$BARD $SOPH $NVDA Is the man in the black leather jacket really about to step down? The golden age of AI computing dominance may be quietly turning the page! 🧥⚡ Without Jensen Huang, the AI wave we're riding today might have taken several more years to arrive.

These past few days, rumors about Huang's next move have been spreading like wildfire through the tech and crypto worlds. Honestly, I have mixed feelings. Many people have only seen computing power skyrocket over the past two years, with AI stocks and related tokens flying everywhere, but they've forgotten that this was built on thirty years of relentless dedication.

Let's rewind to 1999, when GPUs were just born. In 2006, Huang went against the consensus and bet on the CUDA ecosystem. Back then, hardly anyone on Wall Street understood it; some even thought he was burning money on a pointless endeavor. It wasn't until deep learning exploded in 2012 that everyone realized this guy had already built the highway to the AI era! 🛤️

NVIDIA has been around for thirty-three years, and Jensen Huang has been its leader from beginning to end. In Silicon Valley, where executives frequently jump from one company to another, that's practically a miracle.

At every developer conference, watching him take the stage in his signature black leather jacket and unveil the next generation of graphics cards like a rock star—his sheer passion for technology and confidence have certainly fueled the wild narrative around hardware and decentralized computing. 🔥

If that familiar figure really does set down his burden, it would be an irreplaceable loss for the history of technology. Future launches just won't feel quite the same without that black leather jacket; it would be like something was missing.

The industry goes on, and the story of computing power will continue to unfold. But the chapter in which Jensen Huang single-handedly defined an era seems truly about to come to a close. Salute to a legend. How do you think the computing landscape will shift next? 👇💬#黄仁勋辞任CEO,英伟达战略走向受关注