Artificial intelligence vs. human intelligence: how do they measure up?

#artificialintelligence

There's no denying that artificial intelligence is lightyears ahead of what it was just a few years ago. The technology continues to advance at an ever-increasing rate. But the ultimate goal of artificial intelligence researchers is to replicate human intelligence. So how do artificial intelligence and human intelligence measure up? The so-called "deep learning" that artificial intelligence is capable of isn't really the type of profound learning like humans are capable of.



Deep Learning and Neuromorphic Chips

@machinelearnbot

There are three main ingredients to creating artificial intelligence: hardware (compute and memory), software (or algorithms), and data. We've heard a lot of late about deep learning algorithms that are achieving superhuman level performance in various tasks, but what if we changed the hardware? Firstly, we can optimise CPU's which are based on the von Neumann architectures that we have been using since the invention of the computer in the 1940's. These include memory improvements, more processors on a chip (a GPU of the type found in a cell phone, might have almost 200 cores), FPGA's and ASIC's. Such is the case with research being done at MIT and Stanford.


Deep Learning and Neuromorphic Chips

#artificialintelligence

There are three main ingredients to creating artificial intelligence: hardware (compute and memory), software (or algorithms), and data. We've heard a lot of late about deep learning algorithms that are achieving superhuman level performance in various tasks, but what if we changed the hardware? Firstly, we can optimise CPU's which are based on the von Neumann architectures that we have been using since the invention of the computer in the 1940's. These include memory improvements, more processors on a chip (a GPU of the type found in a cell phone, might have almost 200 cores), FPGA's and ASIC's. Such is the case with research being done at MIT and Stanford.


Human Brain vs Machine Learning - A Lost Battle?

#artificialintelligence

Human (or any other animal for that matter) brain computational power is limited by two basic evolution requirements: survival and procreation. Our "hardware" (physiology) and "software" (hard-coded nature psychology) only had to evolve to allow us to perform a set of basic actions - identify Friend or Foe, obtain food, find our place in the social tribe hierarchy, ultimately find a mate and multiply. Anything beyond this point, or not directly leading to this point can be considered redundant, when viewed from the evolution perspective. To accomplish these "life" goals, our brains evolved to a certain physical limit (100 billion neurons per average brain, on average 7000 synaptic connections per neuron). Obviously, evolving beyond this limit was not beneficiary for survival and procreation in the African savannas.