AI Podcast: Your Next Pizza Delivery May Come Topped with AI

You ask, AI delivers.

At least, that’s the concept that Kevin Peterson is trying to achieve with his robotics company, Marble. It recently made news for deploying food delivery robots onto the streets of San Francisco.

Peterson, Marble’s co-founder and software lead, joined this week’s AI Podcast to talk about their efforts to integrate AI into the delivery process.

Marble’s robots, all named “Happy,” look like a white boxcar about the size of a mobility scooter. They’re complete with a trunk, where it stores packages. Users get a code with their delivery confirmation to access their packages.

“We want everyone’s first interaction with the robot to be delightful, actually,” explained Peterson in a conversation with Michael Copeland, the host of NVIDIA’s AI Podcast. “So we spend a lot of time designing that interaction and making sure the vehicle is operating in a way that looks good and is good.”

To provide efficient delivery, the Marble team uses a 3D map system to plan out the best routes for their delivery bots. According to Peterson, the robot has a program that detects last-minute route obstacles, and then will request a re-route.

For Peterson, automating delivery systems is only the beginning.

“There’s a huge amount of impact in the world that comes from having these kinds of autonomous vehicles out there,” he says.

Source: NVIDIA Blog

What Is The NVIDIA GRID License?

Today, the demand for on-demand image processing is increasing. Every program, from Microsoft Office which may run slowly on Windows 10, to advanced imaging software like AutoCAD and Autodesk, for companies in the construction and design industries, can benefit from better image processing.

The NVIDIA GRID License allows for GPU resources to be spread among users, by using a single GPU server. Using Live Migration, this allows for superior image and video processing – and you can even use NVIDIA GRID to run other complex AI Deep Learning calculations, while still maintaining smooth operation. Learn more on Youtube.

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What Is A GPU?

GPU stands for Graphics Processing Unit. GPUs have many more cores than a comparable CPU – the most powerful graphics card have more than 5,000 cores, while most CPUs have a maximum of 10 cores. This makes GPUs faster and more efficient than CPUs for repetitive tasks such as AI development. Learn more on Youtube video.

what is gpu

Is NVIDIA’s DGX Station Better Than DIY Machines For AI/Deep Learning?

Learn more on YouTube.

Is NVIDIA’s DGX Station Better Than DIY Machines For AI/Deep Learning

If you’re interested in AI and deep learning, you must either buy a supercomputer that can handle AI Model Training, or build your own machine to create a DIY machine. But is this a good idea? We don’t think so.

Save Time And IT Resources

Building your own AI computer is usually cheaper than an off-the-shelf unit the NVIDIA DGX Station – but only if you ignore the time and IT resources required to run the unit, download and update software, and maintain the computer. When you factor these costs in, the NVIDIA DGX Station is a much better option.

The NVIDIA DGX Station – Ready To Go For AI Projects

The NVIDIA DGX Station is ideal for AI scientists. This compact supercomputer is small enough to place on your desk, and has low power consumption.

It also offers enhanced security, as your sensitive data does not have to be on the cloud. And because it’s embedded with pre-installed AI software, you can start AI model training in just 2-4 hours. There’s no need to spend extra time and money on more IT equipment or on support services.

Learn more rental NVIDIA DGX Station and NVIDIA Deep Learning Institute.