Silicon Valley giants such as Google and Facebook have been trying to harness artificial intelligence by training brain-inspired neural networks to better represent the real world. Digital Reasoning, a cognitive computing company based in Franklin, Tenn., recently announced that it has trained a neural network consisting of 160 billion parameters—more than 10 times larger than previous neural networks.
The Digital Reasoning neural network easily surpassed previous records held by Google’s 11.2-billion parameter system and Lawrence Livermore National Laboratory’s 15-billion parameter system. But it also showed improved accuracy over previous neural networks in tackling an “industry-standard dataset” consisting of 20,000 word analogies. Digital Reasoning’s model achieved an accuracy of almost 86 percent; significantly higher than Google’s previous record of just over 76 percent and Stanford University’s 75 percent.
“We are extremely proud of the results we have achieved, and the contribution we are making daily to the field of deep learning,” said Matthew Russell, chief technology officer for Digital Reasoning, in a press release.