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) …
Martin Taylor is the Deputy CEO and Co-Founder of Content Guru. In the past couple of years, contact centers have suddenly undergone an extreme character makeover, from asset-sweating tech laggard to leading light in intelligent automation. How has this corporate ugly duckling turned itself into a digital swan? Under pressure to differentiate service offerings and add personalization, many organizations have been quietly deploying key AI technologies -- especially natural language processing (NLP), image recognition and data analysis. The contact center's application of these general-purpose AI technologies is transforming how they model and predict call volumes, enable new automated self-service channels and evolve the role of their oft-maligned workers.
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For the second part of this article series, see here. It has only been 8 years since the modern era of deep learning began at the 2012 ImageNet competition. Progress in the field since then has been breathtaking and relentless. If anything, this breakneck pace is only accelerating. Five years from now, the field of AI will look very different than it does today.
DWS's stake in Arabesque showed how asset management is moving towards AI-powered investing. Artificial intelligence, hailed as investing's next frontier, is already widespread in various forms, but its true potential in portfolio management is still far from being fulfilled. In a study on AI and finance for the Alan Turing Institute, Professor Bonnie Buchanan puts AI's "impressive" growth down to declining processing and data-storage costs, and an immense availability of data. But compared to other fields, the quantity of data or the ability to create and collect new investment data is still not sufficient, despite its abundance, according to Michael Neumann, head of AI quant investing at Arabesque AI in London. Financial data also comes with a lot of'noise', and the definition of success or failure can be more nuanced.
Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Universal Studios Japan has announced an opening date for its Super Nintendo World – and you won't have to fall through any sewer pipes to get in. The theme park will open February 4. (Universal Studios Japan) The specialty video game-themed park will be opening February 4, 2021 in Osaka. The world's first Super Nintendo World will consist of a "highly themed and immersive land featuring Nintendo's legendary worlds, characters and adventures where guests will be able to play inside their favorite Nintendo games," according to a press release shared with Fox News.
When you look more closely at estimates that one-third or one-half of jobs will be "automated," the evidence actually tends to show that one-third to one-half of jobs will be changed in the future by use of technology. Maybe some of those jobs will disappear, but in many other cases, the job itself will evolve, as jobs tends to do over time. Of course, it's a lot less exciting to have a headline which says: "The information technology you use at your job is going to keep changing change in ways that affect what you do at work." Qualifier 2 – job creation from automation An overall view of the effects of automation on jobs also needs to take into account how, over time and in the present, automation has also led to the creation of many new jobs. Lest we forget, the US unemployment rate before the pandemic hit was under 4%, which certainly doesn't look like evidence that total jobs are being reduced.
Amazon Web Services is rolling out a series of new tools within its industrial Internet of things lineup that aim to improve machine performance and uptime. First up the company announced Monitron, a condition monitoring service for customers that currently lack an existing sensor network. The system and its array of sensors can detect potential failures on critical equipment, allowing for the implementation of a predictive maintenance program. For those customers that do have an existing sensor network, AWS introduced an API-based machine learning (ML) service called Lookout for Equipment that functions as a pathway to send sensor data to AWS for predictive modeling. Like Monitron, Lookout for Equipment analyzes sensor data to detect abnormal behavior on industrial machines.
At the end of a three-hour keynote address for Amazon's annual re:Invent conference, which is taking place virtually this year, Amazon Web Services chief executive Andy Jassy wrapped up with an extended discussion about edge computing and its role in hybrid computing. "Hybrid is not just about whether its on-premise or in the cloud," said Jassy. Instead, IT needs "the same APIs, the same control plane, the same tools, the same hardware they get in AWS regions," said Jassy. He was referring to Amazon's AWS Outposts, a rack of equipment deployed at a customer facility that is a fully-managed service from Amazon. Jassy said Amazon has made the Outposts offering easier to purchase now with new form factors, 1U and 2U rack units, versus an entire rack-size deployment.
Amazon Web Services is adding to its portfolio of business intelligence (BI) services with the preview launch of QuickSight Q, a natural language query tool that functions as a companion feature for its QuickSight cloud service. With QuickSight Q, users can search databases using everyday, natural language and receive an response in seconds, said AWS CEO Andy Jassy during his keynote at the company's annual re:Invent developer conference. Using machine learning and natural language processing, trained over multiple data points and business areas, Q is able to extract business terms (such as revenue, growth, allocation, etc.) and intent from a user's question, surface the related data from the source, and return the answer in the form of numbers and graphs. "We will provide natural language to provide what we think the key learning is," said Jassy. "I don't like that our users have to know which databases to access or where data is stored. I want them to be able to type into a search bar and get the answer to a natural language question."
Marshall McLuhan once famously observed, "First we build the tools, then they build us." Building on artificial intelligence (AI), the Internet of Things (IoT), and 5G communications, advanced software systems are remaking the nature and complexity of human engineering. In particular, digital twin technology can provide companies with improved insights to inform the decision making process. In this day and age, processes and machines are so complex that the risks of failure or disruption from experimenting with different approaches becomes too high or costly. To use an old analogy, it's tough to change the wheels on a moving train. And that can be frustrating when new designs might provide significant benefits to existing systems.