Today, Egypt’s AI builders gathered in the Grand Egyptian Museum for a reception that highlighted the nation’s rapidly growing AI ecosystem — spanning AI natives, developers, researchers, startups and enterprises — building applications across industries. The event included a keynote from Paolo Guglielmini, vice president of EMEA at NVIDIA. Ahmed Mostafa, regional AI adoption lead

Just a few years ago, large language models, or LLMs, seemed above all to be extraordinary tools for working with text: writing, summarizing, translating, and answering questions. Then they learned to understand and generate images, sounds, and video. They gained the ability to tackle increasingly complex problems through forms of reasoning, to use external tools

This week two conversations about AI safety went viral that demonstrate just how hard it is to discern AI fact from fiction. In the first case, Andrew Yang, the former presidential candidate and current CEO of mobile carrier Noble Moble, told CNN on Thursday that he had “met with the head of a lab” who

At first glance, a patent draft produced by generative AI in minutes can feel complete enough to file. But patents are not judged at the moment of creation; they are tested later, when they become commercially important and someone starts actively looking for ways to challenge or invalidate them. As AI reduces the cost and

Editorial Note: The visual figures embedded in this article are conceptual diagrams created to intuitively illustrate the geometric and mathematical principles established in the cited MIT research [3], rather than figures taken directly from the original publications For the past decade, the dominant heuristic in artificial intelligence has been straightforward: bigger models yield smarter behavior

What if the traditional financial analyst, reliant on linear heuristics and manual data synthesis, has become a relic of a bygone era? You’ve likely seen the influx of generic marketing claims regarding AI-powered portfolios, yet the persistent confusion between simple automation and deep learning remains a significant barrier for the modern investor. It’s understandable to

Abstract The rapid development of AI-based products and their underlying models has led to constant innovation in deep learning frameworks. Google has been pioneering machine learning usage across dozens of products. Maintaining the multitude of model source codes in different ML frameworks and versions is a significant challenge. So far the maintenance and migration work

The Hariri Institute for Computing at Boston University has named Boston University alumni Mona Jalal as the new lead of its Data Science Mentoring Circles Program (DSMC), effective September 2026. Jalal was selected for her passion for mentoring and experience in bridging cutting-edge AI research and real-world engineering. As a Computer Vision Research Engineer III