Researchers at the University of Waterloo have built what they claim is the most accurate simulation of a functioning brain to date. Despite a seemingly unimpressive count of only 2.5 million neurons, (the human brain is estimated to have somewhere nearing 100 billion neurons), Spaun (Semantic Pointer Architecture Unified Network) is able to process visual inputs, compute answers and write them down using a robotic arm, performing feats of intelligence that up to this point had only been attributed to humans.
Save for a select few areas, our decades-old efforts in creating a true artificial intelligence have mostly come up short: while we’re slowly moving toward more accurate speech recognition, better computerized gaming opponents and “smart” personal assistants on our phones, we’re still a very long way from developing a general-purpose artificial intelligence that displays the plasticity and problem-solving capabilities of an actual brain.
The “reverse engineering” approach of attempting to understand the biology of the human brain and then build a computer that models it isn’t new; but now, thanks to the promising results of research efforts led by Prof. Chris Eliasmith, the technique could gain even more traction.
Using a supercomputer, the researchers modeled the mammalian brain in close detail, capturing its properties, overall structure and connectivity down to the very fine details of each neuron – including which neurotransmitters are used, how voltages are generated in the cell, and how they communicate – into a very large and resource-intensive computer simulation. Then, they hardwired into the system the instructions to perform eight different tasks that involved different forms of high-level cognitive functions, such as abstraction. Tasks included handwriting recognition, answering questions, addition by counting, and even the kind of completion of symbolic patterns that often appears in intelligence tests. More here Scientists build the most accurate computer simulation of the brain yet.