Artificial Intelligence (AI) and Machine Learning (ML) products are unique. They hold enormous power and are by definition constantly changing. Due to the level of sophistication involved, the development process for AI products is distinct from traditional products. In this presentation, Ria Sankar, Director of Program Management at Microsoft, introduces the best practices for developing AI products with insight, integrity, and consistency. Ria Sankar is a founding member of the AI for Good Research Lab at Microsoft.
Various scoring functions have been proposed to quantify the quality of such communities. In this paper, we argue that the popular scoring functions suffer from certain limitations. We identify the necessary features that a scoring function should incorporate in order to characterize good community structure and propose a new scoring function, CEIL (Community detection using External and Internal scores in Large networks), which conforms closely with our characterization. We also demonstrate experimentally the superiority of our scoring function over the existing scoring functions. Modularity, a very popular scoring function, exhibits resolution limit, i.e., one cannot find communities that are much smaller in size compared to the size of the network.
Last year, Intel partnered with Lady Gaga on the Super Bowl Halftime Show to showcase its latest aerial technology called "Shooting Star." Intel did a reprise performance of its Shooting Star technology for Singapore's 52nd birthday this past week. Instead of fireworks, the tech-savvy country celebrated its National Day Parade with a swarm of 300 LED drones animating the night sky with shapes, logos, and even a map of the country. Intel's global drone chief, Anil Nanduri, explained, "There's considerably more operational complexity in handling a 300 drone fleet, compared with 100 drones in a show. You may be able to juggle three, but if you juggle nine, you may have to throw them higher and faster to get more time."