WEBINAR
Optimize Your Model Deployment with Triton Inference Server
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Date: Tuesday, March 1, 2022
Time: 10:00 - 11:15 CET
Duration: 75 Minutes
Time: 10:00 - 11:15 CET
Duration: 75 Minutes
One of the main challenges AI startups are facing is efficiently deploying their Machine and Deep Learning models. In this webinar, we will explore how NVIDIA Triton Inference Server simplifies and accelerates inference on GPUs. Join the webinar to learn how startups can optimize their inference pipeline and scale AI model deployment with ease.
- What are the biggest challenges of inference in a data center or at the edge and how Triton solves them
- The key features of Triton, i.e. support for multiple frameworks, high-performance inference and streamlined model deployment in production
- How a startup deploys Triton in a real-world use case
WEBINAR REGISTRATION
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NVIDIA Inception is a program for startups that provides critical co-marketing support, training, and technology. All of your engineers have access to hands-on, cloud-based training through the NVIDIA Deep Learning Institute, preferred pricing on hardware via our global network of distributors, invitations to exclusive networking events, opportunities to engage with venture capital partners, and more. These benefits were specifically crafted to provide startups faster time to market, as well as platform acceleration which delivers increased ROI. Apply today!Content
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Speakers
Alexander Martynau
Inception program EMEA Community Manager, NVIDIAAlexander Martynau is Inception program EMEA Community Manager. With background in Sales & Communication and a passion for accelerated computing, he has been helping startups adopt NVIDIA platform solutions for the last 4 years. Lately focusing on the rapidly growing MENA startup ecosystem, Alexander identifies future AI champions and helps them scale using cutting-edge NVIDIA technology.
Adam Grzywaczewski
Senior Deep Learning Data Scientist, NVIDIADr. Adam Grzywaczewski is a senior deep learning data scientist at NVIDIA, where his primary responsibility is to support customers in scaling and deployment of their deep learning workloads. Over the last four years, Adam has specialized in large-scale training, focusing not just on deep learning system and software design, but also on algorithms that allow for large batch data/model/pipeline parallel training. Adam works with customers with high computational needs, including key automotive customers and organizations with the need for large scale NLP and conversational AI. Adam also focuses on techniques for computationally efficient inference, including parameter/compute efficient model design and model pruning and quantization.
Ulrik Stig Hansen
Co-Founder, EncordUlrik taught himself to code and sold his first website built using the LAMP stack when he was 14. He started his career managing a multi-million dollar franchise in the emerging markets rates & FX team @ J.P. Morgan. Ulrik holds an M.S. in Computer Science from Imperial College London.
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