Intelligence isn’t just pattern recognition… on AI, brain and other stories
[edited using GPT4] This is me. This is perhaps one of the most intimate ways I could introduce myself: by showing you my neurons firing up, my thoughts flowing, my mind thinking, and my 3-pound brain in action.
My fascination with intelligence first began in the summer of 2014 while visiting Stanford University. I was asked to help a friend with some research. These are images of my brain; perhaps one of the most mesmerizing, but also depressing things I have ever seen. That’s it! My brain is now watching itself think… meta. In fact, learning about intelligence and different approaches to building it has inspired me to learn more about AI and a computer science approach to intelligence building. Different scientific fields are currently joining forces: neuroscience, cognitive science, and computer science are converging with new joint efforts to understand intelligence. Intelligence Quest IQ at MIT is perhaps one of the leading initiatives in this category right now.
Coming back to intelligence and my brain. Every time I used to hear in the media that we were close to figuring out how the brain works, potentially solving the mystery of intelligence, I would get goosebumps. The dream of decoding the mind behind that colorful gif could become a reality. However, after reading a few books on neuroscience and talking to a few scientists, it got me thinking: “But how close are we really to figuring out how the human brain works?” The truth is that no one knows! Let me explain. Imagine we are on a road trip from San Francisco to LA and I tell you we are close to reaching our destination. This statement implies that I know roughly where LA is, the rough distance of our travel from SF to LA, and how far we have gone. That’s why I can tell you roughly how close or far we are from reaching the destination, based on the distance we have traveled. If I tell you we are close to figuring out how our brain works, it implies that I have a rough idea of the scope of the task, and based on the breadth of all the research conducted (distance traveled) in the field of neuroscience (research which is rather scattered), I can say how far or close we are to reaching the goal. You see where I am going with this? There are two problems: no one knows what the scope of “figuring out the brain” is, and secondly, neuroscience is in its humble beginnings, as we are still building tools to test, examine, and understand the human brain. Just think about it for a moment.
If the human brain were so simple…
Some of the “Aha” moments that got me thinking more about neuroscience and tool building can be learned from a talented MIT Media Lab professor and 2015 Spark Prize winner, Ed Boyden, whom I had the pleasure of meeting while at MIT. He compares the mission of understanding the brain to the moon landing mission. This interview is superb. If you want to learn from people who work on the cutting edge of neuroscience, Professor Boyden has some very interesting views.
‘’What I learned was we have to take the brain at face value. We have to accept its complexity, work backwards from that, and survey all the areas of science and engineering in order to build those tools.’’ Ed Boyden
Thank you for engaging, and I hope that together, through this blog and our conversations, we can, as Marvin Minsky would say, unpack “suitcase words” such as AI and intelligence, and raise some new questions worth asking.
