Part III: Neuroscience in AGI/ASI – Future-Looking Practical Applications

In Part 1, we discussed how “the increased interest in neural networks, more specifically deep neural networks, and AI has greatly benefited various technological fields, these techniques are also expected to help further advance scientific fields, such as the neuroscience community.” We also covered that, to help simplify the ambiguous and overwhelming marriage between Neuroscience and AI, we should first categorize the space into two overarching areas: Theoretical and Practical applications. In my case, the connection between neuroscience and AI mostly lies between Neural Oscillations (a.k.a. brainwaves) and Neural Networks (ML/DL). Part 1, more specifically, looked at the current and the projected theoretical applications of neuroscience and AI.

In Part 2, we explored the practical applications of Neuroscience and AI. Unlike the research and the academic communities, which primarily seek applications of theoretical nature, such as conducting research to discover, explore, and explain anything and everything, we discussed that the practical approach mainly seeks applications of practical nature, such as products or services to be marketed and sold. We also noted that the practical approach is not only about tech and/or retail products and services but also includes practical applications in the healthcare industry. 

In the previous edition we discussed how the practical applications of Neuroscience and AI can be further categorized into 1) existing applications and 2) future-looking applications. While we already covered the existing applications, in this edition, we are going to explore the future-looking practical applications of Neuroscience and AI. Although it is extremely hard to predict the future, there are still some elements that, to some extent, we have control over, which in turn can help us foresee what is coming.

First, there is no doubt in my mind that technologies will become an extension of the human brain, not only in BCI applications but also in commercial products and offerings. The first time that I openly talked about this was in 2012 during one of my (lightning) talks at the Smart Data Conference in San Jose, CA. In that talk, I illustrated how the brain and various technologies will be able to harness and enhance each other’s power. Years later, the idea of commercial applications of implants in the human bodies are not as far fetched as they once were. 

While the ideas, the developments, and the production of implants have been in the works over the past few decades, their implementations and/or usage remain ever-evolving. For example, as we covered in the previous edition, BCI has solved for several use cases in the health industry where patients who are unable to speak can write on screens through thinking of alphabets. But what remains yet to be discovered and developed are 1) easy non-invasive ways to make the connection between the brain and the machines and 2) beneficial use cases for commercial use that a seamless collaboration between brains and machines may offer.

Second, let us talk about AGI and ASI – at least this is what we call them now. Although still very forward-looking, AGI and ASI hold endless possibilities of future-looking practical applications in the realm of Neuroscience and AI. If you are not familiar with AGI and ASI yet, below are few highlights of future-looking hypothetical:

AGI: Artificial General Intelligence

The concept of AGI is where the future of AI applications will be able to learn intellectual tasks that us humans and/or animals are capable of doing in our daily lives. For example, it is predicted that AGIs of the future will be able to reason, strategize, learn, plan, and use common sense, and much more. An AGI is predicted to be quite autonomous, surpassing humanity in many tasks.

ASI: Artificial Super Intelligence

The super intelligence of an ASI system is predicted to not only surpass AGI systems, but also humans. These hypothetical entities are to be much more intelligent than the most intelligent humans and be a superior system of some sort who is able to learn, predict, and evolve indefinitely. 

If you are like me and have been flirting with the AGI and ASI hypotheticals over the past decade, and have been learning and researching these systems, you may also be convinced that most likely we are headed towards AGI/ASI-type entities within the next few decades. While my own research has primarily been around the possible integrations between Neuroscience and AGI/ASI, I have generally focused on learning about these hypotheses through books, articles, and talks. The fact is that the more you learn the more you realize the breath of possibilities that these systems may offer. 

There is much to cover about the potential role of Neuroscience in AGI and ASI. As I work through these mind-stretching theoretical and practical concepts, I will share these research findings in my next upcoming book. 

In the meantime, for those curious about some of the practical ways that we, today, are able to incorporate Neuroscience in AI, this book covers a few of the most common neural networks used in neuroscience, as well as the EEG input data that align the best with neural networks, such as frequency domain EEG signals, time domain EEG signals, and EEG images:

Neural Oscillations in Neural Networks: Top neural networks that work best with EEG data and top EEG task classifications and data signals that work best with neural networks

Note that in this edition we only covered an eagle-eye view of the future-looking practical applications of Neuroscience and AI. We have yet to look at the details of these future-looking applications.

If you are an aspiring student, there has never been a time like today where we can be anywhere in the world, with pretty much any background, and still be able to get into the field of computational neuroscience. If you have not checked it out, visit Neuromatch Academy and their YouTube channel (I took their 2021 summer course and have no affiliation with them).

What do you think? Can you think of any additional practical applications of Neuroscience and AI? Let me know and I will add to the list. Thanks!

Disclaimer: For over a decade, I have been researching and exploring ways of Neuroscience (more specifically Neural Oscillations) in AI/ML/DL, Robotics, etc. All writings are my own in the old fashioned way. I do not use ChatGPT or the like to generate content. All views, research, and work is my own. All information provided on Neuroscience & AI Newsletter is for general information purposes only and is the expressed opinion of myself, Nilo Sarraf, and not others. This includes (but is not limited to) my memberships, organizations, institutions, and/or employers.