In classical sculpture there is a great emphasis on movement. In the world of robotics, the emphasis is on actual motion. For the last several years Riga, Latvia-based new media sculptor Krists Pudzens has been fusing the two disciplines with his "electromechanical art." In his first major exhibition, SHIFT, Pudzens showcases a number of kinetic and interactive works created between 2007 and 2014. The show features seven objects that explore various types of perception like audio, visual and tactile sensations, but also function as "closed, introverted" systems with distinct appearances and movement.

Every time a Pokemon Go fan drains a smartphone battery chasing virtual monsters, it's a reminder that chip technology has a long way to go. The company poised to push the boundaries of mobile computing is ARM Holdings Plc, which has built a business designing chips that squeeze the most out of limited battery capacity on mobile devices, dominating 85 percent of the market. Masayoshi Son built SoftBank Group Corp. by making big, early bets on personal computers, broadband and smartphones. Now, he's spending 32 billion to buy ARM, gambling that the company's chips will find their way into self-driving cars, virtual-reality devices and machines with artificial intelligence. Pokemon Go, the hit game that relies on power-hungry GPS and camera functions to work, is showing people the limits and capabilities of their smartphones.

The history of technology is the history of human interaction with machines. Millions of years ago, we started with SOUND (voice), and soon came the WORD (text). The touchscreen made redundant the mechanical keyboard. However, 90% of human communication still happens through voice because it is natural. Unfortunately, technology progress took the time to catch up with it.

The ortho giant's purchase of French surgical robotics firm Medtech could give competitor Mazor Robotics a run for its money, according to one analyst. Zimmer Biomet has officially entered the surgical robotics market with its acquisition of a majority of shares in the French firm Medtech, maker of a robotics platform for neurological and spine procedures. The Warsaw, IN-based company, a leader in the musculoskeletal space, announced July 18 that it had purchased almost 59% of shares in Medtech and also intends to mount an all-cash simplified tender offer to acquire the remaining shares. Zimmer Biomet will continue to operate Medtech out of its current headquarters in Montepellier, France, which will also serve as a "center of excellence" for Zimmer Biomet's surgical robotics development efforts, according to a joint press release from the companies. With the Medtech acquisition, Zimmer Biomet gains the Rosa platform, which is currently used in 20 hospitals in Europe, North America, Asia, and the Middle East, according to the company's website.

Tesla's Gigafactory in the Nevada Desert is finally nearing completion. Set to open on July 29th, it will have the largest footprint of any building in the world. The 5 billion structure will produce 500,000 lithium ion batteries each year to meet demand. When it's complete, Tesla's Gigafactory in the Nevada Desert will have the largest footprint of any building in the world. At the Model 3 launch yesterday, founder Elon Musk said the 5 billion structure will produce 500,000 lithium ion batteries annually to meet demand.

For their study, researchers from New York University Shanghai and University of Hong Kong had 80 students and faculty from the University of Hong Kong participate in several experiments involving different video games. Action-based video games, for example, force the gamer to respond to visual cues. Think driving-centric games, like "Mario Kart," or first-person shooter games, such as "Unreal Tournament." Non-action games, on the other hand, include those like "Sims 2" and "Roller Coaster Tycoon," where the gamer is responsible for directing the action. In one experiment, subjects with no action-based video game experience were asked to played "Mario Kart" or a first-person shooter game.

By John Markoff For more than a decade, Silicon Valley's technology investors and entrepreneurs obsessed over social media and mobile apps that helped people do things like find new friends, fetch a ride home or crowdsource a review of a product or a movie. Now Silicon Valley has found its next shiny new thing. And it does not have a "Like" button. The new era in Silicon Valley centers on artificial intelligence (AI) and robots, a transformation that many believe will have a payoff on the scale of the personal computing industry or the commercial internet, two previous generations that spread computing globally. Computers have begun to speak, listen and see, as well as sprout legs, wings and wheels to move unfettered in the world.

The following interview is one of many included in the report. As part of our ongoing series of interviews surveying the frontiers of machine intelligence, I recently interviewed Gurjeet Singh. Singh is CEO and co-founder of Ayasdi, a company that leverages machine intelligence software to automate and accelerate discovery of data insights. Author of numerous patents and publications in top mathematics and computer science journals, Singh has developed key mathematical and machine learning algorithms for topological data analysis. David Beyer: Let's get started by talking about your background and how you got to where you are today.

Summary: I describe how the TrueSkill algorithm works using concepts you're already familiar with. TrueSkill is used on Xbox Live to rank and match players and it serves as a great way to understand how statistical machine learning is actually applied today. I've also created an open source project where I implemented TrueSkill three different times in increasing complexity and capability. In addition, I've created a detailed supplemental math paper that works out equations that I gloss over here. Feel free to jump to sections that look interesting and ignore ones that seem boring. Don't worry if this post seems a bit long, there are lots of pictures. It seemed easy enough: I wanted to create a database to track the skill levels of my coworkers in chess and foosball. I already knew that I wasn't very good at foosball and would bring down better players. I was curious if an algorithm could do a better job at creating well-balanced matches. I also wanted to see if I was improving at chess. I knew I needed to have an easy way to collect results from everyone and then use an algorithm that would keep getting better with more data. I was looking for a way to compress all that data and distill it down to some simple knowledge of how skilled people are. Based on some previous things that I had heard about, this seemed like a good fit for "machine learning." Machine learning is a hot area in Computer Science-- but it's intimidating. Like most subjects, there's a lot to learn to be an expert in the field. I didn't need to go very deep; I just needed to understand enough to solve my problem. I found a link to the paper describing the TrueSkill algorithm and I read it several times, but it didn't make sense. It was only 8 pages long, but it seemed beyond my capability to understand.

Though deals to private artificial intelligence companies -- excluding incubator/accelerator rounds -- fell 10% in Q2'16, dollar funding reached an all-time high. That was partly thanks to 3 100M mega-rounds by companies using AI: a 154M Series A round went to China-based healthcare startup iCarbonX (with the participation of Tencent, Vcanbio), a 100M growth equity round was raised by New Jersey-based Fractal Analytics (from Khazanah Nasional Berhad), and there was a 100M Series D round raised by California-based cybersecurity unicorn Cylance (from investors including Blackstone Group, Insight Venture Partners, and Khosla Ventures). Our AI category includes companies applying AI solutions to verticals like healthcare, security, advertising, and finance as well as those developing general-purpose AI tech. Nearly 70% of the deals went to startups in the United States in Q2'16. A majority of the startups raising funds were still in their early-stages: Nearly 60% of the deals went to startups raising seed/angel and Series A rounds, while mid-stage startups (Series B and C) received 12% of the deals.