Artificial Intelligence is Obsessed with Recreating with Brain but Does it Need to?

Understanding and recreating the capabilities of the human brain has been one of the ambitions of artificial intelligence(AI) seems its inception. The group within AI practitioners that focus on simulating brain-like capabilities are known as connectionists and they leverage techniques such as neural networks as the fundamental mechanism for recreating models similar to the human brain.

Recreating the capabilities human brain is an incredibly ambitious plan for AI at a moment on which neuroscience is still struggling to understand the brain from a biological and cognitive standpoint. An alternative school of thought within the AI community is that to focus the efforts on recreating the elements of the human brain that enable intelligence and ignore the rest for now.

Brain vs. Intelligence

The region of the brain responsible of intelligence is known as the neocortex and is formed of different layers of neurons that process information and infer specific patterns in order to take actions. The AI practitioners that favor the focus on intelligence essentially propose that should focus on emulating the patterns on the neocortex and ignore other regions of the brain. Although controversial, the idea certainly pragmatic and interesting.

Beyond the obvious goal of AI systems of building and using knowledge, there are several capabilities of the brain that can be achieved by AI systems that focus on recreating intelligence. AI solutions built using this model that can recreate many of the process that are the result of bidirectional interactions between neurons on different regions of the neocortex. These processes power some of the most fascinating capabilities of the brain such as creativity, imagination, reasoning and many others.

What Are We Missing?

By solely focusing on the neocortex, AI systems won’t be able to emulate capabilities driven by other areas of the human brain. One clear example would be human characteristics like emotions that are the dependent on chemical reactions in tithe brain. Fear, anger, sadness, ambition, envy, empathy are some examples of emotions that fall outside the neocortex and, consequently, will be ignored by AI systems that focus on recreating that area of the brain. Many will argue that excluding those characteristics are not necessarily a bad thing ;) After all, who wants to deal with sad, angry or ambitious AI systems?

What Technologies Can Help to Better Model Intelligence?

Undoubtly, the AI platform system is exploding and there are many impressive technologies in the space. Google’s DeepMind seems to be a platform that is constantly reaching new levels to simulate intelligence. During last year’s match between DeepMind’s AlphaGO and GO’s number one player, experts were shocked by the levels of “creativity” and “imagination” demonstrated by AlphaGo.

Among the mainstream frameworks in the AI space, TensorFlow provides a very robust model to model graphs that can bidirectionally exchange data in the form of Tensors. That flexible model is very similar to the foundational elements of the neocortex.

CEO of IntoTheBlock, Chief Scientist at Invector Labs, I write The Sequence Newsletter, Guest lecturer at Columbia University, Angel Investor, Author, Speaker.

CEO of IntoTheBlock, Chief Scientist at Invector Labs, I write The Sequence Newsletter, Guest lecturer at Columbia University, Angel Investor, Author, Speaker.

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