Following on the bit of history in the post immediately below.
First up, ZDNet with the headline story, March 7:
The future of AI hardware may lie in the development of brain cells as computing machines as they offer significant advantages in power consumption and processing speeds.
All signs seem to show that we have officially migrated from the era of the internet to that of AI. If the internet defined a new world of transformation in how we were going to consume, sell, entertain, and beyond, AI is now poised to establish yet another great leap in our collective human activity.
Experts say that AI's lightning-fast computations will bring in unparalleled new gains in productivity and innovation for you and me like never seen before.
We will be able to spot cancerous tumors with lightning speed, unravel the genetic code behind diseases, design new drugs, figure out carbon-free sources of energy, eliminate drudgery, and who knows what else.
Except, there are a few not-so-minor catches.
The first is that Moore's Law -- postulated by Intel's legendary co-founder Gordon Moore who said that chip density will roughly double every 18 months -- is going to hit a wall soon if it hasn't already. (It is increasingly difficult to shrink a chip more than we already have).
"In the 15 years from 1986 to 2001, processor performance increased by an average of 52 percent per year, but by 2018, this had slowed to just 3.5 percent yearly -- a virtual standstill," says Klaus Æ. Mogensen in Farsight magazine.The second problem is more dire. Artificial neural networks (ANNs), which process vast numbers of real-world datasets (big data) using silicon computing chips are spectacular guzzlers of power and water.
Training ANNs on current hardware produces colossal amounts of heat which requires equally massive amounts of cooling which is simply not cool in an era of acute climate crisis.
According to recent estimates, in just three years, AI models and their chips will eventually soak up as much electricity as the government of Netherlands.
If this isn't bad enough, a technical challenge looms where network processing speeds will hit a wall because of the physical separation of data from the processors, a problem commonly referred to as known as the "von Neumann bottleneck."
In other words, what AI desperately needs is an epic AI hardware revolution. Fortuitously, a group of scientists have come up with just that.....
....MUCH MORE
Related:
Coming over the horizon: "The world is running out of data storage. Here’s how DNA can save us"
