IMAGE: Using age predictors within specified age groups to infer causality and identify therapeutic interventions. The deep age predictors can help advance aging research by establishing causal relationships in nonlinear systems. Deep aging clocks can be used for identification of novel therapeutic targets, evaluating the efficacy of various interventions, data quality control, data economics, prediction of health trajectories, mortality, and many other applications. Dr. Alex Zhavoronkov from Insilico Medicine, Hong Kong Science and Technology Park, in Hong Kong, China & The Buck Institute for Research on Aging in Novato, California, USA as well as The Biogerontology Research Foundation in London, UK said "The recent hype cycle in artificial intelligence (AI) resulted in substantial investment in machine learning and increase in available talent in almost every industry and country." Over many generations humans have evolved to develop from a single-cell embryo within a female organism, come out, grow with the help of other humans, reach reproductive age, reproduce, take care of the young, and gradually decline.
The Government is to amend road traffic legislation to allow for the testing of self-driving vehicles on Irish roads. So what has the State got to give the autonomous driving world? It seems that Irish motorists' pain is the automotive industry's potential gain. Self-driving vehicles use a combination of video and radar to feed data to the self-driving programmes. Both the cameras and the radars have shown to work reasonably well on the dry and well-marked highways of certain US states such as California.
Then I remembered that Intel is the company that put the "silicon" in Silicon Valley. Its processors and other technologies provided much of the under-the-hood power for the personal computer revolution. At 51 years old, Intel still has some star power. But it's also going through a period of profound change that's reshaping the culture of the company and the way its products get made. As ever, Intel's main products are the microprocessors that serve as the brains of desktop PCs, laptops and tablets, and servers.
The use of artificial intelligence, machine learning and robotics has enormous potential, but along with that promise come critical privacy and security challenges, says technology attorney Stephen Wu. For example, in healthcare, "we're beginning to see surgical robots ... and robots that take supplies from one part of a hospital to another. But along with those bold technological advances come emerging privacy and security concerns. "The HIPAA Security Rule doesn't talk about surgical robots and AI systems," he notes. Nevertheless, HIPAA's administrative, physical and technical safeguard requirements still apply, he says. As a result, organizations must determine, for example, "what kind of security management procedures are touching these devices and systems - and do you have oversight over them?" Also critical is ensuring that "communications are secure from one point to another," he points out. "If you have an AI system that's drawing records from an electronic health record, how is that transmission being secured?
Artificial Intelligence (AI) is by far one of the most praised trends in Silicon Valley. Yet, in the "real world", opinions tend to be split into two camps: those who desire AI-driven personal assistants on the one hand, and those who fear that such AI solutions will steal their jobs in the future, on the other. Nevermind that Hollywood-like scenario though – the truth is that AI is already here, reading our emails, listening to our conversations, recognizing our faces, and even smelling our breath! AI is not a shiny addition. It is a must-have for any business innovations, and e-commerce seems to be in the avant-garde.
Beyond that, the alerts can help first responders arrive more quickly, too. While a motorist or airplane pilot may call in a smoke report for a general area, Descartes' text-based tool narrows down where the fire is. "That's very beneficial," Griego said, "especially at night when it's hard to determine what mountain range this fire's actually on when you're on top of a peak 20 miles away." The need for all manner of fire-fighting solutions is growing as climate change worsens wildfires across California and the Southwestern US. Wildfires blazed through California's wine country and the Los Angeles area in October, less than a year after a devastating fire leveled the California town of Paradise.
You are free to share this article under the Attribution 4.0 International license. An experimental device uses machine learning tools--and a bathroom scale--to monitor heart failure. Researchers envision this scenario: The user steps onto a the scale and touches metal pads. The device records an electrocardiogram from their fingers and--more importantly--circulation pulsing that makes the body subtly bob up and down on the scale. Machine learning tools compute that heart failure symptoms have worsened.
San Francisco (CNN Business)As wildfire season raged in California this fall, a startup a few states away used artificial intelligence to pinpoint the location of blazes there within minutes -- in some cases far faster than these fires might otherwise be noticed by firefighters or civilians. Santa Fe-based Descartes Labs, which uses AI to analyze satellite imagery, launched its US wildfire detector in July. The company's AI software pores over images coming in roughly every few minutes from two different US government weather satellites, in search of any changes -- the presence of smoke, a shift in thermal infrared data showing hot spots -- that could indicate a fire has ignited. Descartes is testing its detector by sending alerts to select forestry officials in its home state of New Mexico and told CNN Business its wildfire detector has spotted about 6,200 total thus far. The company says it can often detect these fires when they're just about 10 acres in size.
Cameras and computers together can conquer some seriously stunning feats. Giving computers vision has helped us fight wildfires in California, understand complex and treacherous roads -- and even see around corners. Specifically, seven years ago a group of MIT researchers created a new imaging system that used floors, doors, and walls as "mirrors" to understand information about scenes outside a normal line of sight. Using special lasers to produce recognizable 3D images, the work opened up a realm of possibilities in letting us better understand what we can't see. Recently, a different group of scientists from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) has built off of this work, but this time with no special equipment needed: They developed a method that can reconstruct hidden video from just the subtle shadows and reflections on an observed pile of clutter.