3-D sensors coming to this year's smartphones are just the tip of a wave of machine learning-driven photography that will both correct shortcomings of smartphone pictures and also provide some stunning new aspects of photography.
IBM reports results of running a machine learning classifier on two qubits of its "IBM Q" quantum computer. The researchers haven't yet found the "quantum advantage" over classical computing, but are hopeful they're going in the right direction. Is there approach of massive compute enough to dispel deep learning's fascination with hierarchies of representation?
Google, along with researchers at Stanford University and Brown University, have extended the open-source Snorkel tool to make it industrial-strength for enterprise machine learning. The work points the way to a path beyond traditional data integration.
Intel's senior vice president and head of Mobileye, Amnon Shashua, on Wednesday unveiled new research done with colleagues at Hebrew University that both establishes important proof for capabilities of deep learning, and also offers a way forward for computing some commonly intractable problems in quantum physics.
Facebook’s latest research on intelligent agents shows the field continues to be divorced from the underlying motivations and impulses that make dialogue and interaction rewarding.
Google's new "TF-Replicator" technology is meant to be drop-dead simple distributed computing for AI researchers. A key benefit of the technology can be that it takes dramatically less time to reach benchmark results on standard tasks such as ImageNet.
Enterprise software startup Clari builds models of business deals using machine learning to enhance the pursuit of revenue. The company is extending its reach to more and more systems of record inside companies, hoping to create a total picture of "go-to-market" work.
New research from OpenAI and Google's Brain offer novel approaches to reinforcement learning, the technique for developing computer programs to win at video games. They have some fascinating reflections on the nature of the worlds they're building and exploring.
The team of professor Sergey Levine at University of California at Berkeley engineered a novel mash-up of two machine learning tasks, resulting in ways to have a computer continually update its ability to generalize from one learned task to another.
With the acquisition in December of some intellectual property of the AI startup called Sentient Technologies, IT services giant Cognizant technologies takes a major leap into the leading edge of machine learning. It could mean a whole new, high-value set of products for Cognizant, and big resources for an approach to AI that evolves past typical deep learning.