A robot has photographed a nearly intact ancient urn at the bottom of Japan's largest freshwater lake, according to Japanese national paper the Asahi Shimbun. Over the last century, a number of pottery pieces representing a huge range in timeline have been recovered from Lake Biwako, in central Japan. Archaeologists have no idea why. This urn is an example of Haji pottery, earthenware characterized by a rusty reddish-brown color that came from being baked. It measures roughly 12 to 16 inches tall, with the opening at the top measuring roughly 8 inches across, and it likely dates to the seventh or eighth century, according to the newspaper Asahi Shimbun.

MUMBAI NEW DELHI: Artificial intelligence (AI) is the buzz in the jobs bazaar as machine learning and the Internet of Things (IoT) increasingly influence business strategies and analytics. Human resource and search experts estimate a 50-60% higher demand for AI and robotics professionals in 2018 even as machines take over repetitive manual work. "Machines are taking over repetitive tasks. Robotics, AI, big data and analytics will be competencies that will be in great demand," said Shakun Khanna, senior director at Oracle for the Asia-Pacific region. Organisations are being pushed to become even more efficient as jobs turn predictable, said Rishabh Kaul, cofounder of recruitment startup Belong, which helps clients search for and hire AI professionals.

The apparel market is one of the largest in existence, accounting for 2 percent of the world's GDP, and valued at roughly $3 trillion. Every year, American households spend close to $2,000 on apparel alone, and over 211 million of these shoppers make their purchases digitally. In an industry this large, and this competitive, it's hard to keep customers engaged and active with your lines. With the increase of digitalization, retail markets are growing at an unprecedented pace. Newer markets are already beginning to dominate sales.

Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc... ... Nand Kishor is the Product Manager of House of Bots. After finishing his studies in computer science, he ideated & re-launched Real Estate Business Intelligence Tool, where he created one of the leading Business Intelligence Tool for property price analysis in 2012. He also writes, research and sharing knowledge about Artificial Intelligence (AI), Machine Learning (ML), Data Science, Big Data, Python Language etc...

India's small and medium-sized software firms, wanting to ride the wave of Artificial Intelligence (AI) and the Internet of Things (IOT), could soon find a new home in China's northeast corner. Nasscom, India's IT industry body, has negotiated a deal with local authorities in Dalian, a famous port city on the Liaodong Peninsula, to establish an IT corridor at the Bio-diverse Emerging Science Technology (BEST) City, on the outskirts of the metropolis. In turn, it would allow small Indian cyber companies to register with the new IT cluster. The Chinese companies, who are not a part of the top 100 biggies, are also likely to benefit. "The story is a little more complicated," said Gagan Sabharwal, senior director with Nasscom, referring to his disruptive bottom-up model, which could script the next chapter of India's software story. "We want to marry Indian strengths, especially of small companies, in software with China's heft in hardware."

Year 1956 when'Artificial Intelligence' was coined got its place in history and now Year 2018 will super pass that and will attain much more higher level respect for AI, and'as soon as it works, no one will call it AI anymore.' what this means is; the idea that once upon a time, technology like the photo library on our smartphone would have once been considered AI, now it's just the norm. AI would become just a computer inside the robot or another software or a brain siting out of human body. This year my first post of the year is written from New Delhi India. Time has come when Artificial Intelligence will be more closer to you (best of all times) and will be part of every day life for almost everything. Jokes like "Dont you have natural one as comment in the response to the answer "I do artificial intelligence will no longer make sense". We will see data driven machines to give humanized support and help. What can we expect from Artificial Intelligence in 2018. Its very easy and difficult to answer at the same time. Read on this post for artificial intelligence trends we'll see in 2018. We used to think artificial intelligence was a silly sci-fi concept but when you really look into it, it seems like its been slowly encroaching into most areas of everyday life! Year 2018 will be known as year of Artificial Intelligence and Intelligence Augmentation for sure (in my personal opinion). AI usage in FinTech will augment FinTech Intelligence's all time best. FinTech Intelligence will boost Payment Intelligence, Threat intelligence and info-security vulnerability hunting. Amalgamating the latest technology of artificial intelligence, predictive analytics and cognitive messaging to serve millions of customers will be the smartest, most innovative and best winning strategy! AI and regulation will pave the way for Fintech Intelligence. Artificial intelligence will be the new factor of production and it will demonstrate conceivable potential to introduce new sources of growth, reinventing the business in place, changing how work is done and reinforcing the role of people to drive growth in business. Artificial Intelligence will create best Payment intelligence (PI) system at national level which can bring the whole nation together, secured and cleaner of underground and street economies. Imagine a scenario like this "You walk in a shopping mall and get a sms which reads "Walk on to 3rd floor to buy your favorite brand of cloths and get 20% discount".

Through the use of artificial intelligence, we will let billions of people have a go at experiencing the joy of flying," said Mr Xiong, 28, who is also EHang's chief marketing officer.

Lunit Inc., a member company of the K-ICT Born2Global Centre, has developed a deep learning-based technology for analyzing medical images that dramatically lowers the rate of misdiagnosis. Currently, the AI technology is being subjected to a sophistication process in cooperation with major medical institutions in Korea, including Seoul National University Hospital, Severance Hospital of Yonsei University Health System, Samsung Medical Center, and Asan Medical Center. Anthony Paek, the CEO of Lunit, explained, "The data-driven imaging biomarker (DIB) technology that Lunit proposed for the first time ever in 2015 is an AI system that has learned abnormal and clinically significant image patterns from big data." He went on to add, "Currently, DIB technology has achieved an accuracy level comparable to that of human experts. In the future, however, we will have new DIB technologies capable of outperforming humans."

Speed to insight is going to emerge as the key competitive differentiator for businesses, as they start stepping into the era of compute-and-speed-hungry artificial intelligence(AI), and deep learning workloads. IBM, recently announced a new line of accelerated IBM Power Systems Servers, keeping this new requirement of businesses in mind. The systems are built on its new POWER9 processor, which reduces the training times of deep learning frameworks significantly from days to hours and allows building more accurate AI applications in considerably less time. "The era of AI demands a tremendous amount of processing power at unprecedented speed," said Monica Aggarwal, Vice President, IBM India Systems Development Lab. "To meet the demands of the cognitive workload, businesses need to change everything right from the start- the algorithms, the software, and the hardware as well. POWER9 systems bring an integrated AI platform designed to accelerate machine learning and deep learning with both software and hardware that are optimized to work together."

In this paper, we present an initial attempt to learn evolution PDEs from data. Inspired by the latest development of neural network designs in deep learning, we propose a new feed-forward deep network, called PDE-Net, to fulfill two objectives at the same time: to accurately predict dynamics of complex systems and to uncover the underlying hidden PDE models. The basic idea of the proposed PDE-Net is to learn differential operators by learning convolution kernels (filters), and apply neural networks or other machine learning methods to approximate the unknown nonlinear responses. Comparing with existing approaches, which either assume the form of the nonlinear response is known or fix certain finite difference approximations of differential operators, our approach has the most flexibility by learning both differential operators and the nonlinear responses. A special feature of the proposed PDE-Net is that all filters are properly constrained, which enables us to easily identify the governing PDE models while still maintaining the expressive and predictive power of the network. These constrains are carefully designed by fully exploiting the relation between the orders of differential operators and the orders of sum rules of filters (an important concept originated from wavelet theory). We also discuss relations of the PDE-Net with some existing networks in computer vision such as Network-In-Network (NIN) and Residual Neural Network (ResNet). Numerical experiments show that the PDE-Net has the potential to uncover the hidden PDE of the observed dynamics, and predict the dynamical behavior for a relatively long time, even in a noisy environment.