Neuroscience/ML: Discussion on "A Brief History of Intelligence (2023)"

Join us for a discussion on the first section of Max Bennett's terrific and insightful book A Brief History of Intelligence (2023).

About the book

After the success of Large Language Models like ChatGPT, there's a lot of talk about the impending arrival of artificial human-level intelligence. However, there is a lack of consensus about what else needs to happen before we reach AGI.

Max Bennett's A Brief History of Intelligence sheds light on this topic by taking a principled evolutionary neuroscience approach. Intelligence appeared in small steps, starting with less intelligent creatures (e.g. C. Elegans with ~ 300 neurons and ~ 1000 connections) and working all the way up to humans (billions of neurons and trillions of connections). The book examines the evolutionary lineage of humans and traces human intelligence to five evolutionary breakthroughs, and compares and contrasts these evolutionary innovations to various ideas in Deep Learning.

At the end of the book, one gets a good picture of what human intelligence (and animal intelligence in general) is all about, and where Deep Learning stands in relation to it.

The book is written in simple language and is quite the page turner!

About the event

We will discuss the first section of the book titled Breakthrough #1: Steering and the first Bilaterians (page 1 - 104). Participants are expected to have read this section before joining the event.

We will begin at 18:30 with introductions over snacks and drinks. At around 19:00, we will start the discussion.

Our discussion will be open-ended, but could revolve around the following meta-level themes:

1. How does the author's description of the learning and neural circuits in Bilaterians (e.g. nematodes, slugs etc.) match up with what we know about modern Deep Learning architectures?
2. On which points do you disagree with the author's conclusions and why?
3. Which topics in the section did you not quite understand and would like to check if anyone else can explain it to you?
4. What is the relationship between Bilaterian intelligence and human intelligence?

The end time of the discussion is open ended. We have put 3 hours tentatively, but the space allows us to discuss longer if we want.

Looking forward to seeing you there!

Further reading
For those that want to dive deeper into the simple forms of learning seen in the most studied primitive Bilaterians (e.g. C. Elegans and Aplysia) and their parallels in Deep Learning, here are some selected resources.

1. An elegant mind: Learning and memory in Caenorhabditis elegans
2. A Biologically Based Computational Model for Several Simple Forms of Learning (Computational model for associative learning in the slug Aplysia where the neuronal circuit for associative learning is known)
3. Effects of neuromodulation-inspired mechanisms on the performance of deep neural networks in a spatial learning task
4. The Molecular and Systems Biology of Memory
5. Associative learning in the cnidarian Nematostella vectensis (New evidence that radially symmetric and generally immobile animals with decentralized nervous systems i.e no brains can also do associative learning)
6. Virtual C. Elegans

What about the other sections of the book?
Depending on the interest, we will cover the remaining sections of the book in future event. The idea is to use alternate months for this book (until it is done), and the other months for Deep Learning related papers.