Apologies if this isn’t appropriate for the sub. I’m just curious about ML and wish to know more. I often see professionals talking about how the architecture in ML is a major limitation to progress, for example to get to AGI, and comparisons to biological neural nets which are a lot messier and less uniform than artificial neural nets. I’ve seen criticism that the nature of artificial neural nets, which function by using layers of functions to pass values to another adjacent layer and only to that layer is inferior to the more arbitrarily connected topology in animals. If true, why isn’t there more research into ML architectures that have more messier or arbitrarily connected topologies. submitted by /u/Uranusistormy
Originally posted by u/Uranusistormy on r/ArtificialInteligence
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