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) …
Artificial intelligence (AI) is changing the face of business. No longer a futuristic concept, its impact is real. From tech giants like Google, Apple and Amazon to user-centric behemoths like Uber and Starbucks, everyone seems to be using AI technology to transform the customer experience (CX). But, it's not just corporate giants that are deploying AI. Smaller organizations are following suit.
Artificial Intelligence is beginning to have transformative effects on consumers, enterprises, and governments around the world. The impacts are contributing by automating repetitive task, creating efficiencies, ubiquitously improving user experience, and creating ways for humans to improve our cognition. Furthermore, by 2020, the AI market is projected to reach $70 billion, driven by increasing computational power and improving approaches/applications with machine, deep learning, natural language processing and robotics and many a number of other technologies. To gain a better understanding of the perception of AI in the US, PwC surveyed 2,500 consumers and business decision makers. The objective is to better understand their attitudes towards artificial intelligence, and the future implications on business and society.
Today's analytical workloads require faster query performance, advanced analysis methods, and more frequent data updates. For real-time analysis of massive data sets, particularly for use cases where time and location matter, enterprises are turning to new next-generation databases to explore data faster and uncover new insights. "Based on its enormous potential, investments in AI can be expected to increase in 2018, while investments in IoT will need to show measurable return," said CTO and Cofounder of Kinetica Nima Negahban. "The ability to operationalize the entire pipeline with GPU-optimized analytics databases now makes it possible to bring AI and IoT to business intelligence cost-effectively. And this will enable the organization to begin realizing a satisfactory ROI on these and prior investments."
A recent Accenture survey found that 85% of business executives plan to invest heavily in AI-related technologies over the next three years. Most investments, according to the report, will be in major business processes, underpinning a company's finance and accounting, marketing, procurement, and customer relations activities. Ruchir Puri, an IBM fellow and chief architect of IBM Watson, certainly thinks so. "There are many opportunities for AI across front, middle, and back office process, throughout lines of business and within various verticals," Puri noted. "AI capabilities, such as conversation, vision and language technologies, can be used to solve a range of practical enterprise problems, boost productivity and foster new discoveries across any area it is applied to."
In 2018, we will see a rise in artificial intelligence-powered cyberattacks. TechRepublic's Dan Patterson met with IBM Security's vice president of threat intelligence Caleb Barlow to discuss what this means for businesses. Artificial intelligence (AI) and machine learning can be used to help defenders, however the bad guys can also use it to find vulnerabilities in all of our systems, Barlow said. "As we move into 2018, we enter a world where we start to see AI vs. AI, and this is all about staying one step ahead of the bad guys with newer technology, better approaches, and better analytics," he added. Hackers and enterprises have different resources to AI, and they use it for different reasons.
Enterprise software's days are numbered, and if you don't adopt artificial intelligence (AI) and machine learning, your data center will be useless. Those are the claims of Gartner Research Vice President Milind Govekar, who gave a presentation at Gartner's annual conference for IT infrastructure operations professionals recently in Las Vegas. Govekar said that as soon as 2019, at least a third of the largest software vendors will have transitioned their products from cloud-first to cloud-only. Although he didn't mention it by name, you have to think Microsoft is in that category because it is already cloud-first with its enterprise apps. Office 365 already outsells the packaged Office 2016, so I can see a major de-emphasis of the client product in the coming years.
Check out Kris Hammond's tutorial, "AI in the Enterprise," at our 2018 AI Conference in New York City or Beijing. Subscribe to the O'Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes, SoundCloud, RSS. In this episode of the Data Show, I spoke with Kristian Hammond, chief scientist of Narrative Science and professor of EECS at Northwestern University. He has been at the forefront of helping companies understand the power, limitations, and disruptive potential of AI technologies and tools.
As 2017 is coming to its end, it's an opportune time to look at what C-suite executives will be turning their attention to in the coming months. Deloitte's recently released Technology, Media and Telecommunications (TMT) Predictions, provides insights into key technology trends on the consumer and business front. While some may come as no surprise, these developments could have a significant impact on enterprise strategies. Machine learning will intensify for businesses across the board. Medium and large-sized enterprises surveyed say they will double the number of implementations and pilot projects using machine learning technology in 2018, and then double it again by 2020.
There's no doubt that 2017 was an exciting year for Intelligent Virtual Assistants (IVAs) and artificial intelligence. We conducted research showing that consumers' comfort with automated technology is increasing, and most are willing to try out new methods for resolving customer service issues. We also saw how the introduction and growth of new customer care channels such as social media have led to new challenges for enterprises looking to provide a consistent, omnichannel experience for their customers. And, finally, the integration of technology such as voice biometrics has increased the overall security of IVAs and expanded what they can be used to accomplish. Now that we're into a new year, we want to look ahead to what 2018 has in store for IVAs.
Jon Oltsik, an analyst at Enterprise Strategy Group in Milford, Mass., looked into potential pitfalls associated with enterprise security teams collecting ever-increasing reams of data. ESG research indicates that 38% of organizations collect more than 10 TB of data every month, primarily from firewall logs, network devices, antivirus and user activity logs. "Let's face it, well-intentioned security teams are being buried by data today. They go through heroic efforts and do what they can, but there is an obvious and logical outcome here: As security data volume grows, security professionals will only be able to derive an incremental amount of value," Oltsik said. For organizations swamped with security data, Oltsik recommends making data available through standard APIs or putting data in standard formats such as the Common Information Model used by Splunk.