If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
On February 9, 2017, two technology market leaders made announcements: SAP unveiled its next-generation intelligent ERP system, and Nvidia announced that demand for artificial intelligence (AI) applications was driving demand for its graphics platform. Simply speaking, cognitive computing refers to self-learning systems that mimic the way the human brain works. In the SAP announcement, the "intelligent" piece of "intelligent ERP" comes from a digital assistant (SAP CoPilot) of which users can ask questions and to which they can give commands via voice, text, or gestures, just as they would to a human assistant. We might do the same on our path to build artificial intelligence brains."
On February 9, 2017, two technology market leaders made announcements: SAP unveiled its next-generation intelligent ERP system, and Nvidia announced that demand for artificial intelligence (AI) applications was driving demand for its graphics platform. On the face of it, these announcements were business as usual – routine sound bites that proliferate in the tech news landscape. Look a bit deeper, though, and you realize that this day marked a profound shift in both the way businesses use technology and the implications for the rest of us. For decades, developing a computer that could think has been the Holy Grail of technology. And while we have made tremendous progress in our ability to process vast amount of data, the "thinking" part has remained mostly elusive.
Constellation Research hopes you all have a great holiday season this year with friends and family. In the spirit of recognizing memorable achievements in the tech industry, we also want to use this occasion to announce the winners of Constellation's first annual Enterprise Awards. The winners were selected through a combination of internal voting and heated debate among Constellation's analyst team. Each category also includes a number of runner-up winners, as there were so many deserving of recognition. We hope you enjoy reading the results and welcome your comments--approving, dissenting and otherwise.
As more organizations make serious efforts to digitally mature next year -- a surprising 74% are still early or just beginning to mature according to Deloitte's latest digital future's report -- one key question they're asking is what the right technology stack is to use as the basis. Given the breadth and depth required of most transformation efforts -- from the requisite technologies and operating processes to digital talent and business models -- the industry has learned that establishing an effective foundation for the digital future state is vital. In fact, I've found that transforming digitally on top of a strong set of digital fundamentals is a leading best practice that has been validated repeatedly as we look as recent examples of digital transformation, most notably at Nordstrom, General Electric, and TravelEx. So my trip to Barcelona a few weeks ago to SAP's information packed yearly TechEd event afforded me the opportunity to assess the company's latest platform evolution. My goal was to size it up with a lens towards assessing it as a digital transformation-ready platform.
As market leader in enterprise application software, SAP helps companies of all sizes and industries innovate through simplification. From the back office to the boardroom, warehouse to storefront, on premise to cloud, desktop to mobile device - SAP empowers people and organizations to work together more efficiently and use business insight more effectively to stay ahead of the competition. SAP applications and services enable customers to operate profitably, adapt continuously, and grow sustainably. Purpose and Objective: SAP Labs, LLC seeks a Software Developer at our Dublin, CA location to be responsible for development focusing on design, coding, testing, quality assurance of complex product features in a development team pertaining to Machine Learning as it relates to streaming data. Resolves complex issues within and around machine learning aspects inside a enterprise level systems kernel that is like a database kernel.
One day we will "think about machine learning the way we think about electricity: It's hard to imagine the world without it," said SAP Chief Innovation Officer Juergen Mueller at the recent SAP TechEd Barcelona. Under Mueller, SAP has embarked on a journey to bring machine learning to business around the world, essentially "electrifying" all applications with this technology. For the uninitiated, machine learning takes Big Data, runs it against sophisticated algorithms and helps applications to learn from this information. Massively improved computing power makes this possible in real time. Most importantly, it allows applications to "think" and independently resolve problems – going beyond what they were explicitly programmed to do, and often what humans can do.
Companies like Google, IBM and SAP are making massive investments in artificial intelligence. German software maker SAP is investing heavily in artificial intelligence, or AI, especially for business software. AI is expected to fundamentally change our lives in the near future. Cars that navigate autonomously through traffic. Digital assistants that provide doctors with key information needed to make a diagnosis.
"There has been a dramatic increase in work in the last five or six years, coming from the exponential data explosion and an increase in audit regulation bureaucracy," Neil Kinson, chief of staff at enterprise process automation provider (and long-time SAP partner) Redwood Software, said in ZDNet last week. "The automation is being created to solve that problem, rather than to cut costs, [and] a lot of organizations are applying automation just to cope." And we may have only spotted the tip of this iceberg. "We'll see more innovation in the next two years than we have in the last 10 years, all driven by AI," Rod Drury, CEO and founder of New Zealand's cloud-based accountancy software provider Xero, said in Business Insider on Monday. "We're getting a fantastic hit because the fintech space is a relatively small domain with massive amounts of data, and it's inherently high value."
Back in the days when "Bubbles," the liquid-cooled Cray 2, was the fastest supercomputer in the world and before LISP was the programming language of choice in Marvin Minsky's new AI Lab at the Massachusetts Institute of Technology, the pioneers of artificial intelligence (AI) had lofty goals. They believed that AI would eventually give machines the same thinking capabilities as humans. While some question whether machines will ever be able to think in exactly the same way as humans, machine learning and other AI techniques already enable machines to assist humans with complex tasks such as forecasting and reduce the need for people to undertake trivial repetitive tasks. Endowing computers with human-like intelligence has been the holy grail of computer experts since the dawn of electronic computing. Although the term artificial intelligence was not coined until 1956, the roots of the field go back to at least the 1940s, and the idea of AI was crystalized in Alan Turing's famous 1950 paper, "Computing Machinery and Intelligence."
The world's biggest tech companies are investing heavily in artificial intelligence (AI): software that can learn to think and solve problems in a human-like way. Each company takes a slightly different approach to making business processes smarter through the development and deployment of machine learning, or cognitive computing. David Schatsky, head of the trend-sensing program for the US innovation team at Deloitte said at the AI Summit in London earlier this year that the big victories in artificial intelligence over the last couple of decades have all been in games, from IBM's Deep Blue mastering chess in 1997, to Deep Mind's AlphaGo beating Lee Sedol at Go this year. Read next: 10 innovative businesses using IBM Watson: Which companies are using Watson's big data and analytics to power their business?