With China making rapid progress in artificial intelligence (AI)-based research, it is imperative that India view AI as a critical element of its national security strategy, recommends an August 2016 report titled India and the Artificial Intelligence Revolution. Thanks to the increasingly digital economy, fuelled by improving education and globalization, the Indian consumer is unknowingly the country's biggest beneficiary of recent advances in AI, notes the report. From utilizing various applications powered by AI to using a range of online services such as Amazon Marketplace and Netflix that learn from consumers' online behaviour to make intelligent product and service recommendations, consumers are readily engaged with the proliferation of AI in India, whether they appreciate it or not. Indian academics, public researchers, labs, and entrepreneurs face a different challenge than the corporations that dominate the space--the infrastructure necessary for an AI revolution in India has been neglected by policymakers. While lack of physical infrastructure is certainly a major impediment, India's AI development also suffers from the paucity of the necessary cultural infrastructure, which is key for recent advances from lab to marketplace in AI.

Businesses expect AI to boost revenues by 39 percent in 2020. Will artificial intelligence deliver on its bold promise for businesses? Artificial intelligence is already profitable for many companies, and they expect more profits from AI in the years ahead, according to a recent report from Infosys. The report, titled "Amplifying Human Potential: Towards Purposeful Artificial Intelligence" polled 1,600 senior decision makers from large businesses all over the world. The companies surveyed invested an average of $6.7 million in AI in the past 12 months and have been actively using AI for an average of 24 months.

It seems as if you can't pull up a website on data these days without running into the term Artificial Intelligence. And with good reason: Markets and Markets has it pegged as reaching $16 billion by 2022. Wander around the Web and you can hit on stories about everything from the top AI stocks to buy to what universities are offering MBA courses on managing Artificial Intelligence applications and algorithms. There's more action afoot to help developers deal with the surging AI trend, too. Amazon, for example, recently announced new self-service tools to help the development community more easily build Artificial Intelligence capabilities into apps, and Google has a new AI unit that has democratizing AI as part of its mission. Artificial Intelligence is new terrain for many developers, and getting on board in some way, shape or form must be appealing when they hear about the latest moves in the space, including how they're targeting expert talent in the area in a significant way.

For most people, the sound of wedding bells evokes happiness. Whether you're remembering the time you tied the knot with your significant other or finally jumping the broom, weddings are always a joyful celebration. But if you've already gone through the process, or are going through it now, you know just how untrue that emotion is when you're in the planning process. While I haven't had the pleasure of marrying my fiancé yet, I have had the pleasure of being a Maid of Honor quite a few times and am currently in the planning phases with my sister for her wedding – so I speak from experience when I say it's definitely not all sunshine and rainbows. Working with a budget, getting guest lists, picking venues and vendors is no easy task.

The Trump administration's controversial attempt to declare its recent presidential inauguration as having "the largest audience to witness an inauguration, period," has inadvertently highlighted the fact that counting crowds remains a painstaking and inexact science. But the rise of artificial intelligence could soon spare crowd scientists the task of manually counting heads. An early glimpse of how artificial intelligence (AI) could help count crowds appeared in 2013. University of Central Florida researchers showed how computer software based on machine learning can swiftly provide automated headcount estimates for crowds numbering in the hundreds of thousands. Such AI tools still have room for improvement in terms of achieving accurate headcounts based on images.

Many retailers are scared of machine learning. This doesn't come from an unreasonable place. Marketers are afraid to trust technology to assist in making crucial marketing decisions as well. But while machine learning is certainly a game-changer, it doesn't fundamentally alter how businesses communicate with customers. It only better informs marketing decisions to empower smarter and more effective efforts.

While AI initiatives such as IBM Watson, chatbots and digital assistants have garnered much attention over the past year, the current applications only scratch the surface of the technology's potential. For companies, AI will be used to predict customer needs in near real-time, helping them retain customers. The importance of AI to customer interactions is reflected in Forrester's findings, such as that 37% of companies plan to implement intelligent assistants in the next 12 months, and 35% have their sights on cognitive product launches for customers. Some of the other ways AI will be used going forward include leveraging speech recognition for customer interactions, machine learning for making predictions, image recognition in combination with machine learning, robotics and self-driving cars. Already this year, there are signs that robots in stores could revolutionize the customer experience. However, because AI comes with a number of ethical, political and social issues attached, it will be important for companies to develop a plan and have foundational elements in place as they test and learn, per Forrester.

The Internet of Things (IoT) promises to simplify and streamline our lives by automating routine tasks that distract us from our goals. This promise is based on the ubiquitous deployment of smart, connected devices that link everything from industrial control systems to automobiles to refrigerators. Unfortunately, comparatively few of the devices currently deployed have been developed with an eye toward security, and as the DDoS attacks of late October 2016 have demonstrated, this oversight can have devastating, if not catastrophic results. In his session at 19th @ThingsExpo, Richard Blech, Chief Executive Officer at Secure Channels, explored the promise and the pitfalls inherent to IoT and offered a novel way of incorporating an effective security paradigm in which IoT "watchmen" monitor and maintain order within the IoT. Speaker Bio Richard Blech is Chief Executive Officer at Secure Channels Inc.

SAN FRANCISCO--(BUSINESS WIRE)--Kinetica, provider of the fastest, in-memory database accelerated by GPUs, today announced the availability of in-database analytics via user-defined functions (UDFs). This industry-first capability makes the parallel processing power of the GPU accessible to custom analytics functions deployed within Kinetica. This opens the opportunity for machine learning/artificial intelligence libraries such as TensorFlow, BIDMach, Caffe, and Torch to run in-database alongside, and converged with, BI workloads. Kinetica also introduced its extensible and flexible'Reveal' visualization framework for interactive, real-time data exploration. Kinetica's advanced in-database analytics make it possible for organizations to affordably converge Artificial Intelligence, Business Intelligence, Machine Learning, natural language processing, and other data analytics into one powerful platform.

The latest battle between man and machine is being played out on the poker tables of a Pennsylvania casino, and so far humanity is losing. An artificial intelligence computer program called Liberatus has accumulated winnings of almost $800,000 against a team of professional poker players at the Brain Vs. Liberatus, developed by Carnegie Mellon School of Computer Science, is aiming to be the first computer program to win a professional poker tournament--a game considered by many AI researchers to be one of the hardest for computers to beat humans at. Artificial intelligence advances in recent years have seen computers master and eventually outperform the best human players at games including Chess and the game show Jeopardy!. In 2016, researchers at Google's DeepMind developed a system that was able to beat champion Go player Lee Sedol--a significant step for artificial intelligence.