Micron crashes the trillion-dollar club; Google's brain drain deepens

Micron posted fiscal third-quarter revenue of $41.5 billion, up 346 percent from a year ago, with profit jumping to $28.2 billion — and its shares spiked enough on June 25 to briefly vault its market value past Meta and Tesla, near $1.4 trillion. The surge reflects a broader shift: high-bandwidth memory has become the scarcest part of an AI server, and Micron is one of only three suppliers that can make it at scale. Wall Street analysts are now openly asking whether the memory maker is the next Nvidia.

Google has now lost four senior AI researchers in roughly a week — the clearest sign yet that rivals are picking off the people who built Gemini. Transformer co-author Noam Shazeer is heading to OpenAI, while AlphaFold Nobel laureate John Jumper and two more Gemini contributors are going to Anthropic. Jumper's exit alone helped wipe $245 billion off Alphabet's market value in a single session. The departures revive a pointed question for the AI race: can Google DeepMind stay at the frontier while its rivals keep hiring away its core talent?

A new SemiAnalysis analysis argues the US grid simply cannot add capacity fast enough for AI. Data-center demand is set to climb from 21 gigawatts in 2026 to 84 gigawatts by 2030, while net-new firm capacity is barely 15 gigawatts a year — turning available headroom negative across several regions by 2027. The firm projects that behind-the-meter generation — power plants built on-site, bypassing the grid — will supply well over half of new US data centers from 2028 on, because gas-turbine and interconnection lead times now stretch four to six years and on-site power is both faster and more certain.

Ford has rehired about 350 veteran engineers — some retirees, some pulled from suppliers — after concluding that automated, AI-driven quality systems were not catching defects well enough on their own. The 'gray beard' specialists spot failure points before parts reach the plant floor, retrain younger staff, and reprogram the AI tools. One executive admitted the company had wrongly assumed that 'just introducing artificial intelligence' would produce a high-quality product. The reversal helped Ford top J.D. Power's initial-quality ranking among mainstream brands and cut hundreds of millions in warranty and recall costs.

Patronus AI, founded by two former Meta AI researchers, closed a $50 million Series B and launched Digital World Models — large simulated environments that throw realistic failure conditions at AI agents before those agents touch real systems. As companies hand agents access to live tools and data, the bet is that they will pay to catch costly mistakes in a sandbox first. Patronus says its customers already include most frontier labs and hyperscalers, and its revenue grew more than fifteenfold over the past year.