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.
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.
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?
CEO Bill McDermott predicted that over the next five to 10 years machine learning, artificial intelligence, and augmented reality will increasingly come to the fore: "I think very strongly that intelligent applications will fundamentally change the way you do work in the enterprise and the way you collaborate with your trading partners outside of the enterprise," he said. McDermott went on to say that machine learning has the capabilities to help businesses make more informed decisions around how they can better serve their end-customer. "We need the system to tell us what to do," he said. "Based on algorithms of that data and inputs that are in that data bank, we need to be able to advise you on the next step for your sales cycle, who you should meet with, and what the expected outcomes are, and what the level of probability would be on you striking a deal." At the same time, McDermott said the appeal of using machine learning as part of business processes is that it will "liberate workers."
As SAP continues to makes its own transition into the cloud, the company is also focused on delivering applications that will help customers make that same change simpler. At this year's recently held SAP Sapphire Now conference in Orlando, Florida, a key theme for the company was introducing machine learning to its HANA cloud platform. CEO Bill McDermott predicted that over the next five to 10 years the hype will be around machine learning, artificial intelligence, and augmented reality. "I think very strongly that intelligent applications will fundamentally change the way you do work in the enterprise and the way you collaborate with your trading partners outside of the enterprise," McDermott said. He went on to say that machine learning has the capabilities to help businesses make more informed decisions around how they can better serve their end-customer.
He went on to say it's no longer viable for businesses to just automate internal processes, rather the future needs to focus on using automated systems to make intelligent predictions. We're not just automating internal sales process anymore so the sales director has a sales forecast that makes sense. For example, if you're matching a job candidate and profile in the human capital management department, or you're selling a product as a retailer and on social media you're getting a lot of feedback, the machine will learn what that feedback is and make a decision on what the response should be based on what is going on," he said. The company first announced the Digital Boardroom at last year's Sapphire event, which it touted at the time would "contextualise and simplify performance reporting across all areas of business in real-time".
In this context, business application journey has not finished yet. Over this subject, SAP believes on the use of machine learning technology supporting business processes to achieve truly "work liberation". The idea is to have the machine learning from input data and provide a decision on the expected decision to make based on what is happening. SAP has expressed the commitment for supporting customers journey to obtain the best assets for real insight through the pillars of innovation and empathy.