We sit at the threshold of the next generation of artificial intelligence—the development of true machine intelligence. Today, the best of A.I. has given us virtual assistants like Apple’s Siri and big data question/answering systems like IBM Watson. These statistical systems—based on Natural Language Processing—have accomplished a great deal. But, these assistants don’t really understand and do what we ask of them. They understand simple questions but cannot respond to complex or even slightly ambiguous ideas. Imagine you say, “I dropped my book and walked out of the kitchen to the bedroom. Where's the book?" A three-year old can grasp the meaning but your assistant can only scratch their virtual head.
Brains aren’t what you think they are. They aren’t computers and they don’t process data. Cognitive science tells us that the brain is more of a pattern-matching machine than a processing machine. Understanding meaning—Natural Language Understanding—can’t be achieved through statistical processing. NLU relies on a richer environment that looks at patterns in linguistics, as well as sensory perceptions. Machine Intelligence, first published in 1998, takes the reader through the research that lead to Patom Theory, a brain-based theory based solely on a brain that stores, matches, and uses patterns.
Ball, a cognitive scientist, began exploring the gap between how our brains interpret information and how computers work in 1983. Research, development collaborations and idea exchanges with the likes of A.I. co-founder and Turing Award winner Marvin Minsky became the foundation of Patom Theory. The theory has laid the groundwork work for NLU software developments that may lead to truly intelligent machines.
Brains aren’t what you think they are. They aren’t computers and they don’t process data. Cognitive science tells us that the brain is more of a pattern-matching machine than a processing machine. Understanding meaning—Natural Language Understanding—can’t be achieved through statistical processing. NLU relies on a richer environment that looks at patterns in linguistics, as well as sensory perceptions. Machine Intelligence, first published in 1998, takes the reader through the research that lead to Patom Theory, a brain-based theory based solely on a brain that stores, matches, and uses patterns.
Ball, a cognitive scientist, began exploring the gap between how our brains interpret information and how computers work in 1983. Research, development collaborations and idea exchanges with the likes of A.I. co-founder and Turing Award winner Marvin Minsky became the foundation of Patom Theory. The theory has laid the groundwork work for NLU software developments that may lead to truly intelligent machines.
