Industrial production is one of the dirtiest corners of the corporate world. A startup from former Google engineers thinks it can clean it up with artificial intelligence. Phaidra, a company based in Seattle, sells AI software to automate building controls for power plants and other industrial giants. For several years, DeepMind has let its AI system manage the temperature controls inside Google data centers, ultimately shaving huge chunks off the company's electricity bill. Phaidra's algorithms are designed to select the most efficient temperature for unique facilities, such as a steel mill or a vaccine manufacturer, and identify when equipment starts to lag in performance.

The Air Force Research Laboratory (AFRL) awarded BAE Systems a $7.8 million contract to develop tightly integrated machine learning software as part of the Multi-Sensor Exploitation for Tactical Autonomy (META) program. This technology will enable advanced situational awareness and automatic target recognition (ATR). Under the terms of the award, BAE Systems' FAST Labs research and development organization will provide Environmentally Adaptive Geospatial Learning and Exploitation, an innovative suite of machine learning and fusion algorithms. The system integrates multiple elements of the company's extensive autonomy portfolio to provide high confidence detection, tracking, identification, and intent understanding for critical mobile targets in contested environments, including targets under camouflage, concealment, and deception. "With the addition of environmentally adaptive processing, this solution bridges a critical gap in machine learning," said Mark Kolba, program manager for BAE Systems' FAST Labs.

General Electric Company is an American multinational conglomerate incorporated in New York City and headquartered in Boston. As of 2018, the company operates through the following segments: aviation, healthcare, power, renewable energy, digital industry, additive manufacturing and venture capital and finance. If you have forgotten your password you can reset it here.

In September 2019 Alan embarked on a first-of its-kind Masters programme to explore the transformational potential of Applied Artificial Intelligence for industry. The course, delivered by Cranfield University was developed in collaboration with Professor Nick Colosimo, a leading technologist from BAE Systems and Visiting Professor to the University. Alan explained how the course has helped him, not only in his own career development, but in creating a community of experts for the business. A community that is already bringing innovative solutions back to the business. Alan is currently in the third and final year of his studies and is starting work on his final project, a dissertation which carries a large chunk of his final score. Alan is looking to explore the sustainability of AI.

Rockwell Automation, Inc. and Microsoft Corp. announced a five-year partnership expansion to develop integrated, market-ready solutions that help industrial customers improve digital agility through cloud technology. By combining each company's expertise in the industrial and IT markets, respectively, teams can work together more seamlessly, enabling industrial organizations to save on infrastructure costs, speed time-to-value, and increase productivity. Microsoft and Rockwell are working to deliver innovative edge-to-cloud-based solutions that connect information between development, operations and maintenance teams through a singular, trusted data environment. This will allow development teams to digitally prototype, configure and collaborate without investing in costly physical equipment. This unified information environment also enables IT and OT teams to not only securely access and share data models across the organization, but with their ecosystem of partners as well.

General Electric is engaged in a broad range of research and development activities in artificial intelligence, with the dual objectives of improving the productivity of its internal operations and of enhancing future products and services in its aerospace, industrial, aircraft engine, commercial, and service sectors. Many of the applications projected for AI within GE will require significant advances in the state of the art in advanced inference, formal logic, and architectures for real-time systems. New software tools for creating expert systems are needed to expedite the construction of knowledge bases. Further, new application domains such as computer -aided design (CAD), computer- aided manufacturing (CAM), and image understanding based on formal logic require novel concepts in knowledge representation and inference beyond the capabilities of current production rule systems. Fundamental research in artificial intelligence is concentrated at Corporate Research and Development (CR&D), with advanced development and applications pursued in parallel efforts by operating departments.

This paper introduces structured machine learning regressions for prediction and nowcasting with panel data consisting of series sampled at different frequencies. Motivated by the empirical problem of predicting corporate earnings for a large cross-section of firms with macroeconomic, financial, and news time series sampled at different frequencies, we focus on the sparse-group LASSO regularization. This type of regularization can take advantage of the mixed frequency time series panel data structures and we find that it empirically outperforms the unstructured machine learning methods. We obtain oracle inequalities for the pooled and fixed effects sparse-group LASSO panel data estimators recognizing that financial and economic data exhibit heavier than Gaussian tails. To that end, we leverage on a novel Fuk-Nagaev concentration inequality for panel data consisting of heavy-tailed $\tau$-mixing processes which may be of independent interest in other high-dimensional panel data settings.

Raytheon Co. announced on Monday it has begun work on a machine-learning technology allowing machines to teach machines through artificial intelligence use. The $6 million contract is one of four, valued at a total of $20.9 million, between the U.S. Defense Research Projects Agency and Raytheon BBN Technologies, SRI International, BBN Technologies, Teledyne Scientific & Imaging and BAE Systems. The new deal calls for development of systems able to communicate information and the conditions of the initial learning, and recommended strategies and situations calling for those strategies. Known as CAML, or Categorical Abstract Machine Language, it uses a process similar to that in a video game; instead of rules, the system offers a list of choices and identification of a goal. By repeatedly playing the game, the system will learn the best way to achieve the goal.

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Video-based interviews, either on Skype or Facetime or as recorded links, have been used for some years, but now a new and tricky feature has become popular: HR tech companies have begun to deploy artificial intelligence (AI) to assess candidates even as their skills are being tested on several parameters. Companies are using AI-based voice recognition and facial recognition software that reads the candidate in a way that no human can. When a candidate answers questions, AI software reads expressions and measures voice modulation to get into the mind of the candidate. Lying and misleading expressions can be caught. Candidates hear an automated voice and see no one at the other end as they get time to answer questions while looking into the camera.