The U.S. government’s CTO and CIO on Tuesday joined other key tech decision makers, lawmakers, and industry leaders at the start of the two-day GPU Technology Conference in Washington D.C.

Federal CIO Suzette Kent led a panel of civilian agency leaders explaining how they’re using AI.  Moments later, U.S. CTO Michael Kratsios led a discussion of how the federal government is supporting U.S. AI leadership.

And Moira Bergin, the House Committee on Homeland Security’s subcommittee director for cybersecurity and infrastructure protection, joined a discussion of how Congress and the administration are addressing new AI cybersecurity capabilities.

The talks were among the more than 160 sessions — led by a cross-section of Washington  leaders from government and industry — that have drawn more than 3,500 to downtown D.C. this week.

GTC DC — hosted by NVIDIA and its partners, including Booz Allen Hamilton, Dell, IBM, Lockheed Martin and others — has quickly become the capital’s largest AI event. And it’s research, not rhetoric, attendees will tell you, that makes DC an AI accelerator like no other.

The conference is packed with representatives from more than a score of federal agencies — among them the U.S. Department of Energy, NASA, and the National Institutes of Health — together able to marshal scientific efforts on a scale far beyond that of anywhere else in the world.

Putting AI to Work

The conference opened with a keynote from Ian Buck, NVIDIA’s vice president for accelerated computing.

Buck — known for creating the CUDA computing platform that puts GPUs to work powering everything from supercomputing to next-generation AI — detailed the broad range of AI tools NVIDIA makes available to help organizations advance their work.

“The challenge is how do we take AI from innovation to actually applying AI,” Buck said during his keynote address Wednesday morning. “Our challenge, NVIDIA’s challenge, and my challenge is ‘How can I bring AI to industries and activate it?’”

Buck’s message was buttressed by Kent, who led a panel of civilian agency leaders discussing how they’re using AI to improve government services.

“We’re using these AI capabilities to act faster,” Kent said. “In the areas where we’re keeping citizens safe, whether it’s reacting to weather or a problem caused by humans — the speed at which we help is increasing.”

Meanwhile, Kratsios led a discussion about how the U.S government — which has a decades long history of supporting key technology advances — is working to extend U.S. technology leadership in the AI age.

“We fundamentally believe that AI is something that’s going to touch every industry in the United States,” Kratsios said. “We view artificial intelligence as a tool that can empower workers to do their jobs better, safer, faster, and more effectively.”

Wrapping up the day, the House’s Bergin joined Coleman Mehta, senior director of U.S. policy at Palo Alto Networks; Daniel Kroese, associate director of the national risk management center at the Cybersecurity and Infrastructure Security Agency; and Joshua Patterson, GM of data science at NVIDIA.

In a panel moderated by NVIDIA’s  Iain Cunningham, VP of intellectual property and cybersecurity, the four spoke about the new AI capabilities, potential countermeasures, and preparations being made by the administration and Congress.

Bergin said she’s “excited” about the prospects for AI after what she described as a decade of underinvestment in R&D.

“There’s a lot of demystification that needs to happen about what AI actually is, what it’s capabilities are now, and what its capabilities will be later,” Bergin said.

Scores more discussions are slated through Wednesday afternoon.

Underscoring the role AI can play for good, speakers from the Johns Hopkins University Applied Physics Laboratory and the Joint AI Center will discuss how they’re harnessing AI to provide humanitarian assistance and disaster relief.

Expect their discussion — of how they harnessed airborne and satellite imagery data after Hurricane Florence hit North and South Carolina in 2018 — to point the way to more groundbreaking AI feats to come.

The post U.S. Government CTO, CIO Among Leaders Flocking to GTC DC appeared first on The Official NVIDIA Blog.

The U.S. government’s CTO and CIO on Tuesday joined other key tech decision makers, lawmakers and industry leaders at the start of the two-day GPU Technology Conference in Washington, D.C.

U.S. CTO Michael Kratsios gave the conference’s policy day keynote on how the federal government is supporting U.S. AI leadership. And Federal CIO Suzette Kent led a panel of civilian agency leaders explaining how they’re using AI.

Another highlight: a panel on national AI strategy featuring Lynne Parker assistant director for AI with the White House Office of Science and Technology and National Security AI Commissioner Jason Matheny.

The talks were among the more than 160 sessions — led by a cross-section of Washington  leaders from government and industry — that have drawn more than 3,500 to downtown DC this week.

GTC DC — hosted by NVIDIA and its partners, including Booz Allen Hamilton, Dell, IBM, Lockheed Martin and others — has quickly become the capital’s largest AI event. And it’s research, not rhetoric, attendees will tell you, that makes DC an AI accelerator like no other.

The conference is packed with representatives from more than a score of federal agencies — among them the U.S. Department of Energy, NASA and the National Institutes of Health — together able to marshal scientific efforts on a scale far beyond that of anywhere else in the world.

Putting AI to Work

The conference opened with a keynote from Ian Buck, NVIDIA’s vice president for accelerated computing.

Buck — known for creating the CUDA computing platform that puts GPUs to work powering everything from supercomputing to next-generation AI — detailed the broad range of AI tools NVIDIA makes available to help organizations advance their work.

“The challenge is how do we take AI from innovation to actually applying AI,” Buck said during his keynote address Tuesday morning. “Our challenge, NVIDIA’s challenge and my challenge is ‘How can I bring AI to industries and activate it?’”

Buck then joined Kratsios for a discussion about how the U.S. government — which has a decades-long history of supporting key technology advances — is working to extend U.S. technology leadership in the AI age.

“We fundamentally believe that AI is something that’s going to touch every industry in the United States,” Kratsios said. “We view artificial intelligence as a tool that can empower workers to do their jobs better, safer, faster and more effectively.”

Kratsios’s points were buttressed by the speakers on the national AI strategy panel — which included Parker and Matheny — discussing the progress of the U.S. government’s national AI strategy.

They touched on the federal government’s ongoing investment in R&D, obtaining and training the highest quality talent, and implementation of AI across the federal government.

As part of that, Parker, invited listeners to participate in the 30-day public comment period in following the draft release of draft guidance on facilitating industry AI adoption from the U.S. Office of Management and Budget’s Office of Information and Regulatory Affairs.

Kent who is leading federal AI adoption efforts, participated in a discussion about advancing AI adoption across the federal government, as part of a panel of civilian agency leaders.

“We’re using these AI capabilities to act faster,” Kent said. “In the areas where we’re keeping citizens safe, whether it’s reacting to weather or a problem caused by humans — the speed at which we help is increasing.”

Wrapping up the day, Moira Bergin, the House Committee on Homeland Security’s subcommittee director for cybersecurity and infrastructure protection, joined a discussion of how Congress and the administration are addressing new AI cybersecurity capabilities.

Bergin joined Coleman Mehta, senior director of U.S. policy at Palo Alto Networks; Daniel Kroese, associate director of the national risk management center at the Cybersecurity and Infrastructure Security Agency; and Joshua Patterson, general manager of data science at NVIDIA.

Bergin said she’s “excited” about the prospects for AI after what she described as a decade of underinvestment in R&D.

“There’s a lot of demystification that needs to happen about what AI actually is, what it’s capabilities are now and what its capabilities will be later,” Bergin said.

Scores more discussions took place throughout the conference, including packed discussions discussions policies to speed adoption of AI in healthcare and building an inclusive AI workforce across the country.

Underscoring the role AI can play for good, speakers from the Johns Hopkins University Applied Physics Laboratory and the U.S. Department of Defense’s Joint Artificial Intelligence Center will discuss how they’re harnessing AI to provide humanitarian assistance and disaster relief.

Expect their discussion — of how they harnessed airborne and satellite imagery data after Hurricane Florence hit North and South Carolina in 2018 — to point the way to more groundbreaking AI feats to come.

The post US Government CTO, CIO Among Leaders Flocking to GTC DC appeared first on The Official NVIDIA Blog.

Doina Precup is applying Romanian wisdom to the gender gap in the fields of AI and computer science.

The associate professor at McGill University and research team lead at AI startup DeepMind spoke with AI Podcast host Noah Kravitz about her personal experiences, along with the AI4Good Lab she co-founded to give women more access to machine learning training.

Growing up in Romania, Precup attended a high school that specialized in computer science and a technical university. She didn’t experience gender disparity in these learning environments.

“If anything, programming was considered a very good job for women, because you did not need to be working in the fields,” she explained.

It made the gap in Canadian universities and companies even more noticeable. At McGill, Precup saw that female students were hesitant to speak up or pursue graduate studies.

Together with Angelique Mannella, CEO of AM Consulting and an Amazon employee, Precup was inspired to start the AI4Good Lab in 2017.

Key Points From This Episode:

• Aimed at improving women’s access to advanced AI and machine learning, the AI4Good Lab brings together 30 women from across Canada every spring for a seven-week workshop
• Workshop participants take classes, hear from speakers, visit companies and work in small groups to create projects.
• This year’s projects ranged from identifying fake news to using a caf ’s food supplies efficiently to helping people manage chronic pain.
• To hear Precup’s best sci-fi book recommendations, listen to the podcast for her guide to the genre.
• Visit the AI4Good Lab website or Twitter to learn more about participants’ projects and to apply to next year’s workshop. And visit Precup’s Google Scholar page to see her most recent publications.

Tweetables:

“Emphasizing the creativity and the fun in computer science and algorithms is really important, for everybody” — Doina Precup [04:30]

“I also noticed that people were sometimes afraid to speak up in classes, even if they were really good at based on their exams and their assignments and their projects” — Doina Precup [05:43]

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The post AI4Good: Canadian Lab Empowers Women in Computer Science appeared first on The Official NVIDIA Blog.

The AI revolution is here — as near as the closest mailbox — and the time’s right to put AI to work solving your organization’s biggest challenges, NVIDIA’s Ian Buck said Tuesday.

Kicking off the Washington edition of our GPU Technology Conference, Buck, NVIDIA’s VP for accelerated computing, detailed a new generation of technologies that will help companies put modern AI to work.

Buck also announced that the United States Postal Service — the world’s largest delivery service, with 146 billion pieces of mail processed and delivered annually — is adopting end-to-end AI technology from NVIDIA.

“The challenge is how do we take AI from innovation to actually applying AI,” Buck told an audience of more than 3,500 developers, CIOs and federal employees at the three-day GTC DC. “Our challenge, NVIDIA’s challenge, and my challenge is ‘How can I bring AI to industries and activate it.’”

Over the course of his hour-long talk, Buck explained how modern AI is trained and deployed, and described how NVIDIA is adapting AI for the automotive, healthcare, robotics, and 5G industries, among others.

The U.S. Postal Service offers a glimpse at what’s possible.

Buck said the U.S. Postal Service will roll out a deep learning solution based on NVIDIA EGX to 200 processing facilities that should be operational in 2020.

Using EGX, Buck said, the USPS will be able to process packages 10 times faster with higher accuracy and enhance its ability to detect hazardous parcels.

“We’re very excited to see a U.S. agency really leaning into AI, they have a cool problem, processing your mail as quickly as possible, and by working with NVIDIA they’re accelerating that work,” Buck said.

A Day in the Life of AI

Buck, known for creating the CUDA computing platform while still a Stanford student, detailed how NVIDIA’s technologies accelerate every step in the process of putting AI to work from data ingestion, to AI training, and, ultimately, deployment. The next step will be the creation of vertical AI platforms that experts in a wide variety of industries will be able to put to work fast, Buck said.

In healthcare, workers are being inundated with data. A typical radiology department views 8,000 images a day. Three papers per minute are published on the PubMed medical research hub, Buck said.

Buck detailed how the NVIDIA Clara software development kit is able to use a new generation of transfer learning models to help healthcare workers quickly adapt by augmenting an existing pre-trained model to tackle new tasks, such as looking for a particular kind of cancer, in minutes or hours, while using less training data.

Telecommunications is another industry that can benefit from AI as it races to adopt 5G wireless technology. Compared to today’s 4G networks, 5G allows you to download an entire season of “Stranger Things” in just three minutes on a mobile device, compared to three hours. 5G is more responsive, with 1 millisecond of latency, versus 10 milliseconds for 4G. It’s ultra-reliable.

“It is a revolution, and I don’t use that word lightly,” Buck said. “It gives us the opportunity to send enormous streams of data and respond in real time,” Buck said.

To help telcos and their customers make the most of 5Gs, NVIDIA last month launched the NVIDIA EGX edge supercomputing platform. Scalable and secure, these servers pack as much as many as four NVIDIA CUDA Tensor Core GPUs.

Smart cities can benefit from EGX, too.

Running NVIDIA’s Metropolis Internet of Things application framework as part of a pilot program, public safety officials in Dubuque, Iowa, Metropolis picked out a vehicle driving the wrong way onto a freeway.

Of course, NVIDIA is working to help make cars smarter — safer — too. NVIDIA’s autonomous vehicle platform spans everything from cars to trucks to robo taxis to industrial vehicles.

To enable safe development and deployment NVIDIA’s built an end-to-end workflow to develop autonomous vehicles, including systems for collecting data, curating it, labeling it, training AI, replaying it, and using it to simulate the performance of new systems in all kinds of scenarios.

“This is a much more deeper, richer stack than just traditional inference and training,” Buck said.

Lastly, robots are another area where NVIDIA’s building tools that are unleashing a new wave of innovation. In the past, robots were very good at repetitive tasks. The future of robots, however, “is all about interaction,” Buck said.

These new generation of robots are being put to work in retail, agriculture, and the food delivery business — slated to grow to $100 billion by 2025.

To enable all this, NVIDIA built Jetson, an end-to-end robotics platform that lets companies deploy new kinds of robots more quickly. It includes a complete software stack built on to a range of powerful SoCs, starting with the $99 Jetson Nano.

“This is going to be an exciting time for robotics,” Buck said.

It’s yet another example of how NVIDIA is bringing AI to vertical industries, with NVIDIA Clara for healthcare, NVIDIA Metropolis for smart cities and retail, NVIDIA DRIVE for autonomous vehicles, NVIDIA Omniverse for design and media, and NVIDIA Aerial for telcos.

“What’s going to take it to the next level is vertical platforms that allow the healthcare data scientist or smart city engineer to get access to this technology” Buck said.

It’s an effort that extends to help with workforce training through NVIDIA’s Deep Learning Institute. NVIDIA’s Deep Learning Institute has just added 12 new courses, it’s already trained more than 180,000 AI workers. And it’s available to individuals, teams, and universities.

“My goal and my mission is to help put AI to work not just to do amazing demos but to help industries move to adopt AI,” Buck said.

The post Special Delivery: With U.S. Post Office on Board, NVIDIA to Enable AI Deployment, NVIDIA’s Ian Buck Says appeared first on The Official NVIDIA Blog.

The AI revolution is here — as near as the closest mailbox — and the time’s right to put AI to work solving your organization’s biggest challenges, NVIDIA’s Ian Buck said Tuesday.

Kicking off the Washington edition of our GPU Technology Conference, Buck, NVIDIA’s vice president for accelerated computing, detailed a new generation of technologies that will help companies put modern AI to work.

Buck also announced that the United States Postal Service — the world’s largest delivery service, with 146 billion pieces of mail processed and delivered annually — is adopting end-to-end AI technology from NVIDIA.

“The challenge is how do we take AI from innovation to actually applying AI,” Buck told an audience of more than 3,500 developers, CIOs and federal employees at the three-day GTC DC. “Our challenge, NVIDIA’s challenge, and my challenge is ‘How can I bring AI to industries and activate it?’”

Over the course of his hour-long talk, Buck explained how modern AI is trained and deployed, and described how NVIDIA is adapting AI for the automotive, healthcare, robotics and 5G industries, among others.

The U.S. Postal Service offers a glimpse at what’s possible.

Buck said the USPS will roll out a deep learning solution based on NVIDIA EGX to 200 processing facilities that should be operational in 2020.

Using EGX, Buck said, the USPS will be able to process packages 10x faster with higher accuracy.

“We’re very excited to see a U.S. agency really leaning into AI. They have a cool problem, processing your mail as quickly as possible, and by working with NVIDIA they’re accelerating that work,” Buck said.

A Day in the Life of AI

Buck, known for creating the CUDA computing platform while still a Stanford student, detailed how NVIDIA’s technologies accelerate every step in the process of putting AI to work from data ingestion, to AI training, and, ultimately, deployment. The next step will be the creation of vertical AI platforms that experts in a wide variety of industries will be able to put to work fast, Buck said.

In healthcare, workers are being inundated with data. A typical radiology department views 8,000 images a day. Three papers per minute are published on the PubMed medical research hub, Buck said.

Buck detailed how the NVIDIA Clara software development kit uses a new generation of transfer learning models to help healthcare workers quickly adapt. It augments a pretrained model to tackle new tasks, such as looking for a particular kind of cancer, in minutes or hours, while using less training data.

Telecommunications is another industry that can benefit from AI as it races to adopt 5G wireless technology. Compared to today’s 4G networks, 5G allows you to download an entire season of “Stranger Things” in just three minutes on a mobile device, compared to three hours. 5G is more responsive, with 1 millisecond of latency, versus 10 milliseconds for 4G. It’s ultra-reliable.

“It is a revolution, and I don’t use that word lightly,” Buck said. “It gives us the opportunity to send enormous streams of data and respond in real time,” Buck said.

To help telcos and their customers make the most of 5Gs, NVIDIA last month launched the NVIDIA EGX Edge Supercomputing platform. Scalable and secure, these servers pack as many as four NVIDIA CUDA Tensor Core GPUs.

Smart cities can benefit from EGX, too.

Running NVIDIA’s Metropolis Internet of Things application framework as part of a pilot program, public safety officials in Dubuque, Iowa, picked out a vehicle driving the wrong way onto a freeway.

Of course, NVIDIA is working to help make cars smarter — safer — too. NVIDIA’s DRIVE autonomous vehicle platform spans everything from cars to trucks to robotaxis to industrial vehicles.

To enable safe development and deployment, NVIDIA built an end-to-end workflow to develop autonomous vehicles, including systems for collecting data, curating it, labeling it, training AI, replaying it and using it to simulate the performance of new systems in all kinds of scenarios.

“This is a much more deeper, richer stack than just traditional inference and training,” Buck said.

Lastly, robots are another area where NVIDIA is building tools that are unleashing a new wave of innovation. In the past, robots were very good at repetitive tasks. The future of robots, however, “is all about interaction,” Buck said.

These new generation of robots are being put to work in retail, agriculture and the food delivery business — slated to grow to $100 billion by 2025.

To enable all this, NVIDIA built Jetson, an end-to-end robotics platform that lets companies deploy new kinds of robots more quickly. It includes a complete software stack built onto a range of powerful SoCs, starting with the $99 Jetson Nano.

“This is going to be an exciting time for robotics,” Buck said.

It’s yet another example of how NVIDIA is bringing AI to vertical industries, with NVIDIA Clara for healthcare, NVIDIA Metropolis for smart cities and retail, NVIDIA DRIVE for autonomous vehicles, NVIDIA Omniverse for design and media, and NVIDIA Aerial for telcos.

“What’s going to take it to the next level is vertical platforms that allow the healthcare data scientist or smart city engineer to get access to this technology” Buck said.

It’s an effort that extends to help with workforce training through NVIDIA’s Deep Learning Institute. The DLI has just added 12 new courses, it’s already trained more than 180,000 AI workers. And it’s available to individuals, teams and universities.

“My goal and my mission is to help put AI to work not just to do amazing demos, but to help industries move to adopt AI,” Buck said.

The post Special Delivery: With U.S. Postal Service on Board, NVIDIA to Enable AI Deployment, NVIDIA’s Ian Buck Says appeared first on The Official NVIDIA Blog.

From finding the best sushi near you to improving the manufacturing process of industrial components to making the car you drive safer, AI is advancing convenience, productivity and reliability across industries.

But taking advantage of the power of AI is not feasible without a skilled workforce. In fact, industry research indicates that lack of AI skills is the primary reason companies are unable to achieve business value with AI.

This is why companies and government agencies around the world are swarming the job market to hire developers, data scientists, engineers and researchers with AI expertise. But there just aren’t enough AI-trained developers to meet the demand.

To help bridge that gap, NVIDIA created the Deep Learning Institute in 2016 to train developers with hands-on courses in both fundamental and advanced AI topics. In that time, more than 183,000 students have taken advantage of this program to advance their skills.

Today, DLI is expanding its portfolio with a dozen new courses. Among the instructor-led workshops:

• Deep Learning for Autonomous Vehicles – Perception
• Fundamentals of Accelerated Data Science with RAPIDS 
• Applications of AI for Predictive Maintenance
• Applications of AI for Anomaly Detection
• Deep Learning for Industrial Inspection

Onsite workshops are one of the most effective ways to train teams of developers and data scientists. DLI has delivered instructor-led workshops on-site at organizations as diverse as Adobe, Baker Hughes, Booz Allen Hamilton, Cisco, Groupe PSA, and the U.S. Food and Drug Administration. Plus, DLI is working with companies like Lockheed Martin to provide this training at multiple sites across their enterprise.

“Lockheed Martin Corporation is committed to providing our employees with access to advanced training and tools,” said Matt Tarascio, chief data and analytics officer at Lockheed Martin. “The outstanding instructors and material of NVIDIA’s DLI program have been instrumental in helping to accelerate the adoption of modern data-driven AI across the corporation in applications such as deep learning, computer vision, natural language processing, intelligent video analytics and more.”

In addition to in-person training, DLI launched new online, self-paced courses on:

• Fundamentals of Accelerated Data Science with RAPIDS 
• Getting Started with AI on Jetson Nano
• Deep Learning at Scale with Horovod
• High Performance Computing with Containers
• Data Science Workflows for Deep Learning in Medical Applications

Many of the courses offer a certificate of competency to support professional growth. Plus, DLI offers resources to universities including free DLI Teaching Kits to bring AI skills to their classrooms and the DLI Ambassador Program to teach DLI courses to students for free.

Enroll in online, self-paced courses or request an instructor-led workshop for your team.

The post Closing the AI Skills Gap: Deep Learning Institute Adds A Dozen New Courses appeared first on The Official NVIDIA Blog.