Former Infosys CEO Vishal Sikka, who has announced a new AI startup with USD 50 million fund, believes India has the potential to become a world leader in artificial intelligence but the key to this is integrating AI into the country's education system in a massive way. India is at "an inflection point" when it comes to AI or artificial intelligence, Sikka said. Over the next 20-25 years, AI is going to be "a very, very big disruptor" for the Indian society because what one is seeing now in terms of automation and job losses because of automation is just the beginning, said Sikka, who announced his startup Vianai Systems last week. "But on the other hand, if we are able to bring AI education, the ability to build AI systems to India at a very large scale, and I'm talking about like billion plus people, then India can really leap frog and become the world's leader in artificial intelligence, in AI skill and AI talent," Sikka told PTI in an exclusive interview. Doing that requires working on multiple dimensions in parallel, he said.

In the next 10 years, as robots and other tech bring about the "greatest transfer from labour to capital" the industry has witnessed, per a report by Wells Fargo analysts, U.S. banks will slash over 200,000 jobs. Veteran Wall Street Analyst Mike Mayo noted that cuts of such magnitude would comprise over 10 percent of total bank jobs, and pave the way for a "golden age of banking efficiency," the Financial Times reported. Mayo said, according to the outlet, "It's been a rocky 25-year marriage for banking and technology, but it's finally getting on course." Wells Fargo's team of analysts in financial services and technology examined technology's impact throughout the banking industry in the U.S. The 225-page report discussed how artificial intelligence could cut costs for mortgage processing by 10 percent to 20 percent. Cloud computing, on the other hand, could bring in significant savings, while Big Data would enable "more surgical marketing."

SAN ANTONIO--In the warzones of the future, medics touching down amid heavy battlefield casualties will know who to treat first, how to approach every injury, and even who is most likely to live or die -- all before looking at a single wounded soldier. That's the vision of Col. (and Dr.) Jerome Buller, who leads the U.S. Army Institute of Surgical Research. Buller says biometric data gleaned from soldier-borne sensors, combined with in-depth medical and training data and augmented reality lenses, will help medics in combat evaluate the battlefield and everyone in it from a safe distance. They will make their most important decisions before even seeing their patients. "Imagine that [the hypothetical future] medic is able to scan the battlefield and instead of seeing rubble, he's seeing red or green dots, or amber dots, and he knows where to apply resources or not," Buller said during the Defense One and NextGov Genius Machines event here on Wednesday.

DARPA wants to break a network speed bottleneck caused by network interface cards (NICs) that aren't cut out to support tomorrow's demands for artificial intelligence. To achieve its goal, the Department of Defense agency is launching the Fast Network Interface Cards (FastNICs) program. The FastNIC isn't a technology just yet, but DARPA's FastNICs program is seeking engineering talent to help achieve its ambition to boost the performance of the network stack on servers by 100 times. SEE: Sensor'd enterprise: IoT, ML, and big data (ZDNet special report) Download the report as a PDF (TechRepublic) As DARPA explains, networking performance has tracked the same path as computing performance explained by Moore's Law. But NICs, the hardware that connects the computer to an Ethernet network, have not kept pace and, with a few other factors like memory and software design, application throughput is too slow for the future of AI and distributed computing.

A famed Russian technical university is helping to lead the government's push for public-private efforts to develop AI technologies and applications -- including a joint project with China's Huawei -- and to stop top talent from flowing to the West. In December 2017, three months after Vladimir Putin predicted that artificial intelligence could produce "global domination," the Russian government picked the Moscow Institute of Physics and Technologies to host a new Center for Artificial Intelligence. Today, this center aims to foster partnerships among the nation's leading state-run and private companies and universities. This year's events of note include: The Amazon prize, in particular, shows an international recognition of Russian talent, as well as an acknowledgement by one of the world's leading AI players that it needs international input to develop products to be marketed globally. Be the first to receive updates.

In 2018, artificial intelligence took on new tasks, with these smarty-pants algorithms acing everything from disease diagnosis to crater counting. In April, the U.S. Food and Drug Administration permitted marketing of the first artificial intelligence that diagnoses health problems at primary care clinics without specialist supervision (SN: 3/31/18, p. 15). The program, which inspects eye images for signs of diabetes-related vision loss, could be a boon for people in remote or low-resource areas where ophthalmologists are scarce. Other eye-inspecting AI programs are learning to recognize everything from age-related vision loss to heart problems. One artificial intelligence is a celestial cartographer after Galileo's own heart.

"The JAIC is working to bring critical AI detection technology to the first responders who bravely battle wildfires. Increased use of AI will reduce response timelines, increase situational awareness, and save more American lives." Last year's California wildfire season was the deadliest and most destructive in United States history. More than 8,500 fires burned across nearly 1.9 million acres in the state of California and resulted in more than $16.5 billion in damage. Cumulatively, the wildfires were the costliest natural disaster of 2018, as well as one of the deadliest.

In 2010, the small community of specialists who pay attention to US road safety statistics picked up the first signs of a troubling trend: more and more pedestrians were being killed on American roads. That year, 4,302 American pedestrians died, an increase of almost 5% from 2009. The tally has increased almost every year since, with particularly sharp spikes in 2015 and 2016. Last year, 41% more US pedestrians were killed than in 2008. During this same period, overall non-pedestrian road fatalities moved in the opposite direction, decreasing by more than 7%. For drivers, roads are as safe as they have ever been; for people on foot, roads keep getting deadlier. Through the 90s and 00s, the pedestrian death count had declined almost every year. No one would have confused the US for a walkers' paradise – at least part of the reason fewer pedestrians died in this period was that people were driving more and walking less, which meant that there were fewer opportunities to be struck. But at least the death toll was shrinking. The fact that, globally, pedestrian fatalities were much more common in poorer countries made it possible to view pedestrian death as part of an unfortunate, but temporary, stage of development: growing pains on the road to modernity, destined to decrease eventually as a matter of course. The US road death statistics of the last decade have blasted a hole in that theory.

Artificial intelligence is infiltrating every industry, allowing vehicles to navigate without drivers, assisting doctors with medical diagnoses, and mimicking the way humans speak. But for all the authentic and exciting ways it's transforming the tasks computers can perform, there's a lot of hype, too. As Jeremy Achin, CEO of newly minted unicorn DataRobot, puts it: "Everyone knows you have to have machine learning in your story or you're not sexy." The inherently broad term gets bandied about so often that it can start to feel meaningless and gets trotted out by companies to gussy up even simple data analysis. To help cut through the noise, Forbes and data partner Meritech Capital put together a list of private, U.S.-based companies that are wielding some subset of artificial intelligence in a meaningful way and demonstrating real business potential from doing so. One makes robots that can whir around shoppers to help workers restock shelves. Another scans recruiting pitches for unconscious bias. A third analyzes massive data sets to make street-by-street weather predictions. To be included on the list, companies needed to show that techniques like machine learning (where systems learn from data to improve on tasks), natural language processing (which enables programs to "understand" written or spoken language), or computer vision (which relates to how machines "see") are a core part of their business model and future success. Find all the details on our methodology here. The honorees span categories like human resources, security, insurance, and finance, with healthcare, transportation, and infrastructure startups best represented on the list.