Designed to help understand the fundamentals of DS & Algorithms really well. A must have for programming interviews.

With cloud-based, self-learning search, all the required components are hosted and managed by the vendor, such as Coveo. Because of its scalability, it has the potential to change the customer service industry the same way machine learning has impacted e-commerce and social networks. In the past, the high cost of using and managing machine learning systems meant that machine learning was rarely used for traditional enterprise search or self-service support sites. The cloud makes that affordable to all customers and to all departments, especially when deploying self-learning search on self-service support sites and on communities, because of its ability to scale and handle large volumes of data.

SAN JOSE, CA--(Marketwired - Oct 14, 2016) - Technology leaders AMD, Dell EMC, Google, Hewlett Packard Enterprise, IBM, Mellanox Technologies, Micron, NVIDIA and Xilinx today announced a new, open specification that can increase datacenter server performance by up to 10x, enabling corporate and cloud data centers to speed up big data, machine learning, analytics, and other emerging workloads. Servers and related products based on the new standard are expected in the second half of 2017. The new standard, called OpenCAPI and released today by the newly formed OpenCAPI Consortium, provides an open, high-speed pathway for different types of technology -- advanced memory, accelerators, networking and storage -- to more tightly integrate their functions within servers. This data-centric approach to server design, which puts the compute power closer to the data, removes inefficiencies in traditional system architectures to help eliminate system bottlenecks and can significantly improve server performance. OpenCAPI sets a new standard for the industry, providing a high bandwidth, low latency open interface design specification built to minimize the complexity of high-performance accelerator design.

Products using artificial intelligence (AI) are creeping into our lives: in the home, online, at work, in the marketplace, in the doctor's office. What if AI gets carried away, if it hasn't already? Plenty of movies and books that contemplate this. While those scenarios may be easy to dismiss, the consequences of what could happen are not. Unless it's fully grasped for its benefits, companies that use AI are putting their brands at risk if society doesn't adequately understand how it benefits from the technology.

A new report from the Office of Science Technology Policy (OSTP) addresses the fast-growing field of artificial intelligence (AI), which is increasingly poised to reshape the way we live and work. Titled "Preparing for the Future of Artificial Intelligence," the report makes 23 policy recommendations on a number of topics concerned with the best way to harness the power of machine learning and algorithm-driven intelligence for the benefit of society. The OSTP position is that government has several roles to play in driving the direction of AI. Namely, "It should convene conversations about important issues and help to set the agenda for public debate. It should monitor the safety and fairness of applications as they develop, and adapt regulatory frameworks to encourage innovation while protecting the public. It should support basic research and the application of AI to public goods, as well as the development of a skilled, diverse workforce. And government should use AI itself, to serve the public faster, more effectively, and at lower cost."

Research suggests Australians are ready to embrace fintech banking solutions, and the launch of three new London-based chatbot startups may be a sign the rest of the world is gearing up for a revolution too. Artificial intelligence (AI) has been rapidly progressing over the past two decades, with machines reaching and exceeding human performance on an increasing number of tasks. Just this week, the White House released a report entitled Preparing for the future of Artificial Intelligence, which describes the ways in which AI has and continues to yield new opportunities for progress in critical areas such as health, education, energy, and the environment. Another important area of business, ripe for disruption, is finance and banking. In Australia, almost half (47%) the population expect to use financial technology (fintech) services for 50% or more of their financial needs in five years' time.

"It's encouraging to hear how many people are confident that automation and self-service will dominate customer engagement," said Houlne. "We at Humach still believe that humans will be needed to guide and tune these smart machines. Machine learning and artificial intelligence still have a lot left to learn." "2020 Customer" serves as a guide for customer care professionals looking to be proactive in their customer experience strategy. As well as providing interviews and data, it also provides a six-step roadmap for engaging with the customers of the future.

Oren Etzioni, chief executive officer at Allen Institute for Artificial Intelligence, David Kirkpatrick, chief executive officer at Techonomy, and Alex Moore, chief executive officer at Boomerang, discuss the White House's report on artificial intelligence, how A.I. will impact future jobs and the outlook for the technology. They speak to Bloomberg's Emily Chang on "Bloomberg Technology."

As banks look for places to save time and effort by deploying artificial intelligence software, one logical place is cybercrime and fraud investigations. One reason for this is that the amount of cybersecurity threat information keeps growing as the availability of cybersecurity skills in this country shrinks. According to the Ponemon Institute, organizations receive on average nearly 17,000 malware alerts a week, and the time spent responding to these alerts as well as to inaccurate and erroneous intelligence in general costs 1.27 million annually. The group's research has also found that 19% of all security alerts are considered reliable, but only 4% are investigated. According to IBM, 10,000 security research papers are published every year and over 60,000 security blogs are posted each month, adding to the challenge for small security teams to keep up.