"I thought it was incredibly appropriate that the world's first supercomputer dedicated to artificial intelligence would go to the laboratory that was dedicated to open artificial intelligence", Jen-Hsun Huang stated.
OpenAI's researchers will put the first production DGX-1 - packing 170 teraflops of computing power, equal to 250 conventional servers - to work on artificial intelligence's toughest problems.
OpenAI's team is working at the cutting-edge of a field that promises incredible advances. Imagine artificial personal assistants that can coordinate our digital lives and autonomous cars and robots that are accessible to everyone.
Doing that will take technology with the computing power to keep up with OpenAI's researchers. Building DGX-1 took 3,000 people working for three years, Jen-Hsun Huang explained. "So if this is the only one ever shipped, this project would cost $2 billion", he stated.
OpenAI's researchers are eager to put it to work.
"The DGX-1 is a huge advance", OpenAI Research Scientist Ilya Sutskever stated. "It will allow us to explore problems that were completely unexplored before, and it will allow us to achieve levels of performance that werent achievable."
OpenAI - already hailed by some as the "Xerox PARC of AI" - was founded last year to advance digital intelligence in ways that will benefit all humanity.
"Artificial intelligence has the potential to be the most positive technology that humans ever create", stated OpenAI Chief Technology Officer Greg Brockman. "It has the potential to unlock the solutions to problems that have really plagued us for a very long time."
One of the keys to tackling these challenges is what OpenAI's researchers call "generative modelling". If a machine is smart enough to not just recognize speech - but to use that data to generate appropriate responses on its own - then it will behave more intelligently.
"You can take a large amount of data that would help people talk to each other on the internet, and you can train, basically, a chatbot, but you can do it in a way that the computer learns how language works and how people interact", stated OpenAI Research Scientist Andrej Karpathy.
The key to all this: speed. Researchers today are limited by the computational power in their systems.
"Our advances depend on GPUs being fast. Speed of our computers is, in some sense, the lifeblood of deep learning", Ilya Sutskever stated.
"One very easy way of always getting our models to work better is to just scale the amount of compute", Andrej Karpathy stated. "So right now, if we're training on, say, a month of conversations on Reddit, we can, instead, train on entire years of conversations of people talking to each other on all of Reddit."
"And then we can get much more data in terms of how people interact with each other. And, eventually, we'll use that to talk to computers, just like we talk to each other."
Projects like these are the reason why NVIDIA built DGX-1, and why NVIDIA will be delivering DGX-1s to top AI research teams all over the world in the weeks ahead.