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  • Date
    Event Details
  • On Demand
    GenAI Fundamentals with OpenVINO

    GenAI Fundamentals with OpenVINO

    Generative AI (GenAI) models are rapidly evolving, with smaller models now proving to be as effective as their larger counterparts, offering agility and resource efficiency.

    Explore the future of GenAI with our AI Evangelists and an Intel Fellow. Discover how to deploy efficient GenAI models on AI PCs and edge devices using the OpenVINO toolkit for faster, smarter inference.

    Key Takeaways

    • Understand the balance between small and large language models (LLMs).
    • Learn about LLM compression techniques like INT8, INT4, and 1-bit models.
    • Discover new features in the latest OpenVINO release, including broader LLM models, Mixture of Experts (MoE) architecture, and memory optimization.
    • See live demos of GenAI deployment on Intel hardware.
    • Gain insights into deploying AI models with OpenVINO Model Server and new GenAI workloads.

    Speakers

    Anisha Udayakumar

    Anisha Udayakumar
    LinkedIn

    AI Software Evangelist, Asia-Pacific and Japan, Intel

    Paula Ramos, Ph.D

    Paula Ramos, Ph.D
    LinkedIn

    AI Software Evangelist, USA, Intel

    Ria Cheruvu

    Ria Cheruvu
    LinkedIn

    AI Software Evangelist, USA, Intel

    Yury Gorbachev

    Yury Gorbachev
    LinkedIn

    Intel Fellow, OpenVINO Product Architecture, Intel

  • On Demand
    New Era of AI PC: AI to NPU

    New Era of AI PC: AI to NPU

    Discover the unique AI acceleration capabilities of the AI PC, which span across CPU, GPU, and NPU.

    Join this session to gain a comprehensive understanding of leveraging the NPU for AI inference tasks and using OpenVINO to optimize AI applications. Experience live demos showcasing the performance and power efficiency of AI applications on the AI PC.

    Key Takeaways

    • Understand what an AI PC is and its AI acceleration capabilities across CPU, GPU, and NPU.
    • Explore various AI use cases, including conventional and generative AI, and see their practical applications on the AI PC.
    • Learn how the NPU enhances AI application performance and power efficiency, especially for tasks traditionally offloaded to AI accelerators.
    • Discover techniques for optimizing and deploying AI applications on NPU using OpenVINO for maximum efficiency.
    • Experience live demos showing seamless AI application transitions to the NPU with OpenVINO.
    • Find out how developers can leverage OpenVINO on AI PCs to enhance their AI projects.

    Speakers

    Anisha Udayakumar

    Anisha Udayakumar
    LinkedIn

    AI Software Evangelist, Asia-Pacific and Japan, Intel

    Dmitriy Pastushenkov

    Dmitriy Pastushenkov
    LinkedIn

    AI PC Evangelist, Europe, Middle East and Africa, Intel

    Darren Crews

    Darren Crews
    LinkedIn

    Sr. Principal AI Engineer​, Intel

    Dmitry Matveev​

    Dmitry Matveev​
    LinkedIn

    AI Software Engineering Manager​, CCG Client Graphics & AI / NPU IP, Intel

  • On Demand
    Model Compression and Optimization

    Model Compression and Optimization

    Learn to build computer vision and anomaly detection applications using the open-source Anomalib library for real-time defect detection, improving quality control across industries like manufacturing, healthcare, and agriculture.

    Join this session to gain hands-on experience with AI inference solutions, see a robot in action, and stay updated on the latest VAND 2.0 Challenge at CVPR.

    Key Takeaways

    • Understand the fundamentals of the OpenVINO toolkit, OpenVINO runtime, and Neural Network Compression Framework (NNCF) in anomaly detection.
    • Master the integration of state-of-the-art anomaly detection algorithms using Anomalib 1.0.
    • Learn to train and optimize AI models for edge deployment with techniques like quantization and OpenVINO.
    • Gain practical experience in model optimization and deployment on edge devices.
    • Discuss future industry challenges in anomaly detection.

    What's More?

    Participate in the workshop quiz for a chance to win special Amazon vouchers*.

    Speakers

    Anisha Udayakumar

    Anisha Udayakumar
    LinkedIn

    AI Software Evangelist, Asia-Pacific and Japan, Intel

    Paula Ramos, Ph.D

    Paula Ramos, Ph.D
    LinkedIn

    AI Software Evangelist, USA, Intel

    Samet Akcay

    Samet Akcay
    LinkedIn

    AI Research Engineer, Intel

    Zhuo Wu

    Zhuo Wu, Ph.D
    LinkedIn

    AI Software Evangelist, People's Republic of China, Intel

    *Read the 'Terms and Conditions' for the quiz here.

  • On Demand
    Ask it aloud. LLMs on Small Form Factor?

    Ask it aloud. LLMs on Small Form Factor?

    Explore deploying large language models (LLMs) on client PCs and small form factor at the edge, focusing on implementing a conversational voice agent.

    Learn efficient techniques for deploying LLMs on resource-constrained devices using OpenVINO, and see how a Gradio-built interface can enhance usability.

    Key Takeaways

    • Understand how the Edge AI Reference Kit enables advanced LLM deployment on edge devices.
    • Learn how OpenVINO optimizes LLMs for AI PCs, balancing performance and power efficiency.
    • Discover methods to reduce model size and computational demands for efficient LLM applications.
    • Gain practical skills in implementing LLMs with OpenVINO for powerful, efficient AI applications.
    • See how OpenVINO enhances the capabilities of LLMs on edge devices for smarter, faster AI solutions.

    What's More?

    Participate in the workshop quiz for a chance to win special Amazon vouchers*.

    Speakers

    Anisha Udayakumar

    Anisha Udayakumar
    LinkedIn

    AI Software Evangelist, Asia-Pacific and Japan, Intel

    Adrian Boguszewski

    Adrian Boguszewski
    LinkedIn

    AI Software Evangelist, Europe, Middle East and Africa, Intel

    Zhuo Wu

    Zhuo Wu, Ph.D
    LinkedIn

    AI Software Evangelist, People's Republic of China, Intel

    *Read the 'Terms and Conditions' for the quiz here.

  • 7 November 2024
    Bringing GenAI to AI PC

    Bringing GenAI to AI PC

    Dive into generative AI on the latest AI PCs, leveraging AI acceleration across CPU, GPU, and NPU.

    Designed for developers, this session is a comprehensive overview of using GPU and NPU for image-based generative AI and using OpenVINO to optimize the implementation and deployment of AI models such as Stable Diffusion, Latent Consistency Models, and more.

    Key Takeaways

    • Understand AI PC's AI acceleration capabilities across CPU, GPU, and NPU.
    • Explore various AI use cases, including generative AI, with practical applications on AI PCs.
    • Learn how generative AI applications achieve maximum performance and power efficiency using heterogeneous computing.
    • Experience live demos of seamless AI application transitions across CPU, GPU, and NPU with OpenVINO.
    • Discover how to experiment with and leverage OpenVINO on AI PCs for enhancing generative AI projects.

    What's More?

    Participate in the workshop quiz for a chance to win special Amazon vouchers*.

    Speakers

    Anisha Udayakumar

    Anisha Udayakumar
    LinkedIn

    AI Software Evangelist, Asia-Pacific and Japan, Intel

    Dmitriy Pastushenkov

    Dmitriy Pastushenkov
    LinkedIn

    AI PC Evangelist, Europe, Middle East and Africa, Intel

    Ria Cheruvu

    Ria Cheruvu
    LinkedIn

    AI Software Evangelist, USA, Intel

    Ryan Metcalfe

    Ryan Metcalfe
    LinkedIn

    AI Software Solutions Engineer, Intel

    *Read the 'Terms and Conditions' for the quiz here.

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