Predicting the behavior of crowds in complex environments is a key requirement in a multitude of application areas, including crowd and disaster management, architectural design, and urban planning. Given a crowd's immediate state, current approaches simulate crowd movement to arrive at a future state. However, most applications require the ability to predict hundreds of possible simulation outcomes (e.g., under different environment and crowd situations) at real-time rates, for which these approaches are prohibitively expensive. In this paper, we propose an approach to instantly predict the long-term flow of crowds in arbitrarily large, realistic environments. Central to our approach is a novel CAGE representation consisting of Capacity, Agent, Goal, and Environment-oriented information, which efficiently encodes and decodes crowd scenarios into compact, fixed-size representations that are environmentally lossless. We present a framework to facilitate the accurate and efficient prediction of crowd flow in never-before-seen crowd scenarios. We conduct a series of experiments to evaluate the efficacy of our approach and showcase positive results.

We propose a new form of human-machine interaction. It is a pictorial game consisting of interactive rounds of creation between artists and a machine. They repetitively paint one after the other. At its rounds, the computer partially completes the drawing using machine learning algorithms, and projects its additions directly on the canvas, which the artists are free to insert or modify. Alongside fostering creativity, the process is designed to question the growing interaction between humans and machines.

Despite applying multiple filters and typing in carefully crafted keywords, you still can't find what you're looking for online. Overwhelmed by choice, you scroll the page for the fourth time trying to choose one of the 15 shades of white paint. Do you want Paper White or Chalk White? Maybe you want beige instead. You start to wish you never undertook this do-it-yourself (DIY) project; surely, shopping should not be this hard. Ensuring a smooth and stress-free experience is critical in retaining and attracting new customers.

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.