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) …
"The potential benefits are huge; everything that civilization has to offer is a product of human intelligence; we cannot predict what we might achieve when this intelligence is magnified by the tools that AI may provide…" Stephen Hawking famously wrote about the potential for AI to aid humans in creating unprecedented transformation and innovation. Today's businesses focus on improving the customer experience. Customers have more options than ever before, so maintaining loyalty requires innovation, speed, responsiveness and the tools to predict the wants, needs, and preferences of the consumer or client. AI and Machine Learning provides incredibly valuable opportunities for organizations to win over the customer and meld incomparable human insight and judgment with automated intelligence to improve the overall customer experience. Business Analytics systems, most significantly in enterprise environments, are dependent on Machine Learning to process unquantifiable scores of data, and make distinctions between useful, meaningful data, and valueless data.
The'mobile first' movement has resulted in most UX investments being focused on smartphones, tablets, smart home devices, etc. However, the faithful computer and laptop continues to be the workhorse of the masses and is where the most demanding and high-security tasks are performed. So why is it that there are no user-friendly and secure solutions for authenticating into computers and laptops? The insecurity of passwords is a UX problem, and shortcuts to make them easier lead to security risks, which lead to breaches. Most of the much-publicized mega-data breaches the past few years have been because of compromised or stolen passwords.
The 2019 edition of Opus Research's Decision Makers' Guide to Enterprise Intelligent Assistants report determined 7 AIVA to be a top solution for enterprises, and the only virtual agent solution capable of delivering across a breadth of simple FAQs to complex, conversational issues to online transactions. The Opus report presents a comprehensive assessment of 16 enterprise-grade Intelligent Assistant solution providers, with a focus on natural language processing, machine learning, AI, analytics and customer management integration to power digital self-service solutions. The report highlights 7 AIVA's ability to support both voice and digital channels and deliver unified self-service, calling out the company's differentiators as being a unique blend of AI and human insights, two decades of unparalleled experience in customer journeys across all channels, and proprietary insights including more than 150 patents and patent applications. "We analyzed a short-list of the leading providers in natural language processing, machine learning, AI and analytics to develop the industry's most comprehensive assessment of today's virtual agents and digital self-service solutions," said Dan Miller, lead analyst, Opus Research. An agent can take over a bot conversation at any time, and hand the conversation back to the bot to complete the interactions.
The researchers compared the abilities of their hybrid algorithm with those of a purely neural network–based approach published last year (Nature 2018, DOI: 10.1038/nature25978). The two methods were about equally effective at proposing synthetic steps that matched published reactions when their training data included thousands of examples of those reactions. But when there were fewer than 100 examples, the neural network approach rarely identified a verified transformation, while the hybrid version of Chematica found it more than 75% of the time. Several of the hybrid program's proposed reactions to synthesize the glaucoma drug bimatoprost were not represented in its training data, demonstrating its ability to use unusual reactions.
Yes, new technology makes many jobs obsolete. But history shows us that the most dangerous and repetitive jobs are typically the first to go. Consider Ernest Shackleton's storied classified ad for his Imperial Trans-Antarctic expedition in 1914: "Men Wanted for Hazardous Journey. Then, treacherous work for low wages was an accepted reality. Slightly over 100 years later, technological advancements have made such working conditions unacceptable and much less of a reality.
The world is awash in data like never before. From a person's morning Uber ride and favorite coffee spot, to the emails sent from their office--all these activities create massive amounts of data, but also behavioral and investment insights. Warren Buffett's investment style exemplifies the fundamental approach: "Which companies offer the best returns?" On the other hand, hedge fund manager James Simons of Renaissance Technologies is a notable example of the quantitative approach: "What is the best way to predict returns?" Both techniques have one thing in common--they seek excess return from the marketplace, or what is known as "Alpha".
With AI making content production more efficient, marketers can focus on creating human connections with audiences. There's little disagreement that AI and other cognitive technologies hold tremendous potential to bring speed and precision to the content supply chain. For many marketers, however, the question remains: How can brands gain those efficiencies without losing the human insights and empathy that are so critical to effective campaigns? "AI can do a tremendous job at automating the long tail of content and creative production," says Alan Schulman, chief creative officer for customer & marketing with Deloitte Consulting LLP, pointing to tasks such as distributing content at scale and customizing it in multiple languages. "That enables marketers to focus on the ideation and creation process--on finding the fundamental truth that is going to resonate with audiences. That's where the heart and feeling is, and it's still very much a human process."
As fraudsters become more brazen in their efforts, banks are realizing they need to do more than simply respond to suspicious activities as they find them. Instead, a deeper understanding of fraud -- down to its genetic outline -- is needed to be truly effective in fighting it. The new Digital Banking Tracker highlights how banks are adopting new approaches to protect their customers and clients from nefarious actors. Fighting fraud is often a group effort, as can be seen in several global markets. In the UAE, for instance, a group of banks recently banded together to crack down on acts of check-related fraud.
AI is real to many of us in business. Yet much of the debate about machine learning, AI and the use of Big Data remains hyperbolic. Headlines screeching about robot takeovers and mass job losses might do well for click-rates. Data specialists and early adopters may wax lyrical about the technological advances being made, and how these processes far outstrip the capacity, speed and computational power of mere mortals. But both polarities are far behind the more complex, interesting reality – and they're missing out on the real news for us humans.