Abstract-- Logic synthesis requires extensive tuning of the synthesis optimization flow where the quality of results (QoR) depends on the sequence of optimizations used. Efficient design space exploration is challenging due to the exponential number of possible optimization permutations. Therefore, automating the optimization process is necessary. In this work, we propose a novel reinforcement learning-based methodology that navigates the optimization space without human intervention. We demonstrate the training of an Advantage Actor Critic (A2C) agent that seeks to minimize area subject to a timing constraint. Using the proposed methodology, designs can be optimized autonomously with no-humans in-loop. Evaluation on the comprehensive EPFL benchmark suite shows that the agent outperforms existing exploration methodologies and improves QoRs by an average of 13%. Logic synthesis transforms a high-level description of a design into an optimized gate-level representation. Modern logic synthesis tools represent a given design as an And-Inverter Graph (AIG), which encodes representative characteristics for optimizing Boolean functions.

A new paper from researchers at the University of Southern California's Brain and Creativity Institute considers a novel path toward creating robots with'feelings.' The key, according to researchers Kinson Man and Antonio Damasio, is homestasis, a self-preservation principle by which living creatures seek to maintain internal biological equilibrium by avoiding certain environments or kinds of stimuli. Were robots to be programmed with a homeostatic sense of self-preservation, would that put them on a path toward developing true feelings? According to a Science News report on the paper, Man and Damasio consider the most promising lead for feeling robots to come through the combination of soft robotics and deep learning, which when combined might approximate a homeostatic reaction to negative environmental stimuli. Man and Domasio point to a 1954 experiment by W. Ross Ashby that demonstrated how homeostatic sensing might be translated into robotics.

Amazon will take the next step in its bid to take over the food delivery market with its own company-branded grocery stores. In a report from CNET, an Amazon spokesperson confirmed the company's intention to open the first-ever Amazon-branded grocery store in Los Angeles. While the company hasn't released many details, a job listing discovered by CNET suggest the store will be'Amazon's first grocery store' meaning it will likely carry the e-tailing giant's brand name. Amazon is making its first foray into company-branded grocery stores. The outlets will reportedly offer cheaper options compared to the Amazon-owned Whole Foods.

Farmland in Fukushima that was rendered unusable after the disastrous 2011 nuclear meltdown is getting a second chance at productivity. A group of Japanese investors have created a new plan to use the abandoned land to build wind and solar power plants, to be used to send electricity to Tokyo. The plan calls for the construction of eleven solar power plants and ten wind power plants, at an estimated cost of $2.75 billion. Fukushima has been aggressively converting land damaged by the 2011 meltdown, such as this golf course (pictured above) into a source of renewable energy. A new $2.75 billion plan will add eleven new solar plants and ten wind power plants to former farmland The project is expected to be completed in March of 2024 and is backed by a group of investors, including Development Bank of Japan and Mizuho Bank.

How can we bridge the gap between patient expectations and the complex reality of medical diagnosis? The answer, and the future of healthcare, lies in making self-service work through AI, AR, and video. The first two decades of this century saw an information revolution, thanks to widespread internet access. That, in turn, has led to a self-service revolution. We use mobile apps to book theatre tickets, check our bank balances, find the best restaurants.

Filing a patent is the clerical equivalent of pulling teeth -- at least in the U.S. It first requires inventors to determine the type of intellectual property (IP) protection they require (i.e., utility, design, or plant). Then they're on the hook to conduct a United States Patent and Trademark Office (USPTO) database search for similar inventions. If and only if the novelty of their idea passes muster are they allowed to proceed to the next step, which is preparing an application and fees. The system has motivated people like former aerospace engineer Dr. Stephen Thaler to turn to AI in pursuit of a better way. He, along with a team of legal experts and engineers, developed DABUS, a "creativity machine" that's able to generate ideas without human intervention.

Intelligent Business Applications are a significant priority for Microsoft. We just announced our future direction, Microsoft Dynamics 365 in July of 2016. We've seen tremendous momentum in business apps with the launch of our ground-breaking ERP in the cloud and nearly doubling our CRM Online business in FY16. The power of One Microsoft is where we differentiate Dynamics 365 from any other business application provider in the market. We're tying together the power of business processes and data, productivity tools, big data, IoT and device data, and advanced analytics to elevate our message and story around Intelligent Business Applications that help companies drive digital transformation to engage customers, empower employees, optimize operations ad transform product.

Research suggests that airline passengers are open to personalization and even expect airlines to anticipate their needs. Singapore Airlines is one of Panasonic Avionics' partners leveraging passenger data to create a more consistent experience throughout a customer's entire flight journey. The two companies collaborated to create a mobile app, myKrisWorld, that acts as a personalized portal for passengers at every stage of their travel: from pre-flight booking, mobile check-in, and luggage tracking. They can also customize the portal to a specific language, bookmark favorite content and be served recommended content based on their browsing and viewing history.

Lightning regularly kills people and animals, starts fires, damages power lines and keeps aircraft grounded. Until now it has been virtually impossible to predict lightning, with no simple technology for predicting when and where it will strike the earth. Engineers at the Ecole Polytechnique Federale de Lausanne's (EPFL) School of Engineering developed a simple and inexpensive system to predict when lightning will strike. The research led by Farhad Rachidi, resulted in a method of predicting lightning between 10 and 30 minutes before it strikes, within a 30km radius. Using a combination of Artificial Intelligence and meteorological data, researchers are now planning to use this technology in the European Laser Lightning Rod project, a project designed to draw lightning away from areas that are susceptible to lightning damage, the project is shown in the video bellow.

After looking at standard ECG tests, Artificial Intelligence (AI) can help identify patients most likely to die of any medical cause within a year, claim researchers. To reach this conclusion, researchers from Geisinger Health System in Pennsylvania analyzed the results of 1.77 million ECGs and other records from almost 400,000 patients. The team used this data to compare machine learning-based models that either directly analyzed the raw ECG signals or relied on aggregated human-derived measures (standard ECG features typically recorded by a cardiologist) and commonly diagnosed disease patterns. The neural network model that directly analyzed the ECG signals was found to be superior for predicting one-year risk of death. Surprisingly, the neural network was able to accurately predict risk of death even in patients deemed by a physician to have a normal ECG.