Managing supply chain is one of the biggest technological opportunities in the world. The potential to disrupt inefficiencies using innovations has led several startups, especially in India, to rise to the challenge. GoBOLT, a Gurugram-based tech startup, was founded in late 2015, to take on the mammoth and unorganised logistics industry in India. Founders Sumit Sharma, Parag Aggarwal, Naitik Baghlaall come from corporate backgrounds, having worked in companies like Ernst & Young, J M Financial, GSK, and Tata Motors. The idea for GoBOLT was born during Sumit's travels, while travelling to developed economies like the US and Canada, where asset utilisation in the trucking industry is very high.

Accenture is spending $1 billion in re-training training its employees every year as the company sees its customers are increasingly demanding newer technology-led services. The tech services major said it has trained nearly 80% of its technology services employees in technologies such as data analytics, artificial intelligence, machine learning, cloud computing - broadly referred as digital technologies. Digital currently contributes more than 60% of Accenture's $43.2 billion revenue. Nearly 55% of Accenture's employees are in technology services roles globally. "We had (nearly) 200000 people across 180 countries and we pitched that as our strength. One of the clients once asked me it is your strength or weakness, do you really need so many people in future. It was a big question at that point of time we took decision to rotate to new. So our investment in talent is close to a billion dollar globally and nearly 80% of tech services talent are trained in new," said Bhaskar Ghosh, group chief executive, Accenture Technology Services.

Global Artificial Intelligence (AI) in Automotive Market has valued 566.80 Mn in 2016 and is estimated to reach US$ 10,600.3 Global Artificial Intelligence (AI) in Automotive Market is segmented by technology, offering, process, application, and geography. By technology, Global Artificial Intelligence (AI) in the automotive market is divided into Computer Vision, Machine Learning, Context Awareness, natural language processing. Based on the offering, Artificial Intelligence (AI) in Automotive Market is categorized hardware and software. By process, the market is fragmented into Data Mining, Signal Recognition, and Image Recognition.

"We are probably one of the last generations of homo sapiens." Those were the opening words of acclaimed historian and best-selling author Professor Yuval Harari, who spoke at the World Economic Forum Annual Meeting in Davos, Switzerland, where politicians, thought leaders and executives from the world's leading companies congregate to discuss solutions to global challenges. What comes after us, Harari said, are entities that are more different from us than we were from our predecessors, the Neanderthals. However, those species will not be the outcome of the organic evolution of human genes, Harari explained, but the outcome of humans learning to engineer bodies, brains and minds. "This will be the main product of the economy of the 21st century." But how will those species emerge and what will they look like?

Tank warfare isn't traditionally easy to predict. In July 1943, for instance, German military planners believed that their advance on the Russian city of Kursk would be over in ten days. In fact, that attempt lasted nearly two months and ultimately failed. Even the 2003 Battle of Baghdad, in which U.S. forces had air superiority, took a week. The U.S. Army has launched a new effort, dubbed Project Quarterback, to accelerate tank warfare by synchronizing battlefield data with the aid of artificial Intelligence.

We live in a connected world and generate a vast amount of connected data. Social networks, financial transaction systems, biological networks, transportation systems and a telecommunication nexus are all examples. The paper citation network displayed in Figure 1 is another example of connected data. Representing connected data is possible using a graph data structure regularly used in Computer Science. In this article, we will provide an introduction to the assorted types of connected data, what they represent, and the challenges we can solve.

Armed violence is on the rise and we don't know how to stop it1. Since 2011, conflicts worldwide have killed up to 100,000 people a year, three-quarters of whom were in Afghanistan, Iraq and Syria. The rate of major wars has decreased over the past few decades. But the number of civil conflicts has doubled since the 1960s, and terrorist attacks have become more frequent in the past ten years. The nature of conflict is changing.

Machine learning and AI may be deployed on such grand tasks as finding exoplanets and creating photorealistic people, but the same techniques also have some surprising applications in academia: DeepMind has created an AI system that helps scholars understand and recreate fragmentary ancient Greek texts on broken stone tablets. These clay, stone or metal tablets, inscribed as much as 2,700 years ago, are invaluable primary sources for history, literature and anthropology. They're covered in letters, naturally, but often the millennia have not been kind and there are not just cracks and chips but entire missing pieces that may comprise many symbols. Such gaps, or lacunae, are sometimes easy to complete: If I wrote "the sp_der caught the fl_," anyone can tell you that it's actually "the spider caught the fly." But what if it were missing many more letters, and in a dead language, to boot?

As artificial intelligence is being used to solve problems in healthcare, agriculture, weather prediction and more, scientists and engineers are investigating how AI could be used to fight climate change. AI algorithms could indeed be used to build better climate models and determine more efficient methods of reducing CO2 emissions, but AI itself often requires substantial computing power and therefore consumes a lot of energy. Is it possible to reduce the amount of energy consumed by AI and improve its effectiveness when it comes to fighting climate change? Virginia Dignum, an ethical artificial intelligence professor at the Umeå University in Sweden, was recently interviewed by Horizon Magazine. Dignum explained that AI can have a large environmental footprint that can go unexamined.

About a year ago, top deepfake artist Hao Li came to a disturbing realization: Deepfakes, i.e. the technique of human-image synthesis based on artificial intelligence (AI) to create fake content, is rapidly evolving. In fact, Li believes that in as soon as six months, deepfake videos will be completely undetectable. And that's spurring security and privacy concerns as the AI behind the technology becomes commercialized – and gets in the hands of malicious actors. Li, for his part, has seen the positives of the technology as a pioneering computer graphics and vision researcher, particularly for entertainment. He has worked his magic on various high-profile deepfake applications – from leading the charge in putting Paul Walker into Furious 7 after the actor died before the film finished production, to creating the facial-animation technology that Apple now uses in its Animoji feature in the iPhone X. But now, "I believe it will soon be a point where it isn't possible to detect if videos are fake or not," Li told Threatpost.