SoftBank Group Corp. fell as much as 10 percent after a provider of satellite-based internet service that it invested in filed for bankruptcy, ceding some gains from an unprecedented plan to sell assets and buy back shares. OneWeb made the filing late Friday U.S. time after raising about $3.3 billion in debt and equity financing from shareholders including SoftBank, Airbus SE and Qualcomm Inc. since its inception. At least $1 billion of that came from SoftBank, which said it first invested in December 2016 and declined to give a total amount. It is the latest blow to SoftBank founder Masayoshi Son, who last week unveiled a plan to raise $41 billion to buy back shares and slash debt. The announcement sent the shares soaring more than 50 percent in just a few days.

Microsoft is pulling out of an investment in an Israeli facial recognition technology developer as part of a broader policy shift to halt any minority investments in facial recognition startups, the company announced late last week. The decision to withdraw its investment from AnyVision, an Israeli company developing facial recognition software, came as a result of an investigation into reports that AnyVision's technology was being used by the Israeli government to surveil residents in the West Bank. The investigation, conducted by former U.S. Attorney General Eric Holder and his team at Covington & Burling, confirmed that AnyVision's technology was used to monitor border crossings between the West Bank and Israel, but did not "power a mass surveillance program in the West Bank." Microsoft's venture capital arm, M12 Ventures, backed AnyVision as part of the company's $74 million financing round which closed in June 2019. Investors who continue to back the company include DFJ Growth and OG Technology Partners, LightSpeed Venture Partners, Robert Bosch GmbH, Qualcomm Ventures, and Eldridge Industries.

The number of ethical guidelines, frameworks and principles on AI just keeps growing and growing. International organisations, national regulators, parliamentary committees, even the corporate sector, are overflowing with documents proclaiming the need for AI to be ethical. Of course, AI technologies (AITs) cannot themselves be ethical. AITs are, whatever their sophistication, speed and processing power, still just technologies. So, AI ethics, at least for public policy, really refers to the ethics of AI development and use by humans, in specific social, institutional and political situations.

We live in an age where we have unprecedented access to almost any information we need. With the emergence of new technology like artificial intelligence (AI), facial recognition, big data and more, the human experience is being changed forever. Almost anything you need is just a tap away; but this access comes at a price--data for data. A simple online search may seem harmless, but before you know it, you're being bombarded with ads offering you exactly what you were looking for. How exactly does this work?

Human faces pop up on a screen, hundreds of them, one after another. Some have their eyes stretched wide, others show lips clenched. Some have eyes squeezed shut, cheeks lifted and mouths agape. For each one, you must answer this simple question: is this the face of someone having an orgasm or experiencing sudden pain? Psychologist Rachael Jack and her colleagues recruited 80 people to take this test as part of a study1 in 2018.

We live in an age where we have unprecedented access to almost any information we need. With the emergence of new technology like artificial intelligence (AI), facial recognition, big data and more, the human experience is being changed forever. Almost anything you need is just a tap away; but this access comes at a price--data for data. A simple online search may seem harmless, but before you know it, you're being bombarded with ads offering you exactly what you were looking for. How exactly does this work?

Breakthroughs in artificial intelligence (AI) include both simple quality of life upgrades and transformative innovations spanning every industry, from autonomous vehicles to medical diagnostic tools. Within these numerous technologies, there are a number of applications well worth patenting, begging the question: do any of your AI discoveries fall under intellectual property (IP)? By asking this question, businesses can take steps to protect their most valuable innovations and ensure they do not fall into the wrong hands. Do not doubt that plenty of people are already protecting their AI inventions. Since the 1960s, more than 300,000 applications for AI-related patents have been filed, and over 1.5 million scientific papers have been published. The pace has recently quickened, however.

Legal technology is currently receiving a lot of attention from various angles. In this contribution we describe the main technical components of a system that is currently under development in the European innovation project Lynx, which includes partners from industry and research. The key contribution of this paper is a workflow manager that enables the flexible orchestration of workflows based on a portfolio of Natural Language Processing and Content Curation services as well as a Multilingual Legal Knowledge Graph that contains semantic information and meaningful references to legal documents. We also describe different use cases with which we experiment and develop prototypical solutions.

Manufacturers and suppliers commonly offer maintenance contracts to companies who purchase operation-critical equipment. A preventative maintenance application based on a machine learning (ML) model can be used to help avoid failures that could impact business. To build the model, the manufacturer or supplier must spend time, money, and effort. However, to eliminate the costs of a maintenance contract, the customer could duplicate the model and manage the maintenance without the supplier's assistance. To build a machine learning (ML) model for maintenance, an appropriate training set must be collected and labeled; the architecture and training parameters must be chosen for optimal accuracy–speed trade-offs for the algorithm; and computing time is required to train it.

Technology is Chicago's fastest-growing industry sector, having grown more 270 percent over the last decade, according to World Business Chicago. And 2019 was a model year that not only encapsulated the growth of technology in the city but also positioned Chicago for further success in 2020 and beyond. Influential leaders in tech launched Chicago's Plan for 2033, or P33, to enhance the city's viability as a global tech hub with a strong and diverse workforce through the next decade. Mayor Lori E. Lightfoot said on Chicago Tech Day that 15 local tech companies have added or will be adding 2,000 jobs through 2020. Uber announced it would be bringing that same number of jobs to Chicago over the next three years and spending more than $200 million annually on the city. But it isn't just major initiatives and companies with household names that will be bringing continued success to Chicago tech. Smaller startups entering the city's tech scene are shaping everything from mental health care to cryptocurrency trading to vehicle leasing. We found 50 such companies -- all less than three years old -- that are poised for growth in the coming year. Brett Quillen contributed in writing this report. Interested in Chicago tech?See all open roles on Built In CHI Arturo wants to take property risk management to the skies by using drones and satellite, aerial and ground imagery to assess residential and commercial property characteristics. The data it collects is powered by predictive analytics to give clients that lend, insure or invest in properties the ability to minimize risk and determine market patterns.