A McKinsey report from Michael Chui, James Manyika, and Mehdi Miremadi looked at the detailed work activities of more than 800 occupations across 54 countries to study the technical potential for automation and found that almost half of work activities globally could be automated using current technology. However, just because something can be automated doesn't mean it will be. The cost of developing and deploying the hardware and software for automation must be considered, as well as the supply-and-demand dynamics of labor. Other factors include the relative superiority of automation, and regulatory and social acceptance of automation for any particular task or occupation. Jobs that are most vulnerable to automation are highly structured tasks in predictable environments.

This article was published as a part of the Data Science Blogathon. If you are on the path of learning data science, then you definitely have an understanding of what machine learning is. In today's digital world everyone knows what Machine Learning is because it was a trending digital technology across the world. Every step towards adaptation of the future world leads by this current technology, and this current technology is led by data scientists like you and me . Here we only discuss machine learning, If you don't know what it is, then we take a brief introduction to it: Machine learning is the study of the algorithms of computers, that improve automatically through experience and by the use of data. This is the simple definition of machine learning, and when we go into deep then we find that there are huge numbers of algorithms that are used in model building.

In 2015, I got obsessed with the idea of driverless trucks and started Starsky Robotics. In 2016, we became the first street-legal vehicle to be paid to do real work without a person behind the wheel. In 2018, we became the first street-legal truck to do a fully unmanned run, albeit on a closed road. In 2019, our truck became the first fully-unmanned truck to drive on a live highway. I remain incredibly proud of the product, team, and organization we were able to build; one where PhDs and truck drivers worked side by side, where generational challenges were solved by people with more smarts than pedigree, and where we discovered how the future of logistics will work.

DeepSig, a company developing AI to transform wireless for 5G, IoT, and security, raised $5M in its Series A Financing, adding to the $3.5M previously raised. Leawood Venture Capital led the Series A round with participation by Scout Ventures, Blu Venture Investors, and Lockheed Martin Ventures. The additional funding will accelerate DeepSig's AI and machine learning (ML) software development and deployment to improve performance and security while reducing power consumption and cost in 5G and other wireless systems. "We are excited to include DeepSig as a portfolio company in our Fund. Their proven leadership team, combined with their groundbreaking patented technology will have a significant impact across wireless access, 5G networks, and defense markets," said Brendan Fallis, Co-Founder and Managing Partner of Leawood Venture Capital.

Whether you're intrigued or sceptical about it, use of facial recognition technology is growing – and now Fujitsu claims to have developed a way to help track emotions better too. The company's laboratories have come up with an AI-based technology that can track subtle changes of expression such as nervousness or confusion. Companies like Microsoft are already using emotion tools to recognise facial expression, but they are limited to eight "core" states: anger, contempt, fear, disgust, happiness, sadness, surprise or neutral. The current technology works by identifying various action units (AUs) – that is, certain facial muscle movements we make and which can be linked to specific emotions. For example, if both the AU "cheek raiser" and the AU "lip corner puller" are identified together, the AI can conclude that the person it is analysing is happy.

Schneider Electric recently debuted factory upgrades that it claims make its Lexington, KY, factory the first smart factory in the United States. The factory uses technology like augmented reality to give workers live operational data about machines on the floor. And the change resulted in significant improvements in efficiency: a 90% reduction of paperwork and a 20% reduction in the mean repair time. Smart factory owners looking to make the next leap forward in the digital industrial revolution are turning to advanced technology like artificial intelligence and big data. Here are six smart factory developments we're likely to see within the next year.

The fear of robots coming for your job is one of the many challenges confronting 21st-century workers, but the machines aren't ready to take on every industry just yet. Bridgewater Associates, the massive hedge fund founded by legendary investor Ray Dalio, just released a report on the changing relationship between labour and capital in the US. One of the big factors the Bridgewater authors highlighted was the ongoing rise in automation across industries, which they noted could be a support for corporate profits in the years to come as more efficient robots and software potentially replace slower and error-prone human labour. Bridgewater cited a 2016 report from consulting firm McKinsey & Company that looked at which industries in the US were most susceptible to being automated. The McKinsey report used data from the Department of Labour to estimate how much time workers in various industry sectors spent doing different types of tasks, and which of those tasks could, theoretically, be automated using present technology.

Robots aren't replacing everyone, but a quarter of U.S. jobs will be severely disrupted as artificial intelligence accelerates the automation of existing work, according to a new Brookings Institution report. The report, published Thursday, says roughly 36 million Americans hold jobs with'high exposure' to automation - meaning at least 70 percent of their tasks could soon be performed by machines using current technology. Among those most likely to be affected are cooks, waiters and others in food services; short-haul truck drivers; and clerical office workers. Robots aren't replacing everyone, but a quarter of U.S. jobs will be severely disrupted as artificial intelligence accelerates the automation of today's work, according to a new Brookings Institution report. 'That population is going to need to upskill, reskill or change jobs fast,' said Mark Muro, a senior fellow at Brookings and lead author of the report.

Artificial Intelligence, or AI, is everywhere at CES 2019 and may be the hottest topic in conference sessions and on the exhibit floor. There are 490 exhibitors in the directory under the heading "Artificial Intelligence" and it seems like most of the other 4,000 are talking about it as well. With all the benefits of AI being touted for independent-living seniors -- well, for everyone, really -- it's enough to cause a conscientious family caregiver to say "I have to go buy an AI for my senior loved one." Then again, many of the technology devices, appliances, cars, smartphones and more we buy in the future will have AI in them -- and that will be a good thing. Strike that, it will be a GREAT thing.

As the automation of physical and knowledge work advances, many jobs will be redefined rather than eliminated--at least in the short term. The potential of artificial intelligence and advanced robotics to perform tasks once reserved for humans is no longer reserved for spectacular demonstrations by the likes of IBM's Watson, Rethink Robotics' Baxter, DeepMind, or Google's driverless car. Just head to an airport: automated check-in kiosks now dominate many airlines' ticketing areas. Pilots actively steer aircraft for just three to seven minutes of many flights, with autopilot guiding the rest of the journey. Passport-control processes at some airports can place more emphasis on scanning document bar codes than on observing incoming passengers.