A century ago, more than 60,000 tigers roamed the wild. Today, that number has dwindled to around 3,200. Poaching is one of the main drivers of this steep decline. Humans have pushed tigers to near-extinction, whether for their skins, medicine or for trophy hunting. The same applies to other large animal species like elephants and rhinoceros that play unique and crucial roles in the ecosystems where they live.
A team of computer scientists may have developed a surprising way to curb wildlife poaching. Funded by the National Science Foundation (NSF), a team of computer scientists at the University of Southern California (USC) have developed a model for "green security games" that use game theory to protect wildlife from poachers. Game theory uses mathematical equations "to predict the behavior of adversaries and plan optimal approaches for containment," explains NSF, which would allow park rangers to patrol parks and wildlife sanctuaries more effectively. "In most parks, ranger patrols are poorly planned, reactive rather than pro-active and habitual," Fei Fang, a Ph.D. candidate in the computer science department at USC and a researcher involved with the project, tells NSF. "We need to provide actual patrol routes that can be practically followed."
AI services like Apple's Siri and others operate by sending your queries to faraway data centers, which send back responses. The reason they rely on cloud-based computing is that today's electronics don't come with enough computing power to run the processing-heavy algorithms needed for machine learning. The typical CPUs most smartphones use could never handle a system like Siri on the device. But Dr. Chris Eliasmith, a theoretical neuroscientist and co-CEO of Canadian AI startup Applied Brain Research, is confident that a new type of chip is about to change that. "Many have suggested Moore's law is ending and that means we won't get'more compute' cheaper using the same methods," Eliasmith says.
When artificial intelligence technology intersects with abundant oil and gas seismic data, the outcome could yield a more accurate depiction of what lies beneath the surface, enabling cash-strapped drillers to better target sweet spots and maximize returns. It's all based on algorithms that essentially teach computers how to solve complex problems--in this instance, how to quickly and accurately find subsurface faults that lead to lucrative hydrocarbon discoveries. Naveen Rao, the CEO of two-year-old startup Nervana Systems, compared the concept to the brain and its network of neurons. "Each neuron does a little bit of information processing. It combines that with the output of many other neurons, and the whole stack basically processes information that comes in through our sensors," Rao told Hart Energy.
IP Cores Designed for HSA Historically GPT has developed IP specifically for the China market. The company recently announced a range of new IP licensing offerings along with an enhanced geographical licensing program. With the company-wide adoption of HSA standards, GPT now licenses IP worldwide. All GPT processors include HSA support and the company is now offering world-class HSA-enabled processors to its customers. The HSA enabled IP core which is sampling now in silicon is a first implementation of GPT's 3-in-1 Unity architecture designed for multidimensional signal processing including image and video processing.