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WeDoSky, Drone Data Science, solutions raises funds from Mumbai Angels Network
New Delhi [India], Dec 14 (ANI): Higher in resolution than Google Earth/Maps and updated as often as daily, WeDoSky's Drone Data Science solutions help answer the'What' and the'Where' for a geographical area that needs to be monitored. WeDoSky is a data science company focused on generating actionable business insights using drone imagery, to assist various industries like mining, construction, energy and solar. The data extraction and analysis is done using their proprietary software'visualAI' . This is also offered as a standalone SaaS platform for Drone-enabled businesses across the globe. WeDoSky counts titans like Adani Enterprises, Tata Power, Azure Power, and ACC Cement amongst its many clients.
The top business news stories of 2017
The Japan Times newsroom selected these economy and technology stories as the most important of 2017. But the struggling Japanese conglomerate later agreed on the ¥2 trillion sale of its chip unit to a Japan-U.S.-South Korea consortium. It also ended a months-long legal battle with its partner in the venture, Western Digital. Earlier this month, Japan agreed with the EU on a giant free trade deal, eliminating tariffs on 94 percent of imports from the EU. The bloc will eliminate tariffs on 99 percent of its imports from Japan.
Adam - momentum y (aka. cost) terms. • r/MachineLearning
It was the Newton-Raphson method for finding roots of an equation. I thought this method mostly applies for minimization in machine learning as cost is always defined as a positive real valued function. But it was pointed out to me that the update equation of newton-raphson method, which is x x - y / dy_dx, is unstable at local minimas (where dy_dx 0) since it makes the update burst to infinity. Eventually, I landed on this update equation, x x - ((y * dy_dx) / (y dy_dx2)); dy_dx derivative of y wrt. To relate this update equation with the title: if we consider the update portion of the equation - g(x, y) (y * x) / (y x2); y 0 It is quite similar to adam since there is a square gradient term in the denominator and the gradient term in the numerator.
Meet the researchers who used TV episodes of CSI to train artificial intelligence
Federal lawmakers want to have a say in defining artificial intelligence. Researchers are now using TV shows to feed the predictive capability of an AI system. Google said in recent days it's opening an AI-focused research facility in China. And on and on the headlines keep coming, all of which is to say that interest in AI remains acute -- and its presence pervasive -- as 2017 draws to a close. And, based on a few recent developments, 2018 should be another big year of AI-related leaps forward as machines expand their influence over the minutiae of our lives.
AI Has Been Creating Music and the Results Are...Weird
Daren Banarsë agrees on the benefits of collaboration. "I always find it daunting when I have to start a large-scale composition. Maybe I could give the computer a few parameters: the number of players, the mood, even the names of some of my favorite composers, and it could generate a basic structure for me," he says. "I wouldn't expect it to work out of the box, but it would be a starting point. Or it could output a selection of melodic ideas or chord progressions for me to look through. And somewhere in there, there's going to be a computer glitch or random quirk, which could take me in a completely unexpected direction."