Before we get to the headline story, some background. Tesla and Nvidia have a history.
In 2015 - 2016 when everyone thought that autonomous driving was just around the corner, the challenge was seen as both a sensor issue, for example: LIDAR vs cameras, and a machine learning/artificial intelligence problem which boils down to training the AI 'puters with as much data as you can so that out in the real world the autonomous vehicle can say to itself: "Yeah, I've seen this situation before, here's the response that worked best. Both the training and the on-the-road-recall, if they are to be anywhere near efficient, require the fastest chips you can find. Tesla had a whole bunch of data from a few billion miles of actual driving for computers to train on, and, combined with Nvidia's fastest-in-the-world GPU chips, it was a match made in heaven.
Except it wasn't.
The challenge of autonomous driving on open roads alongside non-autonomous vehicles was bigger than anyone in that simple, optimistic time ever envisioned, even in their nightmares. Here's one example about Waymo from a 2017 post:
"When Google was training its self-driving car on the streets of Mountain View, California, the car rounded a corner and encountered a woman in a wheelchair, waving a broom, chasing a duck. The car hadn’t encountered this before so it stopped and waited."
In May 2015 we were posting " Nvidia Wants to Be the Brains Of Your Autonomous Car (NVDA)" and seven months later the more declarative "Class Act: Nvidia Will Be The Brains Of Your Autonomous Car (NVDA)"
Then in October 2016, what was probably the high-water mark for the relationship "Nvidia Could Make $1B From Tesla's Self-Driving Decree: Analyst (TSLA, NVDA)"
Sadly, the task was just too difficult but Mr. Musk thought it was doable if only he could get even faster chips than Nvidia had on offer:
NVIDIA Partner Tesla Reportedly Developing Chip With AMD (TSLA; NVDA; AMD)
Today in leveraged WTFs....
The only reason for Tesla to do this is that NVIDIA's chips are general purpose whereas specialized chips are making inroads in stuff like crypto mining (ASICs), Google's Tensor Processing Units (TPUs) for machine learning and Facebook's hardware efforts.
We've said NVIDIA probably has a couple year head start but this bears watching, so to speak....
Culminating in August 2018's
"Nvidia CEO is 'more than happy to help' if Tesla's A.I. chip doesn't pan out" (NVDA; TSLA)
And now on to the headliner, from Observer, June 8:
There are only a handful of companies in the world worth more than $1 trillion, and semiconductor maker Nvidia recently became one of them, joining the ranks of Apple, Microsoft, Alphabet, Amazon and Saudi Arabia’s state-owned oil producer Saudi Aramco.
Nvidia’s stock price has skyrocketed 165 percent this year, largely thanks to the booming sales of computer chips that power artificial intelligence applications like ChatGPT. Nvidia, a leading manufacturer of graphics processing units (GPUs), is believed to have a virtual monopoly in the A.I. computing market. But Elon Musk, a co-founder of ChatGPT creator OpenAI, believes Nvidia’s dominance won’t last as newer types of chips arrive in the market.
“Many other NN accelerator chips are also under development. Nvidia will not have a monopoly on large-scale training and inference forever,” Musk tweeted yesterday (June 7) in response to a post by Adam D’Angelo, CEO of Quora, a social platform for questions and answers.
The “NN accelerator” Musk mentioned stands for “neural network accelerators,” also known as A.I. accelerators....
....MUCH MORE
