neuro-AI models that leverage knowlege in the neurosciences, artificial intelligence, and modern analyses, to help explain our own intelligence.
The more we can take advantage of how neuroscience and AI can inform each other, the better we’ll be able to understand and build intelligence.
Lessons You Get Right Now When You Join
Module 1: Artificial Neural Networks & The Brain
10 Lessons Covering These Topics:
- Introduces basic models
- Models for understanding
- Examples of modern models
- How ANNs compare with brains
- How ANN functions compare with cognitive functions
Module 2: Learning
13 Lessons Covering These Topics:
- How learning works in ANNs and in brains
- Supervised learning
- Back-propagation in ANNs and in brains
- Unsupervised learning
- Reinforcement learning
- Deep reinforcement learning
- Innate knowledge
Lessons You Will Get Soon When You Join
You’ll get these and all future lessons:
Neuro-AI and Cognitive Functions
Modern and ongoing explanations for cognitive functions, e.g.:
- Language and Transformer models
- Working memory
- Long-term memory
- Executive function
- Cognitive architectures
- Artificial general intelligence (AGI)
Emerging principles in neuroscience
How knowledge about brains can inform AI, e.g.:
- Cortex and cortical columns
- Network neuroscience
- Systems neuroscience
What You Get With The
Lifetime Access To The Neuro-AI Online Program (including any updates in the future)
Ongoing Q&A Sessions
Ongoing Live Discussion Sessions
References In All Lessons For Further Learning
A Student-Only Private Discord Community
Plus: Bonus Interviews With Relevant Guest Experts Including:
Computational Visual Neuroscience Laboratory, University of Minnesota
Topic: Modeling Brain Functions
Director of Emerging Technology, DGMT
Topic: Neural Networks and Biological Detail
The Learning in Neural Circuits Lab, McGill University
Topic: Back-Propagation and the Brain
Hakwan Lau & Sam Gershman
Consciousness and Metacognition Lab, Riken Center For Brain Sciences & Computational Cognitive Neuroscience Lab, Harvard University
Topic: Generative Adversarial Networks and Consciousness
Cognitive and Decision Sciences, University College London
Topic: Concept Learning
What People Are Saying About the Neuro-AI Program
David - Computer Scientist
“Great course! It was very interesting how both fields are joined, a new way to see AI algorithms while getting a broad picture of how the brain works and its theories. I’m now totally engaged in the neuroscience world, eager to continue digging into the field. ”
Thomas - Machine Learning Researcher
“Do it! I promise, you’ll love it!
This course specifically helped me resolve many issues… There have also been a variety of other insights that just happened to fall into my lap – some I had been wondering about, others I didn’t even know about.”
David F - Engineer
“If you’re interested in this area, but don’t know where you’d even begin (especially from a literature-reading perspective) – this is where to start.”
Martin H - Engineer
“(This course is) more than a foundation.
The depth and support available means you can take this and know you can go deep or as broad as you need.”
“It’s worth the money and gives you a solid overview of the current state of neuro-AI tech and understanding. ”
Frequently Asked Questions
Who is this course for?
Many of the students have some education and/or expereince with neuroscience or AI.
But you don’t need that kind of background, just curiousity and interest. Many of the students have a diverse range of backgrounds, education levels, and interests. Here are just a few examples:
- Undergraduate medical student wanting a better understanding of human intelligence.
- Product manager in Big Tech wanting useful analogies from the biological basis of intelligence.
- Software engineer (25 years experience) wanting to understand brains better for neuromorphic computing.
- Computer scientist looking to change careers into biotech.
- 78 year old retail sales retiree interested in Artificial general intelligence.
- Sociologist interested in language and memory.
- MS in Computer Science, transitioning from military to a new career in ML / AI.
- Retired physicist wanting to work on brain-inspired AI.
- Management consultant who loves learning new topics.
- The list goes on…
Does the course require coding or math?
There is no math or coding in the course. It is focused on delivering the conceptual underpinnings of neuro-AI through efficient, condensed lessons.
How Long Do I Have Access?
You have lifetime access to the modules and lessons, and will have lifetime access to any lessons I add as the course grows and new versions are created.
Will My Institution Cover the Cost?
This depends on your institution/department. Some students have successfully received reimbursement for the course from their institution.
Do You Offer a Certification of Completion?
I don’t offer any certifcation. This is not a course recognized by institutions yet. You should take the course solely for your own curiosity and edification.
What is Your Refund Policy?
Due to the nature of this program, and the access you have to all of the course materials, the Neuro-AI course has a no refunds policy. I have worked very hard to create it, and I hope you find it as valuable as I believe it is.