In 2008, the National Academy of Engineering presented 14 Grand Challenges that, if solved, had the potential to radically improve the world. Thanks to recent breakthroughs in artificial intelligence – specifically, the advent of deep neural networks -- we're on pace to solve some of them, Google Senior Fellow Jeff Dean said last week at the Strata Data Conference. The Academy certainly didn't lack for ambition 10 years ago when it drew up the 14 Grand Challenges. Delivering a solution for any one of them – such as providing energy from nuclear fusion or finding out how to sequester carbon – could have a dramatic impact on billions of people's lives. As a result of advances in deep learning techniques, the presence of enormous data collections, and the availability of massive server clusters, we will be able to compute our way toward solving them, Dean told a packed room of attendees during his presentation Thursday afternoon at the San Jose McEnery Convention Center.
A new $10 million XPrize competition wants anyone to be able to control a robot and carry out tasks from 100 kilometres away. Not just that, but untrained users should be able to feel, hear and touch their surroundings too. This latest ambitious X Prize challenge – the ANA XPrize Avatar Challenge – was launched by the non-profit today at the SXSW festival in Austin, Texas. It is sponsored by the Japanese airline ANA. Teams should submit their plans to a panel of expert judges by the end of January 2019.
Sales prediction is an important part of modern business intelligence. First approaches one can apply to predict sales time series are such conventional methods of forecasting as ARIMA and Holt-Winters. But there are several challenges while using these methods. They are: multilevel daily/weekly/monthly/yearly seasonality, many exogenous factors which impact sales, complex trends in different time periods. In such cases, it is not easy to apply conventional methods.
This past weekend, BuildingSP participated in the AEC Hackathon 5.0 in Oakland, California, and we wanted to pass on a very important discovery. Hackathons are intended to break participants out of normal routines and explore the feasibility of projects that can be achieved in a short timeframe using an ad-hoc team. We entered into the weekend with an insight that reflected an important issue: Computational fluid dynamic (CFD) models for heat transfer in buildings can be validated using inexpensive Internet of Things (IoT) technology. Using our hackathon project to explore this insight yielded more value than we anticipated and we think you'll find it exciting. This post describes what we learned and why it's important.