Unlocking the Neural Code: A New Frontier in Artificial Intelligence Explored in New Book
Humans are on the brink of engineering artificial intelligence (AI) that surpasses our own capabilities, predicts AI technology analyst Eitan Michael Azoff in his new book.
In his upcoming book, Towards Human-Level Artificial Intelligence: How Neuroscience Can Inform the Pursuit of Artificial General Intelligence, Azoff explores how cracking the ‘neural code’ will be the key to this transformative leap in AI.
The ‘neural code’ refers to the way the human brain encodes and processes sensory information to perform cognitive tasks like thinking, learning, problem-solving, visualisation, and maintaining an internal dialogue. Azoff argues that once we decipher this code, we can replicate and even enhance these processes in machines, leading to the development of AI that not only matches but exceeds human intelligence in capacity, speed, and capability.
Simulating Consciousness in Machines
Azoff discusses the concept of consciousness, noting that it exists in various forms across species. For instance, even simple creatures like bees exhibit a form of consciousness, albeit without self-awareness. This state of being is akin to what humans experience when they’re entirely immersed in a task, often referred to as being “in the flow.”
Azoff believes that computers can simulate this type of consciousness before moving on to more complex forms. By creating virtual brains that emulate basic consciousness, AI could gain the ability to plan actions, predict events, and recall past incidents—much like animals do.
The Role of Visual Thinking
Another cornerstone of Azoff’s argument is the role of visual thinking in the development of human-level AI. Current AI relies heavily on large language models (LLMs) for processing information, which limits its cognitive resemblance to human thought processes. Since visual thinking predates language in human evolution, Azoff suggests that understanding and replicating visual processing in AI will be a critical step towards emulating human-like thought. This approach could pave the way for AI to develop a form of consciousness that closely mirrors human experience.
“Once we crack the neural code,” Azoff states, “we will engineer faster and superior brains with greater capacity, speed, and supporting technology that will surpass the human brain. We will do that first by modelling visual processing, which will enable us to emulate visual thinking. I speculate that in-the-flow consciousness will emerge from that.”
A Call for Ethical Oversight
Despite his optimism about the future of AI, Azoff issues a cautionary note. He emphasises the importance of ethical oversight to prevent potential misuse of advanced AI technologies. “Until we have more confidence in the machines we build, we should ensure the following two points are always followed,” he advises. “First, we must make sure humans have sole control of the off switch. Second, we must build AI systems with behaviour safety rules implanted.”
As the field of AI continues to advance rapidly, Azoff’s insights offer a glimpse into a future where human-level AI is not just possible but inevitable. His call for ethical considerations serves as a reminder that with great technological power comes great responsibility, urging society to approach the development of AI with caution and foresight.
Azoff’s upcoming book promises to be a compelling read for anyone interested in the future of AI and the profound changes it may bring to human society. You can pre-order “Toward Human-Level Artificial Intelligence, How Neuroscience Can Inform the Pursuit of Artificial General Intelligence or General AI” at Taylor Francis.
It’s becoming clear that with all the brain and consciousness theories out there, the proof will be in the pudding. By this I mean, can any particular theory be used to create a human adult level conscious machine. My bet is on the late Gerald Edelman’s Extended Theory of Neuronal Group Selection. The lead group in robotics based on this theory is the Neurorobotics Lab at UC at Irvine. Dr. Edelman distinguished between primary consciousness, which came first in evolution, and that humans share with other conscious animals, and higher order consciousness, which came to only humans with the acquisition of language. A machine with only primary consciousness will probably have to come first.
What I find special about the TNGS is the Darwin series of automata created at the Neurosciences Institute by Dr. Edelman and his colleagues in the 1990’s and 2000’s. These machines perform in the real world, not in a restricted simulated world, and display convincing physical behavior indicative of higher psychological functions necessary for consciousness, such as perceptual categorization, memory, and learning. They are based on realistic models of the parts of the biological brain that the theory claims subserve these functions. The extended TNGS allows for the emergence of consciousness based only on further evolutionary development of the brain areas responsible for these functions, in a parsimonious way. No other research I’ve encountered is anywhere near as convincing.
I post because on almost every video and article about the brain and consciousness that I encounter, the attitude seems to be that we still know next to nothing about how the brain and consciousness work; that there’s lots of data but no unifying theory. I believe the extended TNGS is that theory. My motivation is to keep that theory in front of the public. And obviously, I consider it the route to a truly conscious machine, primary and higher-order.
My advice to people who want to create a conscious machine is to seriously ground themselves in the extended TNGS and the Darwin automata first, and proceed from there, by applying to Jeff Krichmar’s lab at UC Irvine, possibly. Dr. Edelman’s roadmap to a conscious machine is at https://arxiv.org/abs/2105.10461