Today we look at AI and machine learning’s impact on such diverse spheres as transportation, medical treatment, and astronomy. If you got stuck in traffic this morning (or ever), check out this article on one country’s solution to the problem.
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Traditional cities comprise an inner central business district (CBD), where most people work, surrounded by outer residential and industrial zones. Unfortunately for commuters, the high volume of people traveling to and from the CBD can cause gridlock at peak hours. To alleviate some of this frustration, the Singaporean government is working on creating regional centres by the year 2030. The planners hope to encourage business owners to open at specified regional centres around the city-state, easing peak-time pressure and encouraging public transport use.
One way to lower costs and increase quality in the healthcare system would be to predict which patients will get sick, and while predicting the future seems impossible, that’s exactly what data science and machine learning startup KenSci is hoping to do. Today the company announced that it has raised $8.5 million in a Series A investment round, led by Ignition Partners, to kick their program into high gear. KenSci was spun out of the University of Washington Tacoma in 2015 by two childhood friends — professor Ankur Teredesai, who heads the UW Tacoma’s centre for data science, and longtime Microsoft exec Samir Manjure.
Neural nets mimicking the way that our own gray matter works are increasingly finding use in astronomy, helping shed light on everything from supernova debris to binary stars. A Harvard team led by Ashley Villar, a graduate student in astronomy at Harvard University, used neural nets to study Type Ia supernovae.
This kind of explosion occurs after a white dwarf star obliterates itself after siphoning off too much mass from a companion star. Villar and her colleagues used a neural net to estimate type Ia supernovae metallicities directly from the spectrum of light seen from each one. They trained the neural net on spectra of 400 supernovae, estimating the metallicity of each supernova by looking at how metallic its host galaxy was.
Amazon received approval for a patent (originally filed Dec. 2013) for an automated fashion model, or “Automated Garment Photography With Fit Adjustment.” The patent describes a robotic mannequin that can expand, contract, and strike a variety of poses for its connected, automated photographer. The robotic mannequin can assume different poses, and it can expand and contract across the chest, waist, and hips to represent different body shapes and sizes. An automated “fit-adjustment mechanism” adjusts the clothing as the mannequin’s body shifts, preventing any potential wardrobe malfunctions.
Nest is looking to improve the artificial intelligence (AI) and use of machine learning for its products, as indicated by the recent appointment of Yoky Matsuoka as the company’s chief technology officer. Matsuoka, who previously cofounded Alphabet’s X unit before becoming the VP of technology at Nest, will leave her current position at Apple to employ her expertise in AI and robotics for the company, according to Recode. This move will likely lead to Nest introducing the Google Assistant to its devices, better positioning the voice assistant within the competitive smart home market.
Datalog.ai®, an artificial intelligence (AI) start-up that brings human-like conversation to bots, virtual assistants, IoT devices, and business applications, has today achieved a major breakthrough in AI with its launch of the MyPollyTM platform. MyPolly is the world’s first product that introduces continuous conversation via natural language understanding. MyPolly, which is currently in closed beta testing for developers and bot builders, enables virtual assistants and bots to interpret a human’s input, making MyPolly “smarter” over time.
The success of Toutiao has been achieved, in large part, by using machine learning to figure out users’ interests and tastes, and tailoring its offerings accordingly to get more clicks. Facebook and Twitter also use machine learning to refine recommendations, but they rely more heavily on social connections. When you open the app, you’ll see a stream of posts, ranging from serious news reports to cute videos. The more you click, the more Toutiao learns your tastes and interests, and refines its recommendations. Toutiao was created in 2012 by Zhang Yiming, a 33-year-old entrepreneur.
Announced at the Consumer Electronics Show (CES) in Las Vegas, BelleFox is poised to revolutionize how families interact in this constantly connected world. The BelleFox Wi-Fi router is a unique technology that delivers not only reliability and fast speeds, but a host of features to help parents see and understand their children’s online behaviour — and even to learn more about who their children are as individuals. The system uses Big Data and AI to deliver its powerful, useful insights.
When Cisco bought AppDynamics last night for $3.7 billion, it was initially a bit of a shocker, partly because of the timing, just days before the startup was scheduled to IPO. While the acquisition was clearly part of a longer term strategy by Cisco to shift focus from its hardware business to one based more on cloud software, at its core, the deal was a pure data play.
Sam Charrington, analyst, advisor, consultant, and the principal of CloudPulse Strategies interviews Hilary Mason. She heads Fast Forward Labs which helps organizations accelerate their data science and machine intelligence capabilities through a variety of research and consulting offerings. They discuss the present state and future of AI and how her company fits in with this big picture.