Around the same time, Toyota said it would put an evolution of the Concept-i to work as an escort vehicle at the 2020 Tokyo Olympics. The new LQ concept is that evolution, coming to the Tokyo Motor Show later this month. The Concept-i housed an AI assistant called Yui, the software enlivened with Disney's 12 Principles of Animation that code behaviors to make fabricated things seem real. Toyota's assertion when debuting the Concept-i was, "We don't want to make a cold, technical, dry, soulless machine." The LQ expands the methods of interaction between Yui and occupants, the aim being to personalize the driving experience and "build an emotional bond between car and driver," the development philosophy being, "Learn, Grow, Love."

Download this complimentary webinar to learn how to use Forrester's automation framework to guide decisioning, rationalize your automation portfolio, and prepare for the future of work. In 1983, Lisanne Bainbridge (a researcher at the University of Reading in the UK) wrote the following prescient words in her widely cited paper "Ironies of Automation": "By taking away the easy parts of [the] task, automation can make the difficult parts of the human operator's task more difficult." In other words, automate all the easy things, and what's left for people to do? This maxim has never been truer. When systems become too automated, their behavior in key respects becomes harder and harder to predict and set them straight when they go wrong requires deeper and deeper expertise.

British healthcare workers are hostile to their robotic co-workers, committing "minor acts of sabotage" such as standing in their way, according to a recent study by De Montfort University, which chided the humans for "not playing along with" their automated peers. The researchers contrasted the "problematic" British attitude with that of Norwegian workers, who embraced their silicon colleagues, even giving them friendly nicknames. Some 30 percent of UK jobs will be lost to automation within 15 years if current trends continue apace, according to PricewaterhouseCoopers. The percentage is even greater in the US (38 percent) as well as Germany and France (37 percent), but falls to 25 percent in Scandinavian countries like Norway and Finland. Perhaps this explains the difference in workplace interactions between the British and the Norwegians - the latter aren't as worried about losing their jobs to an electronic interloper.

Spending on IT across the UAE has been witnessing a steady increase, driven by businesses looking to increase efficiency, improve performance, and reduce costs, by investing in artificial intelligence systems, experts said. "We are definitely seeing a significant increase in AI adoption in the UAE," Ali Hyder, group chief executive officer of Focus Softnet, told Khaleej Times. "AI is changing the way we use technology and conduct business, communicate with our customers/vendors and analyse our data. It has the potential to bring change on a wide scale to organisations, where customer and operational data is primary to the business. AI presents organisations with tremendous opportunities to augment human capabilities across industries and this technology is transforming systems through creativity and agility."

Humans can spot patterns of activity, but we can't see through walls. Advanced neural networks that use radio wave imaging to see have the exact opposite problem. Now, a new technique developed by researchers at Massachusetts Institute of Technology is helping the neural networks see the world a little more clearly. The new method uses radio waves to train a neural network to spot patterns of activity that can't be viewed in visible light, according to a paper, titled "Making the Invisible Visible: Action Recognition Through Walls and Occlusions," recently posted to the preprint server arXiv. The researchers say the tech is especially helpful in difficult conditions, such as when someone is obscured in darkness or fog or around a corner.

An artificial intelligence system has outperformed pathologists in differentiating atypia from ductal carcinoma in situ--considered to be the greatest challenge in breast cancer diagnosis. In a diagnostic study involving 240 breast biopsy images, the performance of the AI system was compared with independent interpretations from 87 practicing U.S. pathologists. "In the classification tasks of atypia and DCIS versus benign and DCIS versus atypia, the associated sensitivities are higher than the sensitivity of the practicing pathologists who independently interpreted the same specimens," according to the study's authors. Results of the study, supported by the National Cancer Institute of the National Institutes of Health, were published last week in JAMA Network Open. "Medical images of breast biopsies contain a great deal of complex data, and interpreting them can be very subjective," says senior author Joann Elmore, professor of medicine at UCLA's David Geffen School of Medicine and a researcher at the UCLA Jonsson Comprehensive Cancer Center.

The evolution of artificial intelligence (AI) is one of the most important trends to watch for tech investors. More companies are jumping into the space every day, and while stock pickers still have to exercise caution and shouldn't embrace a business just because it touts an AI connection, the players that cement leading roles in this computing shift could enjoy forefront positions in the overall technology space for decades to come. Pure sales and earnings contributions aren't always front and center in earnings reports, but AI is already a big part of the growth story at many top technology companies. Investors looking to get a jump on big news in the artificial intelligence space this month might want to pay attention to Microsoft (NASDAQ: MSFT), Xilinx (NASDAQ: XLNX), and Amazon (NASDAQ: AMZN) -- three AI leaders that are expected to report earnings before October draws to a close. Microsoft has been one of the market's biggest large-cap winners in recent years, climbing roughly 200% over the last half-decade and quadrupling the S&P 500 index's rise over the stretch.

Bengaluru-based early-stage venture capital firm Inventus Capital Partners has announced the final close of its third fund at INR 369 Cr ($51.98 Mn). Samir Kumar of Inventus Capital Partners told ET that the third fund will make about 15 investments in total. The investment has come in from a mix of institutional investors, such as Small Industries Development Bank of India, family offices and technology entrepreneurs, including founders from its portfolio companies such as Phanindra Sama of redBus and Ramesh Emani of Insta Health. Inventus Capital was set up in 2007 and has been actively involved with investing in startups both in Silicon Valley and in India. It has invested in 65 US-based companies and 26 Indian companies.

This is a quick transcript of the interview of Peter Norvig by Lex Fridman. I find this interview so interesting and revealing, that I decided to take on the task of making a transcript of the interview published in YouTube. Lex Friedman: The following is a conversation with Peter Norvig. A Modern Approach", and educated and inspired a whole generation of researchers, including myself, to get into the field of Artificial Intelligence. This is the Artificial Intelligence podcast. Lex Fridman: Most researchers in the AI community, including myself, own all three editions, red green and blue, of the "Artificial intelligence, a modern approach", the field defining textbook. As many people are aware that you wrote with Stuart Russell, how is the book changed, and how have you changed in relation to it from the first edition to the second, to the third, and now fourth edition as you work on it? Peter Norvig: Yeah so it's been a lot of years, a lot of changes. One of the things changing from the first, to maybe the second, or third, was just the rise of computing power, right? So, I think in the First Edition we said: "here's predicate logic but that only goes so far because pretty soon you have millions of short little medical expressions and they can possibly fit in memory, so we're gonna use first-order logic that's more concise." And then we quickly realized: "Oh, predicate logic is pretty nice because there are really fast Sat solvers, and other things, and look there's only millions of expressions and that fits easily into memory, or maybe even billions fit into memory now.

Change Healthcare, announced that its artificial intelligence (AI) technology has been added to the CareSelect Imaging decision support solution. The new AI capabilities will help healthcare providers using leading electronic health record (EHR) systems enhance workflow efficiency, improve patient safety, provide higher-value care, and meet pending regulatory requirements. CareSelect Imaging now uses Change Healthcare AI in EHR workflow to help physicians streamline imaging orders. In addition, it helps providers comply with new Protecting Access to Medicare Act (PAMA) requirements governing advanced imaging ordered under Medicare Part B. "Bringing Change Healthcare AI to CareSelect Imaging helps providers ensure they're delivering the highest quality, most appropriate care, while reducing their administrative and regulatory burdens through advanced automation," said Michael Mardini, CEO of National Decision Support Company, a Change Healthcare Company. "This is a perfect example of how strategic applications of AI will continue to improve healthcare processes and benefit all stakeholders."