As organizations weave AI into more of their operations, senior executives are realizing data engineers hold a central role in bringing these initiatives to life. After all, AI only delivers when you have large amounts of reliable and well-managed, high-quality data. Indeed, this report finds that data engineers play a pivotal role in their organizations…
This article originally appeared on Medium. Tim O’Brien has given us permission to repost here on Radar. One of the most unexpected changes in software development right now comes from code generation. We’ve all known that it could speed up certain kinds of work, but what’s becoming clear is that it also reshapes the economics…
On Oct. 20 during its annual meeting, the National Academy of Medicine announced the election of 100 new members, including MIT faculty members Dina Katabi and Facundo Batista, along with three additional MIT alumni. Election to the National Academy of Medicine (NAM) is considered one of the highest honors in the fields of health and…
This article is part of a series on the Sens-AI Framework—practical habits for learning and coding with AI. A few decades ago, I worked with a developer who was respected by everyone on our team. Much of that respect came from the fact that he kept adopting new technologies that none of us had worked…
It’s late August in Rwanda’s capital, Kigali, and people are filling a large hall at one of Africa’s biggest gatherings of minds in AI and machine learning. The room is draped in white curtains, and a giant screen blinks with videos created with generative AI. A classic East African folk song by the Tanzanian singer…
When it comes to artificial intelligence, MIT and IBM were there at the beginning: laying foundational work and creating some of the first programs — AI predecessors — and theorizing how machine “intelligence” might come to be. Today, collaborations like the MIT-IBM Watson AI Lab, which launched eight years ago, are continuing to deliver expertise…
This is the second of a three-part series by Markus Eisele. Part 1 can be found here. Stay tuned for part 3. Many AI projects fail. The reason is often simple. Teams try to rebuild last decade’s applications but add AI on top: A CRM system with AI. A chatbot with AI. A search engine…
Chatbots today are everything machines. If it can be put into words—relationship advice, work documents, code—AI will produce it, however imperfectly. But the one thing that almost no chatbot will ever do is stop talking to you. That might seem reasonable. Why should a tech company build a feature that reduces the time people spend…
In the modern enterprise, information is the new capital. While companies pour resources into artificial intelligence, many discover that technology, standing alone, delivers only expense, not transformation. The true engine of change lies not in the algorithm but in the hands and minds of the people who use it. The greatest asset an organization possesses…
It’s hard to keep up with the ever-changing trends of the fashion world. What’s “in” one minute is often out of style the next season, potentially causing you to re-evaluate your wardrobe. Staying current with the latest fashion styles can be wasteful and expensive, though. Roughly 92 million tons of textile waste are produced annually, including…