Recent surveys, studies, forecasts and other quantitative assessments of the progress of AI, highlighted among other findings, disagreements about the impact of chatbots: Do purchase rates go down when people find out they are interacting with a chatbot? Or do chatbots actually increase customer satisfaction and loyalty? And are chatbots already successful in replacing human workers?
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Asked what is the biggest misconception about AI, Yoshua Bengio answered without hesitation “AI is not magic.” Winner of the 2018 Turing Award (with the other “fathers of the deep learning revolution,” Geoffrey Hinton and Yann LeCun), Bengio spoke at the EmTech MIT event about the “amazing progress in AI” while stressing the importance of understanding its current limitations and recognizing that “we are still very far from human-level AI in many ways.”
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Chinese AI startups received $6.1 billion in VC funding over the past four years – almost 70% more than their U.S. counterparts, which raised $3.6 billion during the same period.
The price of computation today is roughly one hundred-millionth what it was in the 1970s, when the first microprocessors became commercially available (see chart). According to figures collected by John McCallum, a computer scientist, a megabyte of data storage in 1956 would have cost around $9,200 ($85,000 in today’s prices). It now costs just $0.00002.
59% of US adults say it is acceptable for law enforcement to use facial recognition to assess security threats in public spaces; only 15% say it is acceptable for advertisers to use facial recognition to see how people respond to public ad displays; 13% of US adults have not heard about facial recognition and 25% say they heard a lot.
In 2002, 56 percent of the jobs studied required low amounts of digital skills. Nearly 40 percent of jobs required medium digital skills and just 5 percent required high digital skills.
A lot has changed. By 2016, the share of jobs requiring high digital skills had jumped to 23 percent. The share requiring medium digital skills rose to 48 percent. And in a huge shift, the share of jobs requiring low digital skills fell from 56 to 30 percent.
Cloud office is the only technology to enter the Plateau of Productivity in the 2019 Gartner Hype Cycle for Digital Government Technology, according to Gartner, Inc. The Plateau of Productivity highlights technologies that are hitting mainstream adoption within organizations….
Government agencies are moving rapidly to adopt cloud-office platforms because of the desire to consolidate collaboration environments, reduce costs, redeploy IT staff, drive simplicity and provide more functionality to users more quickly. Cloud office makes the introduction of capabilities including everyday artificial intelligence (AI), mobile collaboration, collaborative content authoring and workstream collaboration part of the mainstream.
The Hype Cycle for Emerging Technologies is unique among most Gartner Hype Cycles because it garners insights from more than 2,000 technologies into a succinct set of 29 emerging technologies and trends. This Hype Cycle specifically focuses on the set of technologies that show promise in delivering a high degree of competitive advantage over the next five to 10 years…
This year, Gartner refocused the Hype Cycle for Emerging Technologies to shift toward introducing new technologies that have not been previously highlighted in past iterations of this Hype Cycle. While this necessitates retiring most of the technologies that were highlighted in the 2018 version, it does not mean that those technologies have ceased to be important.
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The recent surveys, studies, forecasts and other quantitative assessments of the health and progress of AI highlighted the role of AI in cybersecurity defense and in scoring standardized tests, the relationships between data migrating to the cloud and data modernization, lax security standards for IoT devices, and that the U.S. still leads the global race for AI domination but that China is making more rapid progress.
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“AI will open a new chapter so that humans will know themselves better. Most of the projections about AI are wrong … people who are street-smart about AI are not scared by it”—Jack Ma
“Humans may become too slow. A millisecond is an eternity to a computer today. Computers are already smarter than human beings in many aspects [adding that while humans write AI software today, in the end the machine will do this itself]—Elon Musk
