Data is the fuel that makes artificial intelligence run.
Training machine learning and AI systems requires data. And the quality of datasets has a big impact on the systems’ results.
But compiling quality real-world data for AI and ML can be difficult and expensive.
That’s where synthetic data comes in.
The guest for this week’s AI Podcast episode, Nathan Kundtz, is founder and CEO of Rendered.ai, a platform as a service for creating synthetic data to train AI models. The company is also a member of NVIDIA Inception, a free, global program that nurtures cutting-edge startups.
Kundtz is a physicist by training, holds a Ph.D. from Duke University and previously founded Cometa, a hybrid satellite cellular network company.
Our host, Noah Kravitz, spoke to Kundtz about how AI can be used to generate the data needed to create better AI.
Artem Cherkasov and Olexandr Isayev on Democratizing Drug Discovery With NVIDIA GPUs
It may seem intuitive that AI and deep learning can speed up workflows — including novel drug discovery, a typically years-long and several-billion-dollar endeavor. However, there is a dearth of recent research reviewing how accelerated computing can impact the process. Professors Artem Cherkasov and Olexandr Isayev discuss how GPUs can help democratize drug discovery.
Lending a Helping Hand: Jules Anh Tuan Nguyen on Building a Neuroprosthetic
Is it possible to manipulate things with your mind? Possibly. University of Minnesota postdoctoral researcher Jules Anh Tuan Nguyen discusses allowing amputees to control their prosthetic limbs with their thoughts, using neural decoders and deep learning.
Wild Things: 3D Reconstructions of Endangered Species With NVIDIA’s Sifei Liu
Studying endangered species can be difficult, as they’re elusive, and the act of observing them can disrupt their lives. Sifei Liu, a senior research scientist at NVIDIA, discusses how scientists can avoid these pitfalls by studying AI-generated 3D representations of these endangered species.
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