The bond market is showing signs of anxiety over Big Tech’s enormous AI spending plans. Companies like Meta, Alphabet, and Oracle are issuing massive debt packages despite sitting on huge cash reserves, raising concerns about overcapacity and long-term profitability.
Google continues expanding its Gemini AI ecosystem with a new rollout for Google TV Streamer. The voice-controlled assistant can suggest content based on viewer preferences and provide context about what’s playing. This follows Google’s broader push to integrate Gemini across its hardware products.
AI systems are revealing leadership gaps across industries, from pricing disasters to compliance failures. The most valuable skill now isn’t technical fluency—it’s taking ownership of automated decisions. Boards are being forced to treat AI as enterprise risk rather than just technology.
Wikipedia’s nonprofit foundation wants AI companies to stop scraping its data and pay for API access instead. Running the world’s seventh-most visited site costs $179 million annually, supported mainly by donations that AI chatbots could disrupt.
Google is rolling out new AI-powered tools for Google Maps that let developers create interactive projects using natural language. The features include a builder agent that generates code from text descriptions and an MCP server for accessing Maps documentation. These tools are powered by Gemini mod
New studies show multimodal AI can predict cancer treatment outcomes better than current methods. The technology combines medical images, clinical notes and tumor biology to spot patterns humans miss. Several companies are already bringing these tools closer to real-world use.
The S&P 500 has nearly doubled in five years to 6,700, driven by the Magnificent 7 tech giants placing trillion-dollar AI bets. Meanwhile, gold, Bitcoin, and even junk bonds are soaring as if nothing can go wrong. This simultaneous optimism and fear has investors wondering if a reckoning is coming.
The AI boom is creating an environmental crisis that tech companies aren’t prepared for. New forecasts show massive water and energy demands that will make 2030 net zero targets impossible to meet.
As companies consider replacing expensive engineers with AI coding tools, recent high-profile failures demonstrate why this approach is dangerously premature. From deleted production databases to catastrophic security breaches, the limitations of current AI coding capabilities are becoming painfully
The AI landscape is transforming from simple chatbots to sophisticated agents that can actually think and do. With companies projected to spend over $400 billion on AI this year, we’re witnessing a fundamental shift in how technology integrates with human work. The next decade will see software evol
