Deftr, legal tech company, and Y Combinator Fellowship recipient, today announced the launch of the first AI-powered tool that helps professionals diagram intricate corporate structures. The new product reads text as it is typed in real time, then automatically turns that text into a shareable, interactive graphic illustrating a corporate structure or transaction. Named for the dynamic tax ledger used by the Ottoman Empire, Deftr helps legal and professional service firms focus on high-level, strategic work by leveraging artificial intelligence to automate manual work. From tax law and IRS guidance to corporate structuring and financial regulations, we enable users to navigate legal complexity and understand its practical consequences intuitively, simply, and cheaply. For hundreds of years the Swiss watch had been considered to be the most accurate, trust-worthy and well-designed way of telling the time – the best way to convey that crucial information to a wearer.

The world's first beer brewed with the help of artificial intelligence is now on sale. Four beers have been created, with each recipe altered based on customer feedback received by an algorithm. The system is hidden behind a Facebook Messenger bot, which takes feedback from customers and sends it onto human brewers who change recipes accordingly. IntelligentX, the company behind the beers, said the use of AI would help brewers receive and test customer feedback "more quickly than ever before". Codes printed on the bottles direct people towards the bot, which then asks a series of questions.

Dallas police used a robot to kill a shooting suspect after 5 police officers were shot dead. Some are calling this tactic a first. Dallas police officers comfort each other in honor of the officers who were killed in a massive shootout Thursday. NEW YORK--When Dallas police detonated a "bomb robot" Thursday night to take down a sniper suspect, it was believed to be the first time a robot was used by law enforcement to kill a human being in the U.S. Dallas police chief David Brown explained in a press conference that "other options would have exposed our officers to grave danger." The action raises ethical questions about the role of robots in warfare, or in this case, police work, especially given continuing breakthroughs in machine learning and artificial intelligence.

According to a report in The Information, Houston reiterated this notion at the annual Allen & Co. Sun Valley Conference this week, saying machine learning capabilities that enable more sophisticated data analysis and automated predictive behavior is "something you sprinkle on products to make them better as opposed to a new platform or product." He pointed out that hiring machine learning experts has become "more important" as a result, and they'll play bigger roles as software like Dropbox seeks ways to automate a lot of functionalities such as notifications and messages in the future, the report said. Houston's comment is in line with the trend in the broader business software landscape. Salesforce, for example, has been doubling down on its machine learning capabilities by acquiring a bunch of artificial-intelligence startups lately. Its CEO, Marc Benioff, once said: "This will be the huge shift going forward, which is that everybody wants systems that are smarter, everybody wants systems that are more predictive."

In an effort to apply data-driven insights to one of the most fundamental aspects of running a health care system, UPMC announced today that it has formed Pensiamo, an independent company that aims to help hospitals improve supply chain performance through a comprehensive source-to-pay offering, including cognitive analytics with IBM Watson Health technologies. IBM (NYSE:IBM) is a minority owner of Pensiamo. Supply chain costs are the second-largest and fastest-growing expense behind labor costs for health care providers [1]. The Institute of Medicine estimates that nearly one-third of health care spending is waste [2]. In today's dynamic environment, providers face mounting pressure to improve the effectiveness of patient care while controlling costs.

Your smartphone is about to get even smarter. As artificial intelligence and machine learning become all the more influential across the tech industry, tech giant Google has just made moves to improve its own AI capabilities by purchasing Moodstocks, a French startup that is particularly adept at helping phones recognize objects. Soon, you may be able to simply point your mobile device at whatever strikes your fancy, and have your phone tell you what it is (and perhaps tell you a bit about it). In a blog post announcement on Wednesday morning, Vincent Simonet, the head of Google France's R&D Center noted that a number of Google services already employ machine learning "to make them simpler and more useful in everyday life," including Smart Reply Inbox and Google Translate. And while Google has already "made great strides in terms of visual recognition," Simonet writes, as you can currently search for a term in Google Images and be presented with pretty decent image results, Simonet notes "there is still much to do in this area."

The secret of success is honesty and fair dealing. If you can fake those, you've got it made.

The core idea is that, when understanding, explaining and/or predicting the behavior of an object, we can choose to view it at varying levels of abstraction. The more concrete the level, the more accurate in principle our predictions are; the more abstract, the greater the computational power we gain by zooming out and skipping over the irrelevant details. Dennett defines three levels of abstraction, attained by adopting one of three entirely different "stances", or intellectual strategies: the physical stance; the design stance; and the intentional stance: The most concrete is the physical stance, the domain of physics and chemistry, which makes predictions from knowledge of the physical constitution of the system and the physical laws that govern its operation; and thus, given a particular set of physical laws and initial conditions, and a particular configuration, a specific future state is predicted (this could also be called the "structure stance").[15] At this level, we are concerned with such things as mass, energy, velocity, and chemical composition. When we predict where a ball is going to land based on its current trajectory, we are taking the physical stance.

DLA Piper will use artificial intelligence technology by Kira Systems for due-diligence document review in mergers and acquisitions. Kira's machine-learning software searches texts in contracts, then creates a summary and analysis, according to a press release announcing the deal. Such software is designed to get smarter as it is used. Jonathan Klein, chair of DLA Piper's U.S. mergers and acquisition practice, said in the press release that the technology will make due diligence faster and more efficient, and will mitigate risk throughout the due diligence practice. "We believe that this innovative technology will do for corporate transactional work what e-discovery has done for litigation," he said. DLA Piper already tried the software in its corporate, intellectual property and technology practices.

IntelligentX Brewing Co. has introduced what it calls "the world's first beer brewed by artificial intelligence." The London-based microbrewery is putting a new twist on an old tradition, using machine learning and a Facebook Messenger bot to spot trends and improve its product. "We currently live in a world where companies are using our data to target more advertising at us. We believe we can do something more useful with data," IntelligentX co-founder Hew Leith said in a statement to PCMag. "We can use data to create better products that improve over time. "In this example we [are] combining customer feedback data and a machine-learning algorithm to determine what consumers like about our beers, then brew new versions which are more finely tuned to people's tastes," he continued. "This is the future of data.