Artificial Intelligence

The global AI chip shortage is driving up technology costs, reshaping industries, and increasing demand for a new generation of engineers with expertise in AI hardware and semiconductor design.

AI is transforming the job market, yet 70% of organizations struggle to find skilled talent. For STEM students and early-career professionals, this gap represents a major opportunity.

As artificial intelligence becomes increasingly integral to products developed across healthcare, finance, education, and consumer technology, the skills, relationships, and decisions that define product management are being rewritten.

When the AI surge hit, many companies rushed to replace workers with automation, but a growing rehiring trend is bringing back human employees after AI failed to deliver expected results, and organizations are finding more value in human-AI collaboration versus replacing human work entirely.

While the tools running the internet's backbone today are largely open-source licensed, the debate between open-source and proprietary software continues as both have a meaningful place in the evolving future of computing.

A thought experiment turned viral essay asks what happens when AI boosts company profits but reshapes the workplace and demand, depicting a near-future impacted by AI doom loops and ghost GDP and what it could mean for workers and income growth.

For this year’s tax season, the IRS is leaning heavily on technology to fill the ever-growing tax gap, with artificial intelligence now powering audit selection, fraud detection, taxpayer services, and more.

Google is redefining the way people discover and buy products online with the introduction of its new Gemini AI-powered shopping.

Computer science is one of the most dynamic, in-demand fields in today’s technology-driven world, with career openings expected to increase by 12 percent by 2028. To succeed in this competitive industry, however, professionals must master a blend of technical expertise and management skills through tailored, industry-focused education.

Connecting AI models with external tools and data has been a longstanding challenge until the development of the Model Context Protocol (MCP). But due to its universal interface, the MCP security posture presents a major vulnerability issue, making it susceptible to cyberattacks and exploitation.