Could machines that think someday pose an existential threat to humanity? Some big names in science and tech seem to think so--Stephen Hawking, for one--and they've issued grave warnings about the looming threat of artificial intelligence.

At Google's inaugural TensorFlow Dev Summit in Mountain View, California, today, Google announced the release of version 1.0 of its TensorFlow open source framework for deep learning, a trendy type of artificial intelligence. Google says the release is now production-ready by way of its application programing interface (API). But there are also new tools that will be part of the framework, which includes artificial neural networks that can be trained on data and can then make inferences about new data. Now there are more traditional machine learning tools, including K-means and support vector machines (SVMs), TensorFlow's engineering director, Rajat Monga, said at the conference. And there's an integration with the Python-based Keras library, which was originally meant to ease the use of the Theano deep learning framework.

Aircraft maker Airbus is turning to smart industrial drones, data analytics and machine learning to make aircraft inspections easier and faster. One day while working on a shiny new Airbus A350 aircraft, Ronie Gnecco figured it was time to build a better relationship between drones and passenger airplanes. His bold idea to use flying robots for aircraft safety inspections worked so well it has -- among other projects -- it inspired aircraft manufacturer Airbus to move deeper into the industrial drone revolution. Within a couple of years, the company's intelligent unmanned aerial vehicles (UAV) systems could be used for safety inspections at airports around the world, making planes safer with more on-time flight departures. To make that happen, Gnecco said it will require pioneering efforts from technology experts, regulators and airport authorities from around the world.

Ethan Bloch was in junior high school in Baltimore during the dot-com boom. For his bar mitzvah -- the ceremony that welcomes 13-year-old Jewish boys into adulthood -- Bloch received $7,000 in cash. It was 1998 and, like so many amateur traders at the time, he plunged his wealth into the stock market, mostly software and telecommunication names like Lucent and Nortel. He quickly tripled his money. By age 15, it was all gone.

David Ulevitch, head of Cisco's security business, has a problem with the hype around artificial intelligence, the field that encompasses the booming computer science discipline of machine learning. Suddenly, everyone in the tech world is buzzing about the subject. Marketers, especially ones in the cybersecurity industry, have started plugging it as something of a panacea; there's no network AI can't protect, if the salespeople are to be believed. "The real threat in security is not whether we have things that are too smart," Ulevitch told Fortune in advance of his Wednesday RSA security conference keynote, during which he planned to touch on the topic. Whenever someone starts dropping the latest buzzwords--algorithms, analytics, AI--Ulevitch tunes them out, he said.

Computer vision is concerned with the automatic extraction, analysis and understanding of useful information from a single image or a sequence of images. Making an approach to pursue the most advanced technology takes a lot of innovation and it is exactly what Mantra Labs has been doing. If you are keen to solve real world problem using AI, Drop us a line hello@mantra.ai

This article is by Featured Blogger Daniel Newman from his LinkedIn page. Decades ago, artificial intelligence was a distant concept meant for future generations. We're seeing advancements every day that will make our lives easier and more efficient. And as a way to make big data useful, AI might be a game changer. Data collection has always been an important facet of business, but never before have we been able to access it in such a responsive and useful manner.

The development of Artificial Intelligence (AI) has been remarkable and, in recent years, has experienced several breakthroughs. Will 2017 continue this trend? Commercial enterprises are procuring and developing systems that use AI to aid in their corporate goals, enhancing their performance through the use of autonomy. By exploiting advancements in big data analytics, processing power and clearer computer systems and networks, companies can use automation and AI to augment their current work processes and generate methods of long-term value creation. The stage is set, however, for AI to rise higher than ever before as large players including Apple, Facebook, Google and Microsoft all open-source or share their latest research in AI, to advance collective advancement.

Ravi is a Senior Managing Consultant at IBM (Analytics Platform, North American Lab Services). Ravi is a Distinguished IT Specialist (Open Group certified) with more than 23 years of I/T experience. He has a Masters degree in Business Administration (MBA) from University of Nebraska, Lincoln. He had contributed to 7 other redbooks in the areas of Database, Analytics Accelerator and Information Management tools. IBM SPSS Modeler is a powerful analytic tool that supports all phases of data analytics process, including data preparation, model building, deployment, and model maintenance.

When Google's AlphaGo algorithm beat the Go world champion in 2016, it became apparent that machine learning had arrived and would significantly shape the future. As a new breed of software that is able to learn without being explicitly programmed, machine learning will be able to access and analyze structured as well as unstructured data at a level of complexity that human minds find difficult to grasp. Looking at the quality of today's voice recognition and image recognition software, as well as at the capabilities of self-driving cars, we can already see how self-learning algorithms may influence our lives. Computer scientists have been pursuing artificial intelligence since the 1950s. Now, thanks to recent advances in technology, including Big Data processing, increased computing power, and better algorithms, computers have begun to compete with, or even surpass, abilities once considered exclusive to humans.