Erik Pounds, Director of Product Marketing at NVIDIA, Discusses Enterprise AI On Dinis Guarda YouTube Podcast
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In his latest YouTube podcast, Dinis Guarda interviews Erik Pounds, Director of Product Marketing at NVIDIA to discuss how NVIDIA’s advanced AI technologies are shaping the future of tech industry. The podcast, powered by Businessabc.net and Citiesabc.com, also highlights NVIDIA’s leadership in AI innovation, from GPUs to generative AI.
Erik Pounds is the Director of Product Marketing at NVIDIA, focussed on full-stack solutions in the areas of AI and data science. He is also the Senior Director of Enterprise AI at NVIDIA, responsible for promoting GPU-accelerated tools and technologies like the NVIDIA Merlin deep recommender system and the NVIDIA Riva conversational AI framework.
His team helps developers use NVIDIA’s powerful AI models to create custom solutions for their businesses. Erik explained NVIDIA’s approach to addressing the evolving needs of businesses with advanced technology:
“Every business is trying to figure out how to adopt these new generative AI capabilities to reach new levels of productivity and efficiency. NVIDIA is seen definitely as a technology powerhouse.”
Erik explains to Dinis how NVIDIA’s high-performance GPUs and AI solutions are making businesses more efficient:
“Traditional Computing is very serial: You do one task at a time and you do those as quickly as possible with GPU Computing.
With parallel computing, you're doing many things in parallel at a single time and it just turns out that tasks like processing a large amount of data or training an AI model or running that AI model and production across thousands and thousands of users are just amazing applications for to accelerate computing
Although it's a new type of computing for many, it has been worked on for multiple decades by some amazing innovators and a very large ecosystem. So, for a lot of development teams and businesses and application owners that want to take advantage of accelerated computing, it's now right at your fingertips and it's much easier to leverage.
We're trying to make it so the important things you need to leverage are just a simple API call away through a microservice or a cloud service.”
Its cutting-edge architectures, such as Ampere and Hopper, power GPUs that excel in both training and inference of AI models. Technologies like NVIDIA CUDA enable developers to leverage GPU acceleration easily, enhancing the capabilities of software in fields ranging from scientific research to entertainment.
NVIDIA's innovations in ray tracing and DLSS (Deep Learning Super Sampling) have significantly advanced the realism and performance of graphics in gaming and professional visualisation.
Highlighting the potentials of NVIDIA’s GPU technologies, Erik further adds:
“The impact that Hopper made on generative AI is tremendous. And then, Jensen explains Blackwell as the first platform built for the ground up for the era of generative AI. This is just tremendously exciting, the progress that is being made from platform to platform.
If you adopt NVIDIA software and build your applications on top of our platform, you have a track record of forward and backwards compatibility. This makes it easy for you to adopt these solutions as well as run them across different types of systems.”
Innovations in AI: From interactive avatars to virtual worlds
Erik and Dinis also discuss how innovations in AI are transforming user interactions and development processes. Erik highlighted:
"I think the human-like interfaces into these new applications are going to be very important. You can easily set up a prototype chatbot by deploying a large language model and providing a text input interface. However, the real value comes from using additional AI models that can enhance the application. For example, instead of typing, it would be great to talk to the application. We have a suite of software called NVIDIA Riva, which includes AI models for automatic speech recognition, text-to-speech, and real-time language translation. This allows for a more natural and interactive interface."
He further explained: "For us to really enjoy using these applications, they need to be natural. If an application takes 60 seconds to respond, that's not very natural or enjoyable. Quick, conversational responses are key. Digital avatars and human-like interfaces are also becoming crucial. For instance, fast food restaurants now often use kiosks instead of human cashiers. While these kiosks are efficient, they can be clunky and time-consuming. In the future, you'll be able to talk to a friendly AI-powered kiosk that will make the interaction more seamless and pleasant."
"All these models are available to try out on Nvidia’s website at ai.nvidia.com. You can explore not just large language models but also the latest in speech technology and digital human interfaces. Additionally, Omniverse connects the physical world to virtual worlds in real-time, allowing you to develop and test applications in a virtual environment before deploying them in the real world."
The future of AI
NVIDIA launched the NVIDIA AI Foundry with NVIDIA NIM™ inference microservices, designed to empower enterprises and nations to develop bespoke ‘supermodels’ designed to specific industry needs using the latest Llama 3.1 collection of openly available models.
Commenting on this part of innovation, Erik tells Dinis:
“It's open, and can generate data that you can own and leverage in a commercial type application. One of the new interesting things about this model is that you can use it as it is and customise it.
One of the new applications is synthetic data generation. So, as you're building a custom model, you can take your proprietary data and use that to alter the model to have the knowledge of your domain, or the knowledge of your business, or you can even trade it, do certain skills in a lot of scenarios.
Nvidia AI Foundry gives you a service that you could use to take your proprietary data, bring that into The Foundry and customise these powerful models like Llama. We have evaluation tools as well so that you can evaluate the model across, whether it's industry benchmark or cross-benchmarks that are specific to your application. So, you ensure that you are building the best possible model and guardrail it so the model behaves in the way that you need it. We output models out of The Foundry in a stack that we call NVIDIA NIM that takes an optimised runtime and an easy to use API, wraps it all up into a container that you can deploy anywhere in the world, in the cloud, at the edge, in a device, on a workstation, and so on so forth.
So, now it makes building custom generative AI, its deployment, and use a whole lot easier.”
Erik shares some practical advice on how to approach these changes:
"For businesses, organisations, governments, and nations, one way to take away some of the fear and uncertainty is just to get going. If you're not already engaged in learning about these new technologies and using these new capabilities, I'd say just jump in and start doing that. You'll learn some tremendous advantages that come with it. Yes, there will be new challenges, but they're in line with some of the challenges we've faced before, like when we adopted cloud computing.”
“There were concerns about putting data in the cloud and securing it, but we figured out ways to do that. The same goes for AI. Jump in two feet first, embrace these capabilities, and you'll discover what you need to do to develop, deploy, scale, and secure these new powerful applications. They will benefit your business tremendously. This is why we set up ai.nvidia.com—to give developers easy access to powerful AI models running on NVIDIA accelerated computing. It's free to use, with models of all different shapes and sizes. Whether you're interested in vision models or biology-based models, it's a great place to start learning about NVIDIA and our capabilities."
With a driving passion to create a relatable content, Pallavi progressed from writing as a freelancer to full-time professional. Science, innovation, technology, economics are very few (but not limiting) fields she zealous about. Reading, writing, and teaching are the other activities she loves to get involved beyond content writing for intelligenthq.com, citiesabc.com, and openbusinesscouncil.org
