DoT Blog

  Image by geralt (Pixabay) When I first read the Light Reading article “ AI looks increasingly useless in telecom and anywhere else,”  I had to pause. Not because the argument was new—I’ve seen plenty of skepticism about AI—but because of the tone. It doesn’t just question AI’s utility, but it paints a picture of a lobotomized society , drifting into an “AI psychosis” where people see machines as sentient companions. Boy, it’s an arresting way to start, but also, perhaps, too convenient a metaphor. The author compares our intellectual reliance on AI to muscles wasting away from disuse, citing early studies that show people who lean too much on generative AI may grow less critical, less precise, and even a little sloppy. It’s a provocative analogy, but one that, in my view, overreaches. Yes, there are legitimate concerns: copy-pasting AI outputs without scrutiny is a real problem, and treating chatbots as friends, or worse, as oracles, can be dangerous, but to equate this with...

Image By Seanbatty (Pixabay) According to Encyclopedia Britannica , artificial intelligence (AI) can be defined as: "The ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. The term is frequently applied to the project of developing systems endowed with the intellectual processes characteristic of humans, like the ability to reason, discover meaning, generalize, or learn from previous experiences." By now, we have all heard about how AI can make it possible for computers, machines and other electronic devices to perform increasingly complex and human-like tasks. As all this sounds almost like magic, with machines performing increasingly complex tasks —from new gaming computers to self-driving cars – in reality most of AI technologies rely on the blend of software methods and technologies that imply collecting, processing and recognizing patterns within large amounts of data. So, how does AI W...

Many things have been said and done in the realm of analytics, but visualizations remain as the forefront of the data analysis process, where intuition and correct interpretation can help us make sense of data. As an increasing number of tools emerge, current visualizations are far more than mere pictures in a screen, allowing for movement, exploration and interaction. One of this tools is D3 , an open-source Javascript data visualization library. D3 is perhaps the most popular tool to develop rich and interactive data visualizations, used by small and large companies such as Google and the New York Times. With the next Open Data Science Conference in Boston coming soon, we had the opportunityto talk with DataRobot’s and ODSC speaker Morgane Ciot about her workshop session: “ Intro to 3D ”, the state of data visualization and her very own perspectives around the analytics market. Morgane Ciot is a data visualization engineer at DataRobot , where she specializes in creating...