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) …
Zendesk, customer service and engagement solutions provider, recently introduced the expansion of its Answer Bot product. Answer Bot is a machine learning tool that helps customers find answers for themselves. It pulls data from the Zendesk Guide knowledge base and suggests articles to help customers solve problems on their own. Answer Bot has been around for a few years. However, Zendesk is expanding the service through integration capabilities through API, SDK, Web Widget, and forms (both email and web).
Walmart is using computer vision technology to monitor checkouts and deter potential theft in more than 1,000 stores, the company confirmed to Business Insider. The surveillance program, which Walmart refers to internally as Missed Scan Detection, uses cameras to help identify checkout scanning errors and failures. The cameras track and analyze activities at both self-checkout registers and those manned by Walmart cashiers. When a potential issue arises, such as an item moving past a checkout scanner without getting scanned, the technology notifies checkout attendants so they can intervene. The program is designed to reduce shrinkage, which is the term retailers use to define losses due to theft, scanning errors, fraud, and other causes.
As AI algorithms--and the computing power that drives them--improve year-on-year, their ability to positively transform the world in which we live is unquestionable. In fact, PwC predicts that AI could contribute up to $15.7 trillion to the global economy by 2030. Indeed, as many as one-in-five (20 percent) of the 1,000 US organisations recently surveyed by PwC had plans to implement AI enterprise-wide in 2019. The PwC research also reveals how companies are increasingly initiating AI models at the very core of their production processes, in a bid to enhance operational decision-making and provide forward-looking intelligence to people in every function throughout the business. To many, this move to AI is no surprise.
AI offers exceptional opportunities particularly in digital marketing while irrefutably revolutionizing and propelling the industry. AI is the ability of a computer or computer-enabled robotic systems to process massive amounts of in-depth data and produce outcomes similar to the thought processes of humans in learning, analysing, decision making, and problem-solving. Hence, AI has enabled marketers to comprehend vast data to gain valuable consumer insights, and in turn, improve digital marketing strategies. The applications of AI are essentially limitless, and the field of computer science is on a stark ascendance. The global AI market was worth $7.35 billion in 2018, where the largest portion of revenue was stirred from enterprise applications.
This story was co-published with ProPublica. Ariella Russcol specializes in drama at the Frank Sinatra School of the Arts in Queens, New York, and the senior's performance on this April afternoon didn't disappoint. While the library is normally the quietest room in the school, her ear-piercing screams sounded more like a horror movie than study hall. But they weren't enough to set off a small microphone in the ceiling that was supposed to detect aggression. A few days later, at the Staples Pathways Academy in Westport, Connecticut, junior Sami D'Anna inadvertently triggered the same device with a less spooky sound--a coughing fit from a lingering chest cold.
Do you want to optimise your processes? To manage the increasing volume of data facing by modern organisations today, Artificial Intelligence technologies (AI) offers a new way to ease the ingestion, enrichment and exploitation of their information. Automatic image recognition creates personalised customer experiences, delivering a true competitive advantage. Adding context to your information, AI can bring the right data, to the right person at the right time, delivering superior benefits for companies: happier and more productive teams, increased ROI and a personalised experience for your customers.
In my last article, How to Use AI to Control Your Smart Home, I discussed the changes coming to residential automation with the introduction of AI and processing performed in the cloud. This is bringing advances to smart homes that were the dreams of science fiction only a few years ago. However, with great power comes great responsibility and there is a dark side to the power of AI in a home; privacy. Anyone watching the news is aware of the near-daily headline of privacy fiascos by major technology corporations. Unfortunately, some of these are the same corporations that are delivering a number of the most advanced AI products for smart homes.
When Conor Sprouls, a customer service representative in the call center of insurance giant MetLife talks to a customer over the phone, he keeps one eye on the bottom-right corner of his screen. There, in a little blue box, A.I. tells him how he's doing. The program flashes an icon of a speedometer, indicating that he should slow down. A heart icon pops up. For decades, people have fearfully imagined armies of hyper-efficient robots invading offices and factories, gobbling up jobs once done by humans.
First, before I start, I want to say something about what that is, or what I understand from this. So, here is one interpretation. It is about using data, obviously. So, it has relationships to analytics and data science, and it is, obviously, part of AI in some way. This is my little taxonomy, how I see things linking together. You have computer science, and that has subfields like AI, software engineering, and machine learning is typically considered to be subfield of AI, but a lot of principles of software engineering apply in this area. This is what I want to talk about today. It's heavily used in data science. So, the difference between AI and data science is somewhat fluid if you like, but data science tries to understand what's in data and tries to understand questions about data. But then it tries to use this to make decisions, and then we are back at AI, artificial intelligence, where it's mostly about automating decision making. We have a couple of definitions. AI means using intelligence, making machines intelligent, and that means you can somehow function appropriate in an environment with foresight. Machine learning is a field that looks for algorithms that can automatically improve their performance without explicit programming, but by observing relevant data. And yes, I've thrown in data science as well for good measure, the scientific process of turning data into insight for making better decisions. If you have opened any newspaper, you must have seen the discussion around the ethical dimensions of artificial intelligence, machine learning or data science. Testing touches on that as well because there are quite a few problems in that space, and I'm just listing two here. So, you use data, obviously, to do machine learning. Where does this data come from, and are you allowed to use it? Do you violate any privacy laws, or are you building models that you use to make decisions about people? If you do that, then the general data protection regulation in the EU says you have to be able to explain to an individual if you're making a decision based on an algorithm or a machine, if this decision is of any kind of significant impact. That means, in machine learning, a lot of models are already out of the door because you can't do that. You can't explain why a certain decision comes out of a machine learning model if you use particular models.
Humans cannot compete with artificial intelligence when it comes to deconstructing big data. AI facilitates multiple ways to segment your audience to gain intelligent insights that allow retailers to personalise in a range of different ways. Buyers expect the'you may also like this' feature to show items that are relevant to their tastes. Personalised merchandising sorts the product display to show customers products that genuinely appeal to them. This can even include personalised navigation of the site, with a personalised home page, which is proven to increase conversions.