It’s Time to Learn AI, And It Just Got Easier Than Ever

It is nearly impossible to avoid AI these days. In conversation, it is described as a tool of the future, a tool of power, a tool of opportunity. Well, regardless of the view towards AI, it is something that is better to understand than ignore and it is something that, with understanding, will create and support countless jobs of the future. Fortunately, knowledge about AI — and the ability to design alongside it — is becoming increasingly accessible.

Tech giants around the world are acting swiftly to bring AI to the edge, and NVIDIA has a head start on many of them. The company started out focusing primarily on gaming, specifically in designing and manufacturing graphics processing units (GPUs). Since 2014, however, NVIDIA technology has expanded into sectors such as data centers, professional visualization, healthcare, and autonomous machines.

As AI proliferates, a new generation of students and developers will play a critical role in teaching and training autonomous machines and robots how to behave in the real world. NVIDIA is now taking its AI thought leadership further through the release of the NVIDIA Jetson Nano 2GB Developer Kit which offers “unprecedented, affordable access to state-of-the-art computer solutions for learning autonomy,” says Emilio Frazzoli professor of Dynamic Systems and Control at ETH Zurich.

With this cue card-sized AI embedded devkit, learners of all ages and backgrounds will have access to a powerful machine learning experience that makes creating autonomous robots easier than ever. Get inspired by community projects or follow along to fun step-by-step tutorials, such as this how-to for building a mini DIY autonomous racecar called Jetbot.

With the mutual goal of teaching a wide audience of students about robotics and AI, NVIDIA has partnered with the Duckietown project, which started as an MIT class in 2016 and has since evolved into an open-source platform for robotics and AI education, research and outreach. Duckietown offers hands-on learning activities in which students put AI and robotics components together to address modern autonomy challenges for self-driving cars. Solutions are implemented in the Duckietown robotics ecosystem, where the interplay among theory, algorithms and deployment on real robots is witnessed firsthand in a model urban environment.

Frazzoli added, “The Duckietown educational platform provides a hands-on, scaled-down, accessible version of real-world autonomous systems.”

To encourage educators to adopt STEM projects, NVIDIA has set up a free Jetson AI Course and Certifications program. Teachers can become certified as a Jetson AI Specialist or Jetson AI Ambassador by completing the Jetson AI Fundamentals course and publishing an open-source Jetson project as part of the assessment.

And, for educators to custom-build their AI courses, NVIDIA also offers freely available curriculum and open-source platforms.

The Jetson Nano 2GB Developer Kit has already begun to garner acclaim across the world:

Drew Farris, director of Analytics and AI Research at Booz Allen Hamilton, said: “At Booz Allen, we seek to empower people to change the world. We’re using NVIDIA Jetson to train new technical resources as AI becomes critical for enterprises and personnel leveraging AI to solve the most difficult global challenges.”

Jack Silberman, Ph.D., Lecturer, UC San Diego, Jacobs School of Engineering, Contextual Robotics Institute, said: “NVIDIA’s Jetson AI Certification materials thoroughly cover the fundamentals with the added advantage of hands-on project-based learning. I believe these benefits provide a great foundation for students to prepare for university robotics courses and compete in robotics competitions.”

Christine Nguyen, STEM curriculum director at Boys & Girls Club of Western Pennsylvania, said: “We know how important it is to provide all students with opportunities to impact the future of technology. We’re excited to utilize the NVIDIA Jetson AI Specialist certification materials with our students as they work toward becoming leaders in the fields of AI and robotics.”

“While today’s students and engineers are programming computers, in the near future they’ll be interacting with, and imparting AI to, robots,” said Deepu Talla, vice president and general manager of Edge Computing at NVIDIA. “The new Jetson Nano is the ultimate starter AI computer that allows hands-on learning and experimentation at an incredibly affordable price.”

Understanding the inner workings of AI is an essential skill of the present and will extend long into the future as well.

To learn more visit NVIDIA’s website.

For more, see: 

• Future of Work Page
• Artificial Intelligence: The New Digital Divide?

This post is sponsored by NVIDIA. If you’d like to learn more about our policies and practices regarding sponsored content, please email Mason Pashia.

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