Brain simulator AI platform processes 3 billion synapses/s
The company’s Brain Simulator II is an open-source software platform for proving the evolution of artificial intelligence (AI) to artificial general intelligence (AGI). In what the company says is a significant advance in the development of AGI, the system – comprising an AMD Ryzen Threadripper 3990X CPU running at 2.9 GHz (not overclocked) and 128 Gigabytes of RAM – processed three billion synapses per second.
Seen as another step toward creating brain-level functionality on computers, the spiking neural models used by the Brain Simulator II, says the company, are more like biological neurons than traditional AI models and contribute immensely to the efficiency of the program. Energy analysis of the the higher-level thinking part of the brain – the neocortex – shows that neurons spike on average, only once every six seconds – meaning that its 16 billion neurons generate only 2.5 billion spikes per second in total.
The Brain Simulator’s spiking neural model, says the company, only processes neurons that spike in a specific time interval, rather than processing all of them, and so can be thousands of times faster than traditional artificial neural networks.
“This machine exceeds the processing performance of the human neocortex,” says Charles Simon, CEO of FutureAI, and principal author of the Brain Simulator II. “The CPU alone contains nearly 40 billion transistors and each transistor is nearly a billion times faster than each of the neocortex’s 16 billion neurons.”
The number of synapses that connect signals between neurons is the key to estimating relative performance, says the company. While the human brain has thousands of synapses for each neuron, most are either redundant or “synapses-in-waiting” — synapses that could represent memories should the need arise.
These extraneous synapses are not necessary to the simulation. Depending on the number of synapses used for the estimate, the current simulation ranges from being more capable than the neocortex to perhaps a hundred times slower, says the company, which is easily overcome with a few racks of servers.
Although less efficient traditional AI approaches will still need huge computational resources, spiking neural models open the door to a new era of AGI development. The Brain Simulator II was developed to address problems fundamental to all of AI – problems any three-year-old can solve but no AI can, says the company. This includes comprehension that objects exist in a physical reality; knowing the basic physics that objects fall down, not up; round ones roll but square ones don’t; and understanding the passage of time that blocks must be stacked before the stack can be knocked down.
By eliminating the limitation of computer power, says the company, research in new AGI directions will proceed much faster with AGI expected by the end of the decade.
Related articles:
AI startup claims first steps towards human reasoning
DARPA looks to teach machines common sense
SpiNNaker neuromorphic supercomputer reaches one million cores
Analog electrochemical device efficiently mimics brain synapse
If you enjoyed this article, you will like the following ones: don't miss them by subscribing to :
