Elon Musk’s AI company, xAI, is in hot water after being hit with a lawsuit alleging it misled investors and regulators about its use of gas-burning turbines to power its data centers. The plaintiffs claim the company downplayed the environmental impact while touting its green credentials.

Editor’s Note: This isn’t just about turbines—it’s a test case for how tech giants balance AI’s massive energy demands with their climate pledges. If the allegations stick, it could force more transparency (or backlash) around the hidden environmental costs of cutting-edge tech.

Microsoft just turbocharged weather forecasting with its new AI model, Aurora. It outperformed current systems in 91% of cases when predicting hurricanes, sandstorms, and ocean patterns up to two weeks out—and does it 5,000 times faster. Imagine getting life-saving storm warnings almost instantly instead of waiting hours.

This piece dives into the evolving world of drone warfare, comparing how Iran, Ukraine, and the U.S. are using swarms of autonomous drones to change the game. Iran’s Shahed drones, Ukraine’s nimble quadcopters, and America’s Golden Horde program each showcase different approaches to massed drone attacks—and they’re forcing militaries worldwide to rethink air defense strategies.

A UK biotech company has spent years compiling a massive genetic database, uncovering a million new microbial species and billions of previously unknown genes. Now, they’re trying to use that data to build an AI system that could revolutionize biology—think of it as a "ChatGPT for life sciences." But here’s the catch: even with all that data, training an AI to truly understand biology might be a lot harder than they think.

Editor’s Note: This isn’t just another tech moonshot—it’s a bold attempt to merge cutting-edge AI with the messy, unpredictable world of biology. If it works, it could accelerate drug discovery, environmental science, and even our understanding of life itself. But the story also highlights a sobering reality: biology is complicated, and even mountains of data might not be enough to crack its secrets. For anyone interested in where AI meets real-world science, this is a fascinating case study in ambition versus reality.

A team of researchers used AI to generate a striking new image of the supermassive black hole at the center of our galaxy, but not everyone’s convinced it’s the breakthrough it seems. A Nobel Prize-winning scientist is pushing back, warning that AI isn’t a magic solution—it might be filling in gaps with guesswork rather than revealing true cosmic details.