Search results Search for: Search Refine your results by duration: Any Under 5 mins Under 20 mins Over 20 mins Sort by: Relevance Views Date How Canonical and NVIDIA can help operationalise your AI models quickly Andreea Munteanu, MLOps Product Manager, Canonical; Michael Balint, Sr Manager, Product Architecture, NVIDIA High-performance AI can only be achieved when hardware and software work together. An end-to-end MLOps solution working on hardware designed for AI is... 6 months ago | 39 mins Accelerate Genomic Sequencing Jason Fenwick, NVIDIA Genomics Industry Business Development; Bikash Roy Choudhury, Director of Solutions, HPC/DevOps As life sciences organizations expand Whole Genome Sequencing (WGS), they are experiencing delays during secondary analysis. A GPU-optimized solution ... 2 months ago | 47 mins Innovate & Scale with DGX AI Accelerated Computing Deloitte Artificial Intelligence has steadily been moving from theory to practice, and many companies are now working to figure out how they can leverage these... 10 months ago | 21 mins Accelerate Genomic Sequencing with NVIDIA Clara™ Parabricks® and FlashBlade//S® Bikash Roy Choudhury, Pure Storage & Jason Fenwick, NVIDIA As life sciences organizations expand Whole Genome Sequencing (WGS), they are experiencing delays during secondary analysis. A GPU-optimized solution ... 4 months ago | 54 mins Accelerate Genomic Sequencing with NVIDIA Clara™ Parabricks® and FlashBlade//S® Bikash Roy Choudhury, Pure Storage & Jason Fenwick, NVIDIA As life sciences organizations expand Whole Genome Sequencing (WGS), they are experiencing delays during secondary analysis. A GPU-optimized solution ... 5 months ago | 54 mins Accelerate Genomic Sequencing with NVIDIA Clara™ Parabricks® and FlashBlade//S® Bikash Roy Choudhury, Pure Storage & Jason Fenwick, NVIDIA As life sciences organizations expand Whole Genome Sequencing (WGS), they are experiencing delays during secondary analysis. A GPU-optimized solution ... 5 months ago | 54 mins Scaling MLOps on NVIDIA DGX Systems (Special guest from NVIDIA) Yochay Ettun (cnvrg.io), Michael Balint (NVIDIA) Developing, experimenting, and deploying ML models at scale requires substantial tooling, scripting, tracking, versioning, and monitoring. Data scien... 3 years ago | 40 mins How Canonical and NVIDIA can help operationalise your AI models quickly Andreea Munteanu, MLOps Product Manager, Canonical; Michael Balint, Sr Manager, Product Architecture, NVIDIA High-performance AI can only be achieved when hardware and software work together. An end-to-end MLOps solution working on hardware designed for AI is... 6 months ago | 32 mins Fueling Automotive GPUs with data to power the next generation of deep learning Ramnath Rai Sagar, AI & ML Product Lead, Pure Storage The key battleground for automotive stakeholders over the next three years will be achieving the production of electric, connected and autonomous vehi... 5 years ago | 62 mins From Experimentation to Insights: Building an End-to-End Deep Learning System Tony Paikeday, Dir of Product Marketing, NVIDIA Deep Learning Systems; Roy Kim, Dir of Product Solutions, PureStorage Every organization wants to infuse the power of AI in its business. From development to production training, you need an end-to-end AI workflow that’s... 5 years ago | 61 mins