Slower Artificial Intelligence
Most involved in artificial intelligence research and practice would like faster computers and software. The basic premise remains to be that the brain is a very fast and efficient computing machine and to replicate intelligence will require significant improvement in speed and size of computing. This makes sense. However, such a process is a linear extension of traditional computing ideas in an effort to explain complexity, that is not well understood.
It is conceivable that the brain is not a fast computing machine at all. However, it demonstrates the ability to assimilate complex information quickly to produce outcomes that are extremely impressive. There are two assumptions in the previous statement – first, the brain is assimilating complex information and second it is producing outcomes that are impressive. The first assumption is an observation that the brain has many channels through which it appears to be collecting information but it is not exactly clear if it is using all that information. An alternative hypothesis may be that brain is using only a small percentage of the available information. If the discarding of information is systematic, it will require high computing power but it is also possible that the brain is using simple rules of thump and indiscriminately discarding information because it simply does not have the computing power to process it.
The second assumption that the outcomes the brain produces are impressive is debatable– the human brain perceives its own process as impressive but that is not an absolute. For example, if the brain is selecting from available behavior and outcomes templates (that are limited) based on the inputs, the fact that the templates are complex does not mean that it requires computing intensity. Artificial Intelligence focuses on creating the templates from scratch based on a large amount of input information but the human brain may not do that at all. The operating system, at birth, is loaded with some basic templates and over time the brain makes some changes to these templates. But the outcome itself is really a selection problem (i.e. which template to produce) rather than a design problem (how to design the template).
Many have been fascinated by the workings of the human brain and many have been toiling for the past few decades to try to replicate it using traditional computing – by making the machines faster and their memory larger. It may be worthwhile to step back and challenge the basic assumptions underlying this effort. It may be possible to reproduce the outcomes of the brain by simple processes that require low computing intensity and memory. If so, such intelligence may not be worth replicating.
