It's a world of opportunity rapidly pressuring organizations of all sizes to rapidly adopt technology to not just survive, but to thrive. And Andrew Dugan, chief technology officer at Lumen Technologies, sees proof in the company's own customer base, where "those organizations fared the best throughout covid were the ones that were prepared with their digital transformation." And that's been a common story this year. A 2018 McKinsey survey showed that well before the pandemic 92% of company leaders believed "their business model would not remain economically viable through digitization." This astounding statistic shows the necessity for organizations to start deploying new technologies, not just for the coming year, but for the coming Fourth Industrial Revolution. This podcast episode was produced by Insights, the custom content arm of MIT Technology Review. It was not produced by MIT Technology Review's editorial staff. Lumen plans to play a key role in this preparation and execution: "We see the Fourth Industrial Revolution really transforming daily life ... And it's really driven by that availability and ubiquity of those smart devices." With the rapid evolution of smaller chips and devices, acquiring analyzing, and acting on the data becomes a critical priority for every company. But organizations must be prepared for this increasing onslaught of data.
IBM Watson is considered the grandfather of cognitive search and natural language processing, and Scott Parker was there for its birth. The company he worked for at the time, Vivisimo, had been acquired by IBM, and its enterprise search technology formed a major component of the Watson solution. That was Parker's introduction to the art and science of enterprise search technologies. Now the director of product marketing at enterprise search technology company Sinequa, Parker leverages the power of intelligent search to help extract valuable insights from customer's data. Sinequa is a sponsor of Simpler Media Group's Digital Workplace Experience, starting today as a free, virtual event.
Advertising stands to be rebooted by advances in artificial intelligence – but the industry must re-learn practices to embrace the power of machine learning. In this video interview with Beet.TV, Hlavacek explains how AI could make a step-change. "A number of players in the ecosystem – ad-tech companies, publishers, marketers – they're starting to understand how AI can help them predict what actions their consumers are going to take when they don't have all the data that they're used to having," he says. "AI is a new category of advertising and it's really going to change everything that we do, much of the way programmatic changed everything that close to a decade ago happened in the digital space." So, what is AI really?
How would you describe what Artificial Intelligence is? Michael: When we talk about AI, some people tend to imagine the Terminator. For others, it might be Baymax from "Big Hero 6", "WALL-E", or Hal from "2001: A Space Odyssey". What those examples all have in common is the assumption that AI is unavoidably destined (sooner or later) to develop it's own consciousness and autonomous, evil intent. But when it comes to these portrayals of AI, too often they generate an array of fears by focusing our attention on distant and somewhat dystopian possibilities, rather than the present day realities. They usually depict AI as an alignment of computer intelligence with consciousness, but then frighten us by portraying a world where it's not only conscious, but also evil minded and self-motivated to overtake and destroy us. However, I think it's better to talk about AI in a little bit of a different way.
Regular readers will likely wonder what more I could have to say about machine learning (ML) in search, after having written How Machine Learning In Search Works just a few months ago. Let me assure you, this article is different. Today you won't be reading the ramblings of an SEO professional who fancies himself reasonably informed in how machine learning works as it's related to search. Instead, we'll be turning the tables and learning about search implementations from the perspective of a machine learning expert. This article outlines and hopefully expands on some of the core concepts discussed in an amazing interview with fellow Search Engine Journal contributor Jason Barnard and Dan Fagella of Emerj.
A few weeks ago, I was interviewed by Tim Hughes, of DLA Ignite, about the five biggest mistakes that people make about AI and its impact on the workplace. This article is based on the full interview, which you can find here. It is the use of machinery to replicate a unique human activity, from punch cards that operated sophisticated weaving looms during the industrial revolution, to mid-twentieth century business computers that calculated bills and operated the payroll. Very often these activities are repetitive, error-prone, and in some cases life-threatening. The principle of automation is nearly always the same.
The crystal ball that can predict when, where, and how a customer will spend their money has a new name and it goes by Programmai. This predictive marketing software uses customer data to accurately predict customer spending for both the short and long term. Programmai can even predict the future lifetime value of a customer based on the first interaction. Applying machine learning, marketers can use predictive values from Programmani to develop marketing programs and hone acquisition costs, no longer taking stabs in the dark but instead basing these decisions on justifiable data and forecasts. London TechWatch caught up with CEO Dean Murr to find out how his previous experience at Asos led him to create Programmai, the company's experience raising during the pandemic, and recent funding round.
This particular article needs more visibility on Medium, especially to Machiner Learning practitioners. Wael transcribes an interview with Michael Kanaan, an individual that held an AI leadership role in the US Airforce, and is currently working with MIT's primer AI Lab. Early on in the interview, Michael quickly discards the stereotypical portrayal of AI within Hollywood movies and provides the reader with a more accurate description of AI. Michael accurately points out that what we call AI are simply machine learning algorithms that can derive patterns from data, which in turn creates a predictive model of subject of interest, such as a person's behaviour, stock prices etc. The interview goes on to include discussions around the type of individuals that are suitable for roles in AI, a conversation in which Michael debunks the myth that AI-based positions are reserved for individuals with a STEM(Science, technology, engineering, and mathematics) background.
IBM is a multinational technology company founded in 1911 and operates in over 170 countries worldwide. Today, IBM offers a wide spectrum of products and services that includes software solutions, hardware architecture (server and storage architecture), business and technology services, and global financing solutions. As a data driven-company, IBM understands the importance of data and data analytics at every layer of organization to drive better business decisions. Also, a leading provider of Analytics and Cloud-based solutions, IBM offers a full stack of cloud-based products and services spanning across data analytics, storage, AI, IoT, and blockchain. Check out this article about the Microsoft Data Scientist interview!
Stories create a sacred space that humans have always respected. And science fiction takes us one step further. It gives us the space to imagine what we could be, could do, could make. And sometimes these stories give us an all too real vision of what may yet come to be in our own world. In his new novel, The Ministry for the Future, Kim Stanley Robinson paints a picture of a global temperature that's been allowed to keep rising unchecked, and the harsh results of humanity's inaction. The novel "is about the next three decades," says Robinson.