Recent advances in artificial intelligence (AI) have achieved human-scale speed and accuracy for classification tasks. In turn, these capabilities have made AI a viable replacement for many human activities that at their core involve classification, such as basic mechanical and analytical tasks in low-level service jobs. Current systems do not need to be conscious to recognize patterns and classify them. However, for AI to progress to more complicated tasks requiring intuition and empathy, it must develop capabilities such as metathinking, creativity, and empathy akin to human self-awareness or consciousness. We contend that such a paradigm shift is possible only through a fundamental shift in the state of artificial intelligence toward consciousness, a shift similar to what took place for humans through the process of natural selection and evolution. As such, this paper aims to theoretically explore the requirements for the emergence of consciousness in AI. It also provides a principled understanding of how conscious AI can be detected and how it might be manifested in contrast to the dominant paradigm that seeks to ultimately create machines that are linguistically indistinguishable from humans.

Flash memory is being drawn into the mainstream of enterprise storage, but its tendency to deteriorate with use remains an Achilles' heel. A paper released at the Aug. 9 start of the Flash Memory Summit in Santa Clara, Calif., finds that machine learning can counteract that deterioration and drastically extend its life cycle. The paper was written by Tom Coughlin, president of Coughlin Associates (PDF), a solid state consultant in Atascadero, Calif. He is also general chairman of the summit. The paper was sponsored by NVMdurance, a Limerick, Ireland, firm that is applying machine learning in the software it creates for managing solid state devices.