We are seemingly joined by Bollywood star Shah Rukh Khan (their brand ambassador) during our visit to the BigBasket Offices to interview Subramaniam Mani, their Analytics Head. He believes that the major difference between the software and AI waves is that although India was slow to adopt software service as compared to America, this time around with the AI wave, adoption will be much faster and only slightly behind the leading countries. "This is the second wave. The software wave was 30 years ago. Folks in India realized that they've been able to scale software and I think AI / ML is an extension of software development." While software was often taught through books and in classrooms exclusively, many of the latest artificial intelligence approaches are available to learn online – along with huge suites of open-source tools (from scikit-learn to TensorFlow and beyond). Going in, we knew that one of the key advantages for India would, in fact, be the very IT and ITeS sectors which will make it easy for Indian tech providers to transition into AI services, given that well-developed ecosystems have evolved over the past 25 years in cities like Bangalore and Hyderabad.

How do you get every single girl a full 12 years of quality education? That's the question at the heart of the Malala Fund, the organisation set up by Malala Yousafzai, the young Nobel Prize winner. And she wants to provide this education in parts of the world where it can't be taken for granted. Luckily, she has a powerful ally. In January, Apple revealed a tie-up with Malala Fund as part of the initial goal of getting 100,000 girls into education in Afghanistan, Pakistan, Lebanon, Turkey and Nigeria. But today it has been announced that the collaboration is expanding to Latin America. This expansion means grants will be offered to advocates in Brazil, who will join the Malala Fund's network of so-called Gulmakai Champions.

Can machines learn to reason abstractly? That's the subject of a new paper from Google subsidiary DeepMind titled "Measuring abstract reasoning in neural networks," which was presented at the International Conference on Machine Learning in Stockholm, Sweden this week. The researchers define abstract reasoning as the ability to detect patterns and solve problems on a conceptual level. In humans, they note, verbal, spatial, and mathematical reasoning can be measured empirically with tests that task subjects with teasing out the relationships between shape positions and line colors. "Unfortunately, even in the case of humans, such tests can be invalidated if subjects prepare too much, since test-specific heuristics can be learned that shortcut the need for generally applicable reasoning," the researchers explained. "This potential pitfall is even more acute in the case of neural networks, given their striking capacity for memorization."

Like most people, coffee is one of the most important rituals in my morning routine. There's something about the aroma and taste that kick-starts my ability to have a great day. So imagine my surprise when I found out that a favorite coffee shop was closed before I had to jump on an early-morning flight home. The employees were in the shop, but the gate locked out coffee aficionados, like me, that really needed that jolt of caffeine. Although this experience was understandably a letdown, it was also a source of inspiration.

To ensure the safe operation of a robot, it is crucial to know how the robot reacts under different conditions. But how do you know what disturbs a robot without actually damaging it? The machine learning method developed by scientists from the Institute of Science and Technology Austria (IST Austria) and the Max Planck Institute for Intelligent Systems uses observations made under safe conditions to make accurate predictions for all possible conditions determined by the same physical dynamics. The method is specially developed for real situations and offers simple, interpretable descriptions of the underlying physics. Traditionally, machine learning can only interpolate data - that is, make predictions about a situation that lies "between" other, known situations.

Russia and the United States are moving closer to opening their own centers for military-related research into artificial intelligence, as China did in the spring of last year. But the three governments have differing approaches. The U.S. Joint Artificial Intelligence Center aims to apply lessons from an Air Force pilot project to other military services, while the Chinese approach fuses civilian and military research and Russia's efforts are closely directed from the Kremlin. "What's interesting is the extent to which the Russian government and especially the Ministry of Defense is marshaling resources for the development of AI for its military," said Sam Bendett, an associate research analyst at CNA and a fellow in Russia studies at the American Foreign Policy Council. The new innovation technopolis, dubbed Era and slated to open in September with a bare-bones research staff, is planned to grow to a 50-acre city by 2020.

A recent survey by LexisNexis revealed that around 75% of lawyers recognise that the sector is changing faster than ever – yet only around one in five of those surveyed agree that their own firm needs to evolve. Do 80% of the survey respondents really work for firms who are already at the cutting edge of the profession? Or are they just complacent? And what are the implications for newly qualified lawyers embarking on their careers? Probably the biggest single driver of change in the industry is the increasing advance of technology. Everyone has read about the perceived threat of artificial intelligence (AI) and how it's set to take lawyers' jobs – and although Michael Skapinker of the Financial Times wrote recently that, like plumbers, lawyers are not yet approaching their'Uber' moment and remain largely a "disruption-free profession", other commentators take a slightly different view.

Google's Tilt Brush is one of the best VR painting apps for the Oculus Rift and HTC Vive. Since its release in 2016, artists have drawn magnificent ships, jaw-dropping mountain ranges and imaginative fight scenes in immersive 3D. Most of the app's brushes, however, mimic the real world with flat, ribbon-like strokes. For years, you've had to move around and paint, or'color in' every surface of a 3D object like a cube or cone. It was pretty time consuming.

Medical records of deceased patients are appearing on illicit market places on the dark web, cyber security researchers have discovered. Cyber criminals are advertising huge caches of personal data of up to 140 million patients, with their value exceeding that of stolen credit card details. The morbid trend follows an increasing amount of incidents of medical data breaches, as reported by Oren Koriat, an analyst at the security firm Cynerio. "Cynerio is still seeing continued growth in the number of incidents of patient medical record breaches from hacking and unauthorised access to healthcare systems," Mr Koriat wrote. "Recently, Cynerio has detected an interesting new wrinkle in the sale of stolen medical data on the dark web. Our research team found a post from a vendor on the dark web offering the medical records of the deceased."

Researchers are developing AI algorithms to detect breast cancer in mammograms.BSIP/UIG/Getty Dexter Hadley thinks that artificial intelligence (AI) could do a far better job at detecting breast cancer than doctors do -- if screening algorithms could be trained on millions of mammograms. The problem is getting access to such massive quantities of data. Because of privacy laws in many countries, sensitive medical information remains largely off-limits to researchers and technology companies. So Hadley, a physician and computational biologist at the University of California, San Francisco, is trying a radical solution. He and his colleagues are building a system that allows people to share their medical data with researchers easily and securely -- and retain control over it.