The chipmaker’s prospects look bright. Its AI business is growing fast, through specialised chips and the advanced software that lets programmers fine-tune them
“WE’RE ALWAYS 30 days away from going out of business,” is a mantra of Jen-Hsun Huang, co-founder of Nvidia, a semiconductor company. That may be a little hyperbolic coming from the boss of a company whose market value has increased from $31bn to $486bn in five years and which has eclipsed Intel, once the world’s mightiest chipmaker, by selling high-performance chips for gaming and artificial intelligence . But only a little.
Now Mr Huang wants to make it broader and deeper still. In September Nvidia confirmed rumours that it was buying Arm, a Britain-based firm that designs zippy and energy-efficient chips for most of the world’s smartphones, for $40bn. The idea is to use Arm’s design prowess to engineer central processing units for data centres and AI uses that would complement Nvidia’s existing strength in specialised chips known as graphics-processing units .
But the AI business is growing fast . It includes specialised chips as well as advanced software that lets programmers fine-tune them—itself enabled by an earlier bet by Mr Huang, which some investors criticised at the time as an expensive distraction. In 2004 Mr Huang started investing in “Cuda”, a base software layer that enables just such fine-tuning, and implanting it in all of Nvidia’s chips.
Today its AI hardware-software combo is designed to work seamlessly with the machine-learning algorithms collected in libraries such as TensorFlow and PyTorch , boosting the algorithms’ number-crunching power. Nvidia has created programs to hook its hardware and software up to the IT systems of big business customers with AI projects of their own. All this makes AI developers’ job immeasurably easier, says a former Nvidia executive.
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