If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Not many robotics companies can boast legions of fans online, but not many robotics companies make robots quite like Boston Dynamics. Each time the firm shares new footage of its machines, they cause a sensation. Whether it's a pack of robot dogs towing a truck or a human-like bot leaping nimbly up a set of boxes, Boston Dynamics' bots are uniquely thrilling. And when a parody video circulated last month showing a CGI "Bosstown Dynamics" robot turning on its creators, many mistook it for the real thing -- a testament to how far the company has pushed what seems technologically possible. But for all its engineering prowess, Boston Dynamics now faces its biggest challenge yet: turning its stable of robots into an actual business.
Artificial Intelligence (AI) and machine learning is no more an unheard concept. AI is everywhere now and is slowly taking over routine jobs from human beings. Digital marketers and businesses are implementing AI to improve their rankings, increase sales revenue, and cut operational costs at the same time. AI is placing itself in almost every aspect of our life. Back in the 2000s, who would have thought of controlling their home appliances using Amazon Echo or Google Home?
By now, most people have interacted, often unknowingly, with artificial intelligence (AI) through increasingly ubiquitous chatbots or smart products and devices. Across industries, there is a host of far more intriguing applications of AI emerging in fields such as healthcare, manufacturing, insurance, and professional services. These use cases demonstrate that, far from replacing human intelligence, AI – when employed responsibly – is unleashing human expertise and creativity in ways that deliver tremendous value to the individual, the enterprise and even the community. Gartner projects the global business value derived from AI will reach $3.9tn by 2022, through improved customer experience, new revenue and cost reduction. Gartner predicts that decision automation--harnessing unstructured data to make sense of ambiguity--will be a key driver of this trend, growing from 2% of AI-derived value in 2018 to 16% by 2022.
According to a new study from the Institute for Public Policy Research (IPPR), nearly 10% of women work in jobs with a high potential for automation, compared with only 4% of men. So what, I hear you say. Substitute "robots" for "austerity", "the demise of unionisation", "public-sector pay freezes", "modern life" – pick any of these and women will always come off worst. Except maybe this time the pointy heads are on to something: perhaps better understanding what the risks are will give us all some agency, and even allow us to change the future. As Carys Roberts, the author of the IPPR report, tells me: "We don't even talk about risks in this area, because there are so many different factors.
NASA introduced the term "digital twin" in a 2010 technology roadmap describing the tools of space travel. Almost a decade later, "digital twin" has emerged as a key tool. It enables a terrestrial space shot. We are being shown the global Industry 4.0's evolution of Digital Twin: from automation to autonomy. We talk about "digital transformation" in the Fourth Industrial Revolution, but "digital" has been around since the Third Revolution.
WASHINGTON - The use of robots in U.S. manufacturing has more than tripled over the two decades, and has doubled in the rest of the world, replacing certain categories of worker, according to a report published Monday. As of 2017, automation in the United States had risen to 1.8 robots for every 1,000 workers from just 0.5 recorded 22 years earlier, according to research by the Federal Reserve Bank of St. Louis. The report found the highest prevalence of robots in the auto sector, with France in the lead, followed by the United States and Germany. Automation has eroded the number of intermediate "middle-skill" occupations, while the share of high-skill and low-skill positions has grown, it said. France leads the way in employing robots to build cars, using 148 robots for every 1,000 workers, compared to 136 in the United States, while Italy and Germany each use about 120, the study found.
Amazon announced last week that it will spend $700 million to train about 100,000 workers in the US by 2025, helping them move into more highly skilled jobs. The New York Times observed that with this program Amazon is acknowledging that "advances in automation technology will handle many tasks now done by people." The number of jobs which AI and machines will displace in the future has been the subject of numerous studies and surveys and op-eds and policy papers since 2013, when a pair of Oxford academics, Carl Benedikt Frey and Michael Osborne, estimated that 47% of American jobs are at high risk of automation by the mid-2030s. McKinsey Global Institute: between 40 million and 160 million women worldwide may need to transition between occupations by 2030, often into higher-skilled roles. Clerical work, done by secretaries, schedulers and bookkeepers, is an area especially susceptible to automation, and 72% of those jobs in advanced economies are held by women.
In a world where technology is changing rapidly, it can be hard for businesses to keep up with shifting consumer demands. Take how customers interact with businesses, for instance. According to a recent study by Drift, people now prefer real-time interaction as they make their purchases, meaning that just having an online storefront is no longer enough. For startups looking to grow a loyal customer base, the immediate needs of users can be especially intimidating and even seem, at times, insurmountable. Entrepreneurs with small employee bases would have no way of being there for every customer and anticipating each person's needs in real time.
DALLAS - At a vast greenhouse in the central Danish city of Odense, a squad of robots move thin plastic pots of herbs for shipping without even putting a dent in them. For moviegoers used to seeing humanoid machines in action, that might not seem special -- but in truth, it is a remarkable feat. Robots until recently have been limited to precise, preprogrammed and repetitive heavy-duty jobs like automotive manufacturing. Yet at the Rosborg Food greenhouse, the OnRobot devices adjust on the fly. One pot might be slightly out of position.
Artificial Intelligence and Machine Learning, fondly known as AI & ML respectively, are the hottest buzzwords in the Software Industry today. The Testing community, Service-organisations, and Testing Product / Tools companies have also leaped on this bandwagon. While some interesting work is happening in the Software Testing space, there does seem to be a lot of hype as well. It is unfortunately not very easy to figure out the core interesting work / research / solutions from the fluff around. See my blog post - "ODSC - Data Science, AI, ML - Hype, or Reality?" as a reference.