It’s about making the lives of scientists and researchers easier, Jensen Huang, CEO and co-founder of Nvidia tells TechCrunch. He’s speaking of the keynote address he intends to give at the company’s upcoming GTC conference. Held in San Jose, miles away from the company’s new imposing headquarters, Nvidia is set to host thousands of attendees from the world’s top artificial intelligence, automotive and gaming companies. To Huang, his address needs to inspire and entertain. That should be easy. He’s naturally inspiring and entertaining.
Huang has risen to the elite among Silicon Valley’s visionary leaders. Scores of reports show Nvidia employees love working for him and his addresses are often technical yet accessible. He commands an audience through his passion for the technology his company is creating.
He’s been at the helm of Nvidia since co-founding the company at age 30 in 1993 and has led Nvidia from the maker of computer graphics cards to become the premier platform for artificial intelligence and machine learning. This positions Nvidia at the forefront as the computing industry contemplates a fundamental shift in processing.
Nvidia saw it coming.
In 2008 and 2009 researchers started using GPUs made by Nvidia and AMD to handle work typically performed by microprocessors. The parallel computing processors built into graphics cards made by these two companies offered distinct advantages over the X86 platform championed by Intel. At the time Nvidia was pushing hard into mobile and computing graphics, but several years earlier the company started heavily investing in designing graphics chips to handle non-graphical functions. The industry noticed, and Nvidia made a play for supercomputers.
Now, nearly ten years later, Nvidia’s products are among the fastest and most efficient supercomputing platforms available. Nvidia is set to, literally, power the computing world.
“We’ve been pioneering this computing approach called GPU computing for over the last decade,” Jensen said. “Over the last seven or eight years, it really went into turbo charge because the model is perfect for artificial intelligence.”
Read the source article at TechCrunch.com.