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Wednesday, December 2, 2020 9:00 am PST

Analyze, Test and Deploy AI from Anywhere, Anytime

Get your AI applications from development to deployment faster. The 2021.1 release of the Intel® Distribution of OpenVINO™ toolkit adds integration between two popular tools to speed the process.

Using the toolkit’s Deep Learning (DL) Workbench tool, developers can analyze and optimize their models—and now they can also remotely deploy on Intel® architecture using Intel® DevCloud for the Edge—an open development sandbox in the cloud.

With the integration, developers can compare, visualize, and fine-tune their models against multiple hardware configurations without the need for an Intel® processor on their bench.

Join Intel experts Marat Fatekhov, Jason Domer, Ramakrishna Dorairaju, and Zoe Cayetano to learn more about this new integration:

  • An overview of the new integration with Intel DevCloud for the Edge
  • How to use DL Workbench, the UI optimization tool in the Intel Distribution of OpenVINO toolkit, to easily visualize and analyze DL workloads.
  • How you can develop, fine-tune and remotely experiment using both the DL Workbench and the Intel DevCloud for the Edge

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Ramakrishna Dorairaju, Lead Software Architect, Intel Corporation

Rama is a System Engineer focused on solving problems related to Edge Computing by bringing easy access to accelerated AI. Rama has 20+ years of experience in Embedded systems, Satellite broadcast & mobile communications and IoT/Edge computing domains, with a strong understanding of computer vision, cloud architectures and ML/DL Workloads.

Ryan Palmer, Developer Experience Architect, Intel Corporation

Ryan works within Intel’s Internet of Things Group to research and design optimal experiences for AI developers. He holds a M.S. in Human-Factors Engineering and has spent 15 years at Intel on the leading edge of innovation and design of hardware and software solutions.

Marat Fatekhov, Software Developer, Intel Corporation

Marat has more than 5 years of programming experience with focus on extending Intel portfolio of tools for Mobile, Media and AI markets. Currently working in the OpenVINO Deep Learning Workbench team. Marat holds Bachelor’s degree in Business Informatics and Applied Mathematics and Masters degree in Management from Higher School of Economics, Nizhniy Novgorod.

Tuesday, December 8, 2020 9:00 am PST

AI Beyond Computer Vision with the Intel® Distribution of OpenVINO™ toolkit

AI development is a rapidly growing field and the demand for a common toolkit is even more necessary, whether your workload uses computer vision or natural language processing. The 2021.1 release of the Intel® Distribution of OpenVINO™ toolkit helps developers meet this growing demand.

The 2021.1 release of the Intel® Distribution of OpenVINO™ toolkit adds support for audio, speech, language, machine translation, recommender systems, and more. Now developers can use deep learning inference to build machines that listen, feel, and recognize patterns beyond computer vision.

Join OpenVINO toolkit experts Julie Maas, Neelay Shah, Anthony Reina and Zoe Cayetano for an overview of the new beyond vision support built-in to the latest release of Intel Distribution of OpenVINO toolkit, including:

  • A walkthrough of available development resources, including a framework for processing audio inputs, pre-trained models, and fine-tuning recipes for network compression.
  • Use cases including voice-enabled and contactless retail kiosks, and those that are enabling the discovery of new pharmaceuticals and manufacturing methods with biomedical text search.
  • Live coding demo for audio analytics, automatic speech recognition, and natural language processing.

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Download the Intel Distribution of OpenVINO toolkit—Download the 2021.1 release to take advantage of the latest updates.

Zoe Cayatano, Product Manager, Intel Corporation

Passionate about democratizing technology access for everyone and working on projects with outsized impact on the world, Zoe is a Product Manager for AI and IoT working on a variety of interdisciplinary business and engineering problems. Prior to Intel, she was a data science researcher for a particle accelerator at Arizona State University, where she analyzed electron beam dynamics of novel x-ray lasers that were used for crystallography, quantum materials and bioimaging. She holds Bachelor’s degrees in Applied Physics and Business.

Julie Maas, Product Manager, Intel Corporation

Julie Maas is a product manager within Platform Management and Customer Engineering in the Internet of Things Group at Intel Corporation. She is responsible for driving opportunities for Multimodal Sensemaking across IOTG’s developer offering for software products and tools.

Neelay Shah, Sensing and Media Analytics Architect, Intel Corporation

Neelay is responsible for providing developer tools and solutions that accelerate time to market for Intel’s customers. He works to simplify the deployment of optimized analytics to solve real world problems. Since 2016, Neelay has been advancing the state of sensing and media analytics in intelligent systems, integrating new technologies into consumer laptops such as sensor based adaptive performance, display and wake. Intel User Awareness was recognized at CES in 2019 as part of Intel’s Innovation Excellence Program in partnership with top laptop manufacturers. With the explosion of video and media analytics, Neelay now works to accelerate new media analytics use cases at the edge and in the cloud. Neelay graduated from Williams College with a Bachelor of Arts in Computer Science and from the University of Illinois at Urbana-Champaign with a Masters in Computer Science specializing in machine learning. He was a 2006 Siebel Scholar and an inaugural member of the UIUC creative writing MFA program. He doesn’t believe in spare time, but away from his laptop he enjoys playing ultimate frisbee, biking, reading, writing, listening to the Grateful Dead, cheering for the Kansas City Chiefs and spending time with his wife, two dogs, two cats, and two boys.

Wednesday, December 9, 2020 9:00 am PST

Achieve AI Performance from Datacenter to Edge

Artificial intelligence offers competitive advantages to almost every industry. But attaining AI’s benefits comes with steep challenges. Namely, managing huge volumes of data. This webinar unpacks key software tools and techniques for harnessing your datasets.

AI applications must necessarily achieve a high bar. They must crunch, assess, and accurately visualize enormous, complex datasets in real-time. They must be parallelized. And they must be optimized to run across multiple architectures.

Two “powered by oneAPI” toolkits are purpose-built to meet all of those challenges. The Intel® AI Analytics Toolkit focuses on AI developers and data scientists. The Intel® Distribution of OpenVINO™ Toolkit provides AI application developers high performance for model deployment across Intel® architectures.

In this session, Intel AI product manager Saumya Satish address Intel’s holistic approach to AI and Data Science and discusses a set of software tools that enable development and deployment of machine and deep learning models across XPUs.

She’ll cover:

  • Key tools and frameworks—part of the oneAPI ecosystem—that deliver drop-in acceleration for AI workloads using complex scientific computations and big data analysis
  • How the Intel AI Analytics Toolkit and OpenVINO toolkit leverage oneAPI libraries to exploit cutting-edge hardware features
  • How to maximize performance for model training, inference, and deployment
  • Optimized machine learning and data analytics Python packages

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Saumya Satish, Product Manager, Intel Corporation

Saumya is a Product Manager for AI software products, with a focus on deep learning and data analytics technologies. She is passionate about the developer ecosystem and keen to provide the right set of tools that help developers build innovative applications, particularly AI and machine learning domains. Since joining Intel in 2011, she has worked as a Research Scientist and Technical Evangelist on some of Intel’s Imaging and Computer Vision software products. Saumya holds a Master’s degree in Electrical Engineering from University of Florida, Gainesville. A native of India, she is currently based in San Jose, California.

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