The robot revolution has long been thought of as apocalyptic for blue-collar workers whose tasks are manual and repetitive. A widely cited 2017 McKinsey study said 50 percent of work activities were already automatable using current technology and those activities were most prevalent in manufacturing. New data suggests white-collar workers -- even those whose work presumes more analytic thinking, higher paychecks, and relative job security -- may not be safe from the relentless drumbeat of automation. That's because artificial intelligence -- powerful computer tech like machine learning that can make human-like decisions and use real-time data to learn and improve -- has white-collar work in its sights, according to a new study by Stanford University economist Michael Webb and published by Brookings Institution. The scope of jobs potentially impacted by AI reaches far beyond white-collar jobs like telemarketing, a field that has already been decimated by bots, into jobs previously thought to be squarely in the province of humans: knowledge workers like chemical engineers, physicists, and market-research analysts.

Artificial Intelligence (AI) and machine learning enter the research mainstream of biopharmaceutical companies, such as GlaxoSmithKline (GSK). GlaxoSmithKline (GSK) is creating a data-focused culture and a global machine-learning team. GlaxoSmithKline's (GSK's) data-first approach to drug discovery and development comes directly from chief executive officer (CEO) Emma Walmsley and chief scientific officer (CSO) Hal Barron. Their goal is doubling the chance of successful medicines being produced by using genetically validated targets. And that demands a strong team in artificial intelligence and machine learning (AI/ML).

Increasingly variable hydrologic regimes combined with more frequent and intense extreme events are challenging water systems management worldwide. These trends emphasize the need of accurate medium‐ to long‐term predictions to timely prompt anticipatory operations. Despite in some locations global climate oscillations and particularly the El Niño Southern Oscillation (ENSO) may contribute to extending forecast lead times, in other regions there is no consensus on how ENSO can be detected, and used as local conditions are also influenced by other concurrent climate signals. In this work, we introduce the Climate State Intelligence framework to capture the state of multiple global climate signals via artificial intelligence and improve seasonal forecasts. These forecasts are used as additional inputs for informing water system operations and their value is quantified as the corresponding gain in system performance.

Leading health tech start up EQL, part of the NHS DigitalHealth.London and Google for Startups programmes, has entered into a new partnership with Raintree Systems Inc. one of the world's largest providers of specialist practice management and clinical documentation tools. Under the terms of the global alliance EQL's innovative AI-driven physiotherapy assessment tool, Phio, will form part of the patient engagement platform provided by Raintree Systems. This is part of the company's commitment to bringing the power of software and technology to specialist medical fields to enhance and extend the skills of healthcare professionals in serving their patients. Raintree Systems provides solutions to some of the largest Physical Therapy providers in the world including commercial, non-profit, educational and government agencies across the US and Canada. Phio is the debut product from EQL which launched in June, initially providing an agile triage tool that signposts users to suitable MSK care pathways.

A team of researchers from the University of Colorado Boulder are working to apply machine learning artificial intelligence (AI) in psychiatry, with a speech-based mobile app that can categorise a patient's mental health status as well as, or better than, a human can. The university research paper has been published in Schizophrenia Bulletin, and lays out the promise and potential pitfalls of AI in psychiatry. Peter Foltz, a research professor at the Institute of Cognitive Science and co-author of the paper, said: "We are not in any way trying to replace clinicians, but we do believe we can create tools that will allow them to better monitor their patients." In Europe, the WHO estimated that 44.3 million people suffer with depression and 37.3 million suffer with anxiety. Diagnosis of mental health disorders are based on an age-old method that can be subjective and unreliable, notes paper co-author Brita Elvevåg, a cognitive neuroscientist at the University of Tromsø, Norway.

Located in the Nazca Desert in southern Peru, the Nazca Lines are a collection of giant etchings that only make sense from a great height. Now AI is helping speed up the hunt for more hidden symbols--and has already had some success. Mysterious sand symbols: Since their discovery in the 1920s, the Nazca Lines have continued to mystify experts. Created between 200 BCE and 600 CE, they were made by removing stones to reveal the white sand beneath and depict various geometric shapes, people, and animals, known as geoglyphs. In 1994 they were designated a UNESCO World Heritage Site, but their purpose and meaning have continued to elude historians.

Universities have long been a source of talented leaders for industry, but an accelerating exodus of professors with expertise in artificial intelligence has caused concerns. A recent Bloomberg op-ed asked, "If industry keeps hiring the cutting-edge scholars, who will train the next generation of innovators in artificial intelligence?" This article analyzes the problem and suggests solutions. The brain drain of AI experts out of academia can be explained in simple economic terms. The demand for experts has outpaced supply, leading to sharply increased prices.

General inference problems and quantifying uncertainty have long been the cornerstone of statistical science. While machine learning advances have permeated many disciplines, inference for these procedures, and in particular, causal inference, has not been widespread. However, this is rapidly changing. As different scientific fields begin to converge on machine learning for causal inference, we thought now would be an excellent time to have a public discussion. In our roles as editors of Biostatistics, we decided to organize a series of commentaries on the topic from scholars with expertise in statistics, computer science, epidemiology, health economics, policy, and law.

Artificial Intelligence (AI) is the next big thing in the technology field and a large number of organizations are already implementing AI and the demand for professionals in AI is growing at an amazing speed. Artificial Intelligence (AI) course with ExcelR will provide you with a wide understanding of the concepts of Artificial Intelligence (AI) to make computer programs to solve problems and achieve goals in the world. Artificial Intelligence (AI) makes computers to perform tasks such as speech recognition, decision-making and visual perception which normally requires human intelligence that aims to develop intelligent machines. The basic grounding in the ExcelR's practices in AI is likely to become valuable in the field of business and profession. This course is intended to cover the concepts of Artificial Intelligence from the basics to advanced implementation.

Athenta provided surveillance and a centralized web-based platform for monitoring and management of 20 Zonal Viewing Centers and end-point devices spread across the Sultanpur, Lodhi for the festival of Guru Purab. They offered the Integrated Command and Control Center as the nerve center for all Smart City Operations working as a virtual third eye providing 24*7 operational monitoring of the entire city. Gopal Joshi, Director Sales, Athenta Technologies, said, "We are extremely pleased to be a part of such a festival where we are contributing with our solutions to keep a check on every single activity and surveillance equipment and ensuring the system and the infrastructure is up and running efficiently. Athenta aims to achieve twin purpose with this initiative i.e. to control any incident for safe procession and safety of the devotees and secondly by increasing the efficiency of the city surveillance for easy access and monitoring." The Integrated Command and Control Center takes live feed from CCTV cameras/Surveillance System, city network, automation location tracking system (ALTS), Video Management System (VMS), Variable Message System (VaMS) & Video Analytics; installed all over the city to gather inputs from various departments and applications for analysis and research for better planning and implementation of the City.