Robots are going to play an integral role in hospital care soon. At least that's what Julie Shah -- an MIT professor who leads the Interactive Robotics Group at the university's Computer Science and Artificial Intelligence Laboratory -- is working on.

Macy's is testing a mobile tool using artificial intelligence that lets shoppers get answers customized to the store they're in -- like where a particular brand is located or what's in stock -- that they would normally ask a sales associate face-to-face. The tool, which the nation's largest department store chain calls a "mobile companion," can be accessed for now through a browser and will accept questions in 10 U.S. locations about products, services and facilities. It uses natural language and offers feedback in seconds. It's developed by IBM Watson -- the Jeopardy-winning "cognitive computing" service and is designed to keep learning more about the store's customers. That's a key element as Macy's seeks to spur sluggish sales, make being at the store more enjoyable and distinguish itself from online portals and specialty retailers.

Google's acquisition of artificial intelligence startup DeepMind in 2014 has resulted in the search giant making a 15 percent improvement in power usage efficiency, DeepMind's co-founder reportedly said. Google reportedly paid 650 million for the London-based artificial intelligence firm founded by neuroscientist Demis Hassabis, Shane Legg and Mustafa Suleyman. The AI built by the company mastered playing the Atari video games but most of its projects are yet to translate into revenue. However, it is helping the tech giant tackle the massive energy bills it deals with because of its data centers. Google said it used 4,402,836 MWh of electricity in 2014, equivalent to the average yearly consumption of about 366,903 U.S. family homes, according to Bloomberg.

Facebook unveiled a new laser-based concept for high-speed internet that will bypass the need for dedicated wavelength spectra and government licenses that come with them. Published Tuesday in the journal Optica, the technique was developed by researchers at Facebook's Connectivity Lab. The team is exploring a variety of technologies, including high-altitude long-endurance planes, satellites and lasers." It calls its new concept, which also uses drone technology, free-space optical communication. Explaining their rationale behind turning to laser for data transmission, the researchers say in the paper: "While optical communications have become the de facto standard for high-throughput wired communication channels, microwave and millimeter wave carrier frequencies are still the standard for wireless links. However, the limited availability of spectrum restricts the data rates that can be achieved through these channels."

Time Series prediction is a difficult problem both to frame and to address with machine learning. In this post you will discover how to develop neural network models for time series prediction in Python using the Keras deep learning library. The problem we are going to look at in this post is the international airline passengers prediction problem. This is a problem where given a year and a month, the task is to predict the number of international airline passengers in units of 1,000. Below is a sample of the first few lines of the file.

Please attach one file in ."pdf" Please attach one file in ".pdf" containing your letter of interest (Max. Please attach the Statement of past and proposed future research (2-3 pages) in .pdf The reference letters shall be submitted directly by the referees. Each referee you indicate in this form shall automatically receive an e-mail with instructions to submit the recommendation letter to BCAM.

Google just paid for part of its acquisition of DeepMind in a surprising way. The internet giant is using technology from the DeepMind artificial intelligence subsidiary for big savings on the power consumed by its data centers, according to DeepMind Co-Founder Demis Hassabis. In recent months, the Alphabet unit put a DeepMind AI system in control of parts of its data centers to reduce power consumption by manipulating computer servers and related equipment like cooling systems. It uses a similar technique to DeepMind software that taught itself to play Atari video games, Hassabis said in an interview at a recent AI conference in New York. The system cut power usage in the data centers by several percentage points, "which is a huge saving in terms of cost but, also, great for the environment," he said.

Apple fixed this error shortly after its virtual assistant was first released in 2011. But a new contest shows that computers still lack the common sense required to avoid such embarrassing mix-ups. The results of the contest were presented at an academic conference in New York this week, and they provide some measure of how much work needs to be done to make computers truly intelligent. The Winograd Schema Challenge asks computers to make sense of sentences that are ambiguous but usually simple for humans to parse. Disambiguating Winograd Schema sentences requires some common-sense understanding.

Would you like to see a machine that can carry on an intelligent and helpful conversation? Want to be part of the next wave of AI-driven innovation in customer care? If you answered yes to the above, you could be just what we're looking for... True AI is a venture backed artificial intelligence startup that automates customer support using machine learning/deep learning. Our product is the result of our own research, building on top of cutting-edge deep learning breakthroughs. The founders are deep learning experts, with backgrounds at labs of names such as Yoshua Bengio and Amazon.