One sector that is expected to boom over the next decade is artificial intelligence. There are many businesses that claim they're part of AI development, so it's hard to know which shares will give the clearest exposure to AI and deliver good returns. All of the top US businesses are doing something with AI one way or another. Microsoft, Alphabet (Google), Facebook, Amazon and Apple are all trying to make their technology better with AI. If it's hard to pick one winner out of a group then why not just buy the whole group?

The Microsoft AI Residency program is a 12-month role designed to advance your career in machine learning research and engineering. The goal of the AI Residency is to help residents become creative and productive AI Researchers, Scientists and Engineers. Residents will gain skills and hands-on experience working on practical AI and machine learning problems that help tackle some of society's toughest challenges. In our program, you will have the opportunity to work alongside prominent researchers and engineers in either Redmond, WA or Cambridge, UK and contribute to research and products that impact billions of people. Within the 12 months, residents will work on two projects that are assigned based on mutual interest and each resident will work closely with project leads and dedicated mentors.

On Tuesday, career and job site LinkedIn released its annual "Emerging Jobs" list, which identifies the roles that have seen the largest rate of hiring growth from 2015 through this year. No. 1 on the list: Artificial Intelligence Specialist -- typically an engineer, researcher or other specialty that focuses on machine learning and artificial intelligence, figuring out things like where it makes sense to implement AI or building AI systems. Hiring for this role has been tremendous, growing 74% annually in the past 4 years alone. "AI has infiltrated every industry, and right now the demand for people skilled in AI is outpacing the supply for it," Guy Berger, the principal economist at LinkedIn, tells MarketWatch. "This is the third year in a row a role related to machine learning or artificial intelligence has topped the list, and we can only expect demand to increase."

Paige Dickie develops Artificial Intelligence (AI) and digital strategy for Canada's banking sector at the Vector Institute for Artificial Intelligence in Toronto. She began her career in management consulting -- much to the disappointment of her father, an engineer -- because she had earned advanced engineering degrees in biomedical and mechanical engineering. Dickie initially worked at McKinsey, the global consulting firm, helping multinational financial institutions across a range of fields from data strategy and digital transformation to setting up innovation centers. She recently joined Vector to lead what she describes as "an exciting project with Canada's banking industry. It's an industry-wide, sector-wide, country-wide initiative where we have three different work streams -- a consortium work stream, a regulatory work stream, and a research-based work stream." Knowledge@Wharton interviewed Dickie at a recent conference on artificial intelligence and machine learning in the financial industry, organized in New York City by the SWIFT Institute in collaboration with Cornell's SC Johnson College of Business.

The U.S. Department of Veterans Affairs (VA) established the National Artificial Intelligence Institute (NAII) for advancing the health and well-being of Veterans, as part of the commemoration of National Veterans and Military Families Month in November. The new NAII is incorporating input from Veterans and its partners across federal agencies, industry, nonprofits and academia, to prioritize and realize artificial intelligence (AI) research and development that is meaningful to Veterans and the public. "VA has a unique opportunity to be a leader in artificial intelligence," said VA Secretary Robert Wilkie. "VA's artificial intelligence institute will usher in new capabilities and opportunities that will improve health outcomes for our nation's heroes." VA is an ideal environment for advancing AI technology to benefit Veterans.

For instance, Ericsson predicts in the latest Mobility Report that by the end of 2019 there will be 1.3 billion cellular IoT connections worldwide. By 2025 this number is expected to jump to 5 billion. Meanwhile, McKinsey estimates* that the economic value to be generated by IoT globally will amount to $3.9–11.1 trillion per year by 2025, and a focus in 2020 and beyond will be connectivity driving valuable outcomes. As enterprises become "digitized" and enable more connected machines, sensors and solutions, the current computing power done in the cloud simply won't be fast enough to optimize performance in real-time. In order to monitor, analyze and optimize connected IoT applications, enterprises will need computing power done near the edge.

You might know Moody's Corporation for its credit rating agency, Moody's Investors Service, trusted by bond investors for opinions on credit risk. But the company, founded way back in 1909, grew ever-larger, and in 2007, Moody's Analytics was established to focus on non-rating activities – including economic research, consulting services and software development. Today, the employees of Moody's Analytics include a large number of machine learning and deep learning experts. To find out more about the business, we quizzed one such expert, Ashit Talukder, head of machine learning at Moody's Analytics, who previously spent 12 years at NASA's Jet Propulsion Laboratory and served as the CTO of the US Department of Labor. Q: Most people know Moody's as a credit rating agency.

Some AI systems achieve goals in challenging environments by drawing on representations of the world informed by past experiences. They generalize these to novel situations, enabling them to complete tasks even in settings they haven't encountered before. As it turns out, reinforcement learning -- a training technique that employs rewards to drive software policies toward goals -- is particularly well-suited to learning world models that summarize an agent's experience, and by extension to facilitating the learning of novel behaviors. Researchers hailing from Google, Alphabet subsidiary DeepMind, and the University of Toronto sought to exploit this with an agent -- Dreamer -- designed to internalize a world model and plan ahead to select actions by "imagining" their long-term outcomes. They say that it not only works for any learning objective, but that Dreamer exceeds existing approaches in data efficiency and computation time as well as final performance.

The digital networking of camera systems presents the prospects of improving the ways, where resources are used to design procedures efficiently and also reduce costs. FREMONT, CA: As per a research, firm Statista, there are more than 20 billion end devices that have been already networked through the Internet, and by the next year, the number will increase more than three times by. The end devices have become more intelligent and efficient, which is driven by the advancement conducted in artificial intelligence (AI), machine learning, and even 5G. IoT helps the cameras to assist the users in increasing their understanding of the behaviors of the passengers and employees. The knowledge about different technologies opens up new opportunities for advancing the procedures and reduces downtime.

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