Investing in Artificial
Intelligence: A Path for US Leadership
By IAN BUCK, NVIDIA
May 10, 2018
the nation can better prepare its computing infrastructure to meet AI’s
challenges and opportunities.
I am fortunate today to be in
Washington with leaders from three dozen companies, including many of
our close partners, to discuss with administration officials how the
U.S. can continue to lead the world in research, development and the
adoption of artificial intelligence. I’d like to thank the Office of
Science and Technology Policy for convening this important meeting.
AI is becoming the world’s most important computational tool —
applicable to a wide variety of industries including transportation,
energy and healthcare. But AI is enormously demanding in terms of
computation — it requires processing hundreds of millions of data points
to extract insight. Therefore, it’s important for us to discuss how to
improve our nation’s computing infrastructure to support AI and maintain
leadership in this space.
In our meetings, I hope to reiterate some of the themes I shared a few
months ago with the House Subcommittee on Information Technology — that
we need to increase funding for research, give university researchers
access to GPU computing clusters, open access to datasets, and train
more AI developers and data scientists.
There’s simply no replacement for the federal government significantly
increasing support for fundamental research to bolster university
research. Funding drives research. Research, in turn, drives innovation,
from startups to multinationals.
Government also has a role in providing the infrastructure to support
research. Universities need access to large-scale, state-of-the art, GPU-accelerated
computing systems to do cutting-edge research. But most lack the
expertise to procure and run them. The government should provide better
access to universities for future computing systems — all of which need
to support high performance computing and AI workloads.
Data is the lifeblood of AI. Developers and researchers need access to
high-quality data. Federal agencies should disclose what datasets are
available, including anonymized healthcare, weather, satellite and
Simulation for Safe Autonomous Vehicles
Safety is essential for autonomous vehicles and it’s our highest
priority. For the U.S. to lead, we need to ensure safety and time to
market. Developing a safe vehicle requires traveling billions of miles,
which is extraordinarily challenging. Computer simulation is an ideal
methodology to test and validate AI for self-driving cars, enabling us
to accelerate development and improve safety under a wide variety of
road and weather conditions.
Simulation together with AI will greatly advance autonomous vehicle
technology to achieve the highest levels of safety. Simulation should be
part of the virtual “drivers test” of autonomous systems. This will help
reduce the terrible toll of 37,000 American fatalities each year.
often have different regulations for transportation infrastructure. The
federal government should make recommendations for all 50 states to
share unified autonomous vehicle guidelines and smart infrastructure,
including street lights, sensors and construction zones.
The government should partner with industry to train more developers and
data scientists. Academia can’t do this by itself. NVIDIA trains tens of
thousands of developers and data scientists each year, partnering with
educational leaders such as Coursera and Udacity.
In my recent testimony before Congress, I said that AI represents the
biggest technological and economic shift in our lifetime. The stakes are
huge — trillions of dollars in opportunity for American companies, and
life-saving breakthroughs. I look forward to continuing to work with our
partners in Washington and throughout the country to strengthen our
leadership, foster innovation and drive advances that will lead us to a