Many advanced artificial intelligence projects say they are working toward building a conscious machine, based on the idea that brain Iphone Cases functions merely encode and process multisensory information. The assumption goes, then, that once brain functions are properly understood, it should be possible to program them into a computer. Microsoft recently announced that it would spend US$1 billion on a project to do just LG Cases.
So far, though, attempts to build supercomputer brains have not even come close. A multi-billion-dollar European project that began in 2013 is now largely understood to have failed. That effort has shifted to look more like a similar but less ambitious project in the U.S., developing new software tools for researchers to study brain data, rather than simulating a brain.
Some researchers continue to insist that simulating neuroscience with computers is the way to go. Others, like me, view these efforts as doomed to failure because we do not believe consciousness is computable. Our basic argument is that brains integrate and compress multiple components of an experience, including sight and smell — which simply can’t be handled in the way today’s computers sense, process and store data.
Brains don’t operate like computers
Living organisms store experiences in their brains by adapting neural connections in an active process between the subject and the environment. By contrast, a computer records data in short-term and long-term memory blocks. That difference means the brain’s information handling must also be different from how computers work.
The mind actively explores the environment to find elements that guide the performance of one action or another. Perception is not directly related to the sensory data: A person can identify a table from many different angles, without having to consciously interpret the data and then ask its memory if that pattern could be created by alternate views of an item identified some time earlier.
Another perspective on this is that the most mundane memory tasks are associated with multiple areas of the brain — some of which are quite large. Skill learning and expertise involve reorganization and physical changes, such as changing the strengths of connections between neurons. Those transformations cannot be replicated fully in a computer with a fixed architecture.