Unleash the Power of Generative AI with NVIDIA NIM microservicesAs organizations transition from generative AI experiments to deploying and scaling generative AI applications in production, the focus on production model deployment for inference—where AI delivers results—is growing. In addition to strategies that ensure data security and compliance while enabling flexibility and agility for innovation, enterprises need a streamlined, cost-effective approach to managing AI inference at scale.Master NVIDIA NIM microservices for deploying foundation models securely and efficiently. This workshop covers comprehensive deployment strategies for Language Models, Vision Language Models, Speech Models, Embeddings, and Rerankers. Learn to implement production-grade runtimes with enterprise support across cloud and data center environments.Join us for an engaging webinar where we'll explore key considerations for deploying and scaling generative AI in production, including the critical role of AI inference. Through real-world case studies highlighting successful enterprise deployments, we'll uncover best practices supporting enterprise data security and compliance, enabling developer innovation and agility, and unlocking AI inference for production applications at scale.Don't miss out on this opportunity to accelerate your enterprise journey to generative AI.LearningsThe Current Landscape of Generative AI:Understand the latest trends and challenges in deploying generative AI models.NVIDIA NIM microservices:A Game-Changer: Discover how NVIDIA NIMs can significantly improve the performance and efficiency of your generative AI inferences. Learn how to implement production-ready AI applications using NVIDIA NIM microservices & ensure security and compliance in model deployment.Real-World Case Studies:Hear from industry experts atxxxxas they share their experiences using NVIDIA NIMs to optimize their AI applications.(C) NVIDIA Corporation 2025. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

NVIDIA's groundbreaking AI blueprint enables developers and enterprises to create video analytics AI agents capable of understanding, searching, and summarizing videos. These interactive AI agents are being deployed in cities, factories, sports arenas, warehouses, and more—letting users make better decisions faster from richer insights and streamline operations.Customizing a video analytics AI agent to interact with domain-specific visual information is critical for producing accurate and reliable results for specialized use cases. Learn how to apply prompt engineering and fine-tune the VLMs powering these agents to boost productivity and solve your business needs.(C) NVIDIA Corporation 2025. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

NVIDIA's groundbreaking AI blueprint enables developers and enterprises to create video analytics AI agents capable of understanding, searching, and summarizing videos. These interactive AI agents are being deployed in cities, factories, sports arenas, warehouses, and more—letting users make better decisions faster from richer insights and streamline operations.Customizing a video analytics AI agent to interact with domain-specific visual information is critical for producing accurate and reliable results for specialized use cases. Learn how to apply prompt engineering and fine-tune the VLMs powering these agents to boost productivity and solve your business needs.(C) NVIDIA Corporation 2025. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

In this webinar we'll go behind the scenes of the new GPU engine to see how Polars' declarative API and query optimizer enable seamless GPU acceleration.(C) NVIDIA Corporation 2025. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

Join us to explore how generative AI, large language models (LLMs), vision language models (VLMs) and multimodal large language models (MLLMs) offer unprecedented capabilities. Understand the latest research in the field and get a glimpse into what’s coming next. You’ll also get a chance to hear direct from companies across industries as they share details about how they've built visual AI Agents to enable organizations to transform data into actionable insights at scale. They’ll demonstrate real-world applications and dive into the details on technical implementations. Then you’ll learn how you can fast-track development of your own visual AI agent with the latest NVIDIA Blueprint for video search and summarization.By attending the webinar, you'll:Learn directly from top researchers in vision and multimodal AI on the latest approachesHear about ongoing efforts to increase best practices in the responsible training and deployment of AI research systemsHear from different organizations on how they adopt the technologies to enable new business capabilities(C) NVIDIA Corporation 2025. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

Although the promise of AI to improve business operations and outcomes is starting to be realized, many organizations still struggle to implement AI solutions in production. The challenges of managing complex AI pipelines on GPU-accelerated infrastructure have held back adoption. NVIDIA AI Enterprise, the software platform for production AI, is designed to simplify this process, and this webinar will show you how by walking through an actual example of deploying a generative AI workflow, from prototyping to production at scale. By the end of this session, you’ll learn how to deploy AI microservices in your own infrastructure, whether on-prem or in the cloud, and how to manage a generative AI pipeline running on Kubernetes in production.In this webinar we will:Explore the NVIDIA API catalog of NVIDIA NIM microservices and determine what is required for deploying them to your own infrastructureUse tools such as NIM Operator to simplify the deployment of these containers as part of a whole generative AI pipelineManage the deployment, including how to configure automatic scaling as well as service monitoringCompare the experience of doing this in an on-prem cluster and a cloud-managed Kubernetes services(C) NVIDIA Corporation 2024. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

The future is clear: Every company will be an AI company. AI will be used to generate new insights, transform business operations, and improve business outcomes. While many organizations realize the importance of AI and the heightened pace of data-driven innovations, developing AI applications can be challenging and resource constrained. By leveraging NVIDIA vGPU solutions, your virtual desktop infrastructure can quickly and efficiently become an AI platform to start your AI journey. Join this webinar to learn more about how to jump-start AI developments, best practices for setting up optimized virtual machines, and the toolkits that NVIDIA provides.By attending this webinar, you will:Get an overview of NVIDIA RTX Virtual Workstation for AISee generative AI workloads demosLearn how to use the AI Workstation Toolkits for AI practitioners and IT professionalsHear about best practices for sizing and deployments (C) NVIDIA Corporation 2024. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

The integration of AI into traditional workflows and enterprise applications is blurring the lines between serial and parallel processing, requiring a new accelerated compute platform with a hybrid architecture that can seamlessly blend the flexibility and energy efficiency of the ARM CPU with the performance of the GPU. Join this webinar to hear from HEAVY.AI and Vultr on how the NVIDIA Grace Hopper™ Superchip’s converged memory architecture is accelerating a wide array of enterprise workloads for their customers, from database and analytics to LLM-powered agents, all while unlocking energy savings in the data center. In this webinar, you’ll learn:The benefits of the converged memory architecture of the NVIDIA GH200 SuperchipHow HEAVY.AI is leveraging NVIDIA GH200 to accelerate database query times, unlock new analytical insights, and deliver cost savings for its customersHow Vultr built out its NVIDIA GH200 cloud instances and how its customers are leveraging it to build LLM-powered digital agents(C) NVIDIA Corporation 2024. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

The rise of AI is transforming the way we work—from using chatbots to enhance productivity to automating meeting management via virtual assistants. As enterprises constantly build more resilient and higher-performing digital workspaces, they need to ensure their infrastructure will be future-proof for a remote workforce dependent on AI.Join this webinar, where NVIDIA will discuss how this AI revolution will change the remote work landscape and what to consider when equipping your data center to power the next generation of virtual desktops. By attending this webinar, you will:Learn about AI adoption and use cases in workspacesHear about building an AI-ready data center for your remote workforceExplore virtual GPU solutions for AI-powered workloadsGet your questions answered in a live Q&A session(C) NVIDIA Corporation 2024. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

There has been a huge rise in the use of graphics processing units for general purpose computing outside of purely visual applications. From accelerating scientific research simulations, to training artificial intelligences in an extensive range of fields, or analyzing medical images to predicting new proteins.This talk will look at Python-based software, tools, and frameworks that are available to help researchers and practitioners utilize the technology on NVIDIA GPU-based systems.Register now to see how to supercharge your applications with the power of NVIDIA GPUS.In this webinar, you'll learn:About available Python-based frameworks to accelerate your applicationHow to use RAPIDS to accelerate pandas with zero code changeHow to take advantage of libraries such as cuDNNWays to program directly for the hardware on the NVIDIA platform(C) NVIDIA Corporation 2024. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

Join us for an insightful webinar to learn how you can improve the accuracy and scalability of text retrieval for production-ready generative AI pipelines. With the newest available NVIDIA NeMo™ Retriever and NVIDIA NIM microservices, developers and IT practitioners can elevate enterprise data insights for several use cases.Built as an NVIDIA NIM, the NeMo Retriever microservices can be used together, or individually to complement community models, NVIDIA models, or your own custom models, and can be easily customized and deployed anywhere your enterprise data resides. Learn how to achieve the most accurate responses for text Q&A, and deploy wherever your enterprise data lives—cloud, data center, or hybrid.By joining this webinar, you’ll explore:What NVIDIA NeMo Retriever and NIM microservices are, and the applicable use cases.How to build enterprise-grade retrieval pipelines wherever your data lives.Real-world examples and performance benchmarks.How to get started quickly and seamlessly.Live Q&A.(C) NVIDIA Corporation 2024. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

Join us for a panel discussion to learn how to kick-start or accelerate your career in AI. Hear from our expert panelists as they outline the ever-evolving AI career paths, ways to gain valuable skills, what employers are looking for, and how to stand out from the crowd.You’ll also hear how our panelists forged their own AI careers, sharing actionable hints and tips along the way. This includes valuable advice on how to use cutting-edge tools and technologies in your AI projects. They’ll also point you to the resources, training and certifications that will supercharge your professional growth. Whether you’re a student, a recent graduate, or a seasoned professional, this webinar will provide you with valuable insights and inspiration for navigating your career in AI and other technologies.Register now to explore career paths and opportunities in AI.By joining this webinar, you’ll:Understand multiple career paths within AIExplore extracurricular training and resourcesHear how to make yourself stand out to employersGet your questions answered (C) NVIDIA Corporation 2024. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

지난 7월 첫번째 웨비나에 이어 진행하는 한국 NIM 개발자 웨비나에서는 헬스케어를 주제로 첨단 AI 도구를 활용한 메디컬 LLM와 신약 개발 혁신을 확인해 봅니다.첫 번째 파트에서는 거대 언어 모델(LLM)이 임상 연구를 어떻게 혁신할 수 있는지, RAG(Retrieval-Augmented Generation) 기능을 포함한 활용법을 소개합니다. NVIDIA NIM을 활용하면 LLM에 익숙하지 않은 생물학 연구자, 의사 분들도 쉽게 LLM을 도입하여 연구와 업무 도구로 이용하실 수있습니다. Writer의 Palmyra-Med NIM을 활용하여 신약/치료법 검색, 의학 논문 요약, 치료 지침 해석, 희귀 사례 보고서 제작을 위해 메디컬 LLM을 활용하는 방법을 라이브 핸즈온 데모로 함께 다룰 예정입니다.두 번째 파트에서는 AI 기반 Smart Drug Discovery를 주제로 신약 개발 파이프라인 혁신을 선보일 예정입니다. 이번 이벤트에서는 의학 종사자, 연구자, 제약 전문가, AI에 관심 있는 분들을 대상으로 하며, 인공지능이 디지털 생물학과 신약 개발 파이프라인을 과정을 어떻게 변혁할 수 있는지 탐구할 수 있는 기회를 제공합니다. 핸즈온 데모를 통해 단백질 3D 구조 예측을 위한 ESMFold, 화학식 생성을 위한 MolMIM, 생성된 화학식과 단백질의 결합 여부 판별을 위한 DiffDock NIM을 활용하여 타겟 질병의 단백질을 선택하기 위해 여러 단계의 파이프라인을 통합하여 신약 개발의 각 단계를 강화하고 효율화하는 방법을 소개합니다. 이번 이벤트를 통해 헬스케어의 미래를 직접 확인해 보세요. 연구 역량을 강화하고 싶거나 AI와 헬스케어의 교차점에 대해 궁금한 분들 모두에게 도움이 되는 리소스와 인사이트를 제공할 예정입니다.이벤트 관련 사전 질문은 다음 링크를 통해 제출해주시면 감사하겠습니다. - https://forms.gle/DTSXgmsZrHUzdeTi6본 웨비나를 통해 다음을 알아볼 수 있습니다:헬스케어 분야의 NIM 소개 (새롭게 출시되었습니다!)기업을 위한 헬스케어 산업 활용 사례Part 1. Medical LLM다양한 의료분야의 워크로드 혁신을 위해 Medical LLM을 활용하는 방법RAG 기능을 사용한 LLM 및 RAG 통합을 위한 데이터 준비 방법 - 라이브 데모Part 2. AI 기반 Smart Drug Discovery신약 개발을 위해 NIM 을 구현하는 방법 - 라이브 데모인터랙티브 Q&A 세션(C) NVIDIA Corporation 2024. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

デジタルツインをどのように始めるか、進め方と必要なリソースとは？さらに AI とロボットのシミュレーションをどのように組み込むべきか、国内の先進事例をもとにその手法を学びます。本ウェビナーでは、国内での Omniverse を活用したデジタルツイン導入を推進いただいているパートナー様と共に実現可能な産業デジタル化の手法を探ります。アジェンダデジタルツイン開発に必要なステップエヌビディア合同会社 プロフェッショナル ビジュアライゼーション ビジネス デベロップメント マネージャー高橋 想Omniverse上でのデジタルツイン開発を始める上で必要となるステップや開発に必要なリソースについて解説を致します。AIロボットシミュレーションを実現するデジタルツイン開発株式会社理経 執行役員 次世代事業開発部長 兼 経営企画室長石川 大樹 氏株式会社マクニカ クラビス カンパニー 技術統括部 技術第4部第1課広田 勇貴 氏本セッションでは、Omniverseを活用したAIロボットシミュレーション手法を紹介します。マクニカ倉庫のデジタルツイン化事例を基に、特徴的な機能とUSDを用いた最新の開発手法を解説します。OmniverseとROSで実現するロボット活用新時代東京工科大学 名誉教授田胡 和哉 氏AIやシミュレーション技術により、従来とは異なる場面でのロボット活用が可能になっています。ROSロボットの実例を通じ、Omniverse、Isaac、Jetsonを用いたロボットの実現と、産業における新しい活用方法について具体的に紹介します。(C) NVIDIA Corporation 2024. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

Learn how advances in high-performance computing and AI-enabled technology are revolutionizing financial services. (C) NVIDIA Corporation 2024. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

NVIDIA NIM이 어떻게 여러분의 생성형 AI 프로젝트를 전환할 수 있는지 알아보고, 몇 주가 아닌 몇 분 만에 AI 애플리케이션을 구축하고 배포할 수 있는 기회를 놓치지 마세요. 이번 개발자 밋업에서는 NVIDIA의 최첨단 추론 마이크로서비스의 주요 기능 및 주요 적용 사례를 알아보고 산업의 주요 솔루션 쇼케이스를 직접 경험하실 수 있습니다.생성형 AI 애플리케이션은 점점 더 복잡해지고 있으며, 텍스트, 이미지, 비디오, 음성 등을 생성하기 위해 다양한 기능을 가진 여러 모델을 활용하고 있습니다. NVIDIA NIM은 개발자가 생성형 AI를 애플리케이션에 간단하고 표준화된 방식으로 추가할 수 있도록 하여 생산성을 크게 높여줍니다."NVIDIA NIM은 모든 플랫폼에 통합되어, 모든 개발자에게 접근 가능하며, 어디서나 실행 가능합니다. 이는 기술 산업이 모든 조직에 생성형 AI를 제공할 수 있도록 도와줍니다."라고 NVIDIA의 창립자이자 CEO인 젠슨 황(Jensen Huang)은 말했습니다.이번 밋업을 통해 개발자들은 컴퓨텍스에서 새롭게 발표된 NVIDIA 개발자 프로그램을 통해 연구, 개발 및 테스트를 위해 무료로 NIM에 접근하는 방법과, 기업들이 엔터프라이즈 파트너십을 통해 NIM을 플랫폼에 통합하여 도메인 특화 애플리케이션을 위한 생성형 AI 배포를 가속화하는 방법을 배울 수 있습니다.이번 이벤트를 통해 다음을 배울 수 있습니다:NIM 소개 : 주요 기능과 이점NIM 구현 방법 (Screen captured 데모) - Llama-3 NIM이 새로이 오픈되었습니다!기업을 위한 주요 적용 사례인터랙티브 질의 응답 세션이번 밋업을 통해 NVIDIA NIM의 강력한 기능을 직접 경험하고, 생성형 AI 프로젝트를 신속하게 구현하는 방법을 배우시길 바랍니다.(C) NVIDIA Corporation 2024. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

Join us for a panel discussion on fostering career growth and learning in the fields of AI and other advanced technologies. Our panelists will share their unique career journeys, valuable insights, and tips and tricks for success.Discover how certifications and additional learning resources have played a pivotal role in shaping the careers of our panelists. Gain valuable advice on leveraging NVIDIA technologies and resources to accelerate your own professional growth. Whether you’re a student, a recent graduate, or a seasoned professional, this webinar will provide you with valuable insights and inspiration for navigating your career in AI and other technologies. Don’t miss this opportunity to learn from industry experts and gain valuable career guidance. Register now to secure your spot and kickstart your journey. By joining this webinar, you’ll:Learn how to navigate your career in AI and other technologiesBe able to Identify nontraditional career paths Explore extracurricular training and resources Understand the power of connections, LinkedIn, and certifications (C) NVIDIA Corporation 2024. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

工場デジタルツインの先にあるもの、それが仮想工場：バーチャルファクトリーです。生産ラインの計画、ロボットのシミュレーション、作業者のワークフロー、センサーの検証やIoT連携、さらには生成 AI の活用など、デジタル化が産業の効率化を更に推進します。本ウェビナーでは、国内での Omniverse を活用したデジタルツイン導入を推進いただいているパートナー様と共に実現可能な産業デジタル化の手法を探ります。アジェンダ仮想工場とは？最新事例とその手法エヌビディア合同会社 エンタープライズマーケティング シニアマネージャ 田中 秀明 / エンタープライズ事業本部 シニア ビジネス デベロップメント マネージャー 中嶋 雅浩生成 AI と OpenUSD、NVIDIA Omniverse は仮想工場の実現に向けたキーとなるソリューションです。最新事例と活用いただける資料をご紹介、さらにデジタルツイン構築の最初の関門であるデータ準備の実際をご案内します。Omniverseで仮想工場を実現する「CTC Omniverseデジタルツイン構築サービス」のご紹介伊藤忠テクノソリューションズ株式会社 エンタープライズビジネス企画本部 デジタルビジネス推進第 1 部 デジタルツイン推進課比留間 紀夫氏設計や製造の過程でデジタル化された仮想空間の中でシミュレーションや検討を行いたいというニーズが多く聞かれるようになってきました。その中でNVIDIA Omniverse（以下 Omniverse）を検討されているお客様も多くいらっしゃると思います。 Omniverseは非常に多くの機能を備えたプラットフォームであることから、いざ利用しようとしてもどこから始めて良いのか、どう課題が解決できるのかという事がわからないという声も良くお聞きします。 CTCではそういったお客様向けにOmniverseの活用を伴奏型サービスとして「CTC Omniverse デジタルツイン構築サービス」をご提供させていただいております。本講演では過去の事例などを交えて、本サービスがどのように活用いただけるのかご紹介させていただきます。フィジカルと時空を超えた製品レビュー空間『3D-MeasureVerse』東京貿易テクノシステム株式会社 営業企画部 先行開発チーム チーフエンジニア吉實 興二 氏精密な3D計測データをオムニバース空間(VR)に取り込み、実製品のレビューを他拠点間でリアリスティックに行える『3D-MeasureVerse』をご紹介いたします。(C) NVIDIA Corporation 2024. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

As organizations transition from generative AI experiments to deploying and scaling generative AI applications in production, the focus on production model deployment for inference—where AI delivers results—is growing. In addition to strategies that ensure data security and compliance while enabling flexibility and agility for innovation, enterprises need a streamlined, cost-effective approach to managing AI inference at scale.Join us for an engaging webinar where we'll explore key considerations for deploying and scaling generative AI in production, including the critical role of AI inference. Through real-world case studies highlighting successful enterprise deployments, we'll uncover best practices supporting enterprise data security and compliance, enabling developer innovation and agility, and unlocking AI inference for production applications at scale. Don't miss out on this opportunity to accelerate your enterprise journey to generative AI.By joining this webinar, you’ll explore:Challenges of and best practices for deploying generative AI to productionKey considerations and techniques for optimizing AI inferenceReal-world case studies of enterprise generative AI deploymentsResources and how to get started with NVIDIA software(C) NVIDIA Corporation 2024. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

ネットワークは現代のデータセンターのバックボーンであり、 AI 時代の到来により新しいワークロードへの対応が必要になります。たとえば、 大規模な AI モデルをトレーニングし、膨大な量のデータを処理するには、増加するノードを拡張して処理するネットワークの能力が不可欠です。 NVIDIA は、AI ネットワーキングに、NVIDIA Spectrum™-X Ethernet と NVIDIA Quantum InfiniBand という 2 つのオプションを提供しています。本ウェビナーでは、データセンターの未来を形成し、AI 時代を促進する上で、ネットワーキング テクノロジーが果たす重要な役割についてご紹介します。ウェビナー概要：AI がデータセンター設計に与える影響と、基礎モデルのトレーニングや生成 AI の導入などの主要なワークロードに対応する新しい要件NVIDIA Spectrum-X が AI 用に設計された世界初のイーサネット プラットフォームであり、AI クラウドに必要なマルチテナント、トラフィック負荷分散や輻輳制御によって生成 AIパフォーマンスを向上させる仕組みNVIDIA Quantum InfiniBand が、AI ファクトリーに必要な低遅延、スケーラブルなパフォーマンス、およびネットワーク内コンピューティングなどの独自の機能をどのように提供するかNVIDIA のデータセンター及びネットワークにおける取り組みにご理解を深めていただくとともに、皆さまのビジネスの一助にしていただければ幸いです。ご多忙の折とは存じますが、ぜひご参加いただけますよう、皆様のご参加をお待ちしております。(C) NVIDIA Corporation 2024. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

산호세에서 진행된 오프라인 행사에 아쉽게도 참석하지 못한 많은 분들을 위해 GTC 2024의 유일한 한국 세션이였던 "Korean AI Expert Day"를 다시 진행합니다.NVIDIA 전문가들이 직접 젠슨 황 CEO의 GTC 키노트의 내용을 요약 정리하고, 업계 내 AI 트렌드와 디지털 트윈 모범 사례들도 함께 공유할 예정입니다.주요 아젠다:GTC 2024 키노트 핵심 정리산업별 AI 디지털 트윈 우수 사례질의응답 (Q&A)(C) NVIDIA Corporation 2024. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

Clinical Large Language Models (CLLMs) are now a tangible reality in healthcare. Beyond their application in medical tasks, like drafting discharge summaries, they offer significant potential for workflow optimization and business intelligence. At University Hospital Essen, these technologies are being developed and integrated directly into patient care.In this webinar you will learn about recent advancements in the application of CLLMs:CLUE: A new benchmark to assess the clinical language understanding of LLMsRAW: Retrieval augmented writing of clinical documentsAn advanced medical vision language model that excels in visual downstream tasksFLAME (Fast, Language-Agnostic Metrics Engine) to enable quick and efficient medical data querying for informed decision-makingLearn more about NVIDIA LLM and Generative AI Solutions or visit the Clinic’s page for more details.(C) NVIDIA Corporation 2024. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

3 月 末に開催した NVIDIA 最大の AI カンファレンス「 GTC 2024」 では、アクセラレーテッド コンピューティング と 生成 AI を飛躍的に進化させる数多くの新技術やソリューション、そして次世代アーキテクチャー「Blackwell」を発表しました。当ウェビナーでは、これら GTC 2024 での主要な発表内容について、 NVIDIA日本法人の専門家より改めて詳細に解説いたします。また、マイクロソフト、アマゾンウェブサービス、デロイト トーマツ コンサルティング社にも登壇いただき、拡大するエコシステムがもたらすソリューションやビジネス価値もご紹介します。NVIDIA が創り出す未来とその実現を支える技術に関する理解を深め、皆さまのビジネスや取り組みの一助にしていただければ幸いです。皆さまのご参加をお待ちしております。【お問合せ】 NVIDIA セミナー事務局 Email : GTC_Japan@nvidia.com(C) NVIDIA Corporation 2024. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

Pharmaceutical researchers are continually on the quest for better, faster ways to design drugs, but juggling independently designed software and data sources has created a long-standing challenge. NVIDIA and OneAngstrom have collaborated to reduce this fragmentation. Join the discussion and see how molecular design is more accessible than ever before.In this webinar, you’ll learn how: Integrative molecular modeling results in streamlined, state-of-the-art workflows for scientists To access NVIDIA BioNeMo™ in just a few clicks to predict protein structures and dock libraries of ligands directly To combine BioNeMo with all other extensions available in SAMSON for modeling, simulation, analysis, visualization, scripting, and more Visit the BioNeMo page for more details.(C) NVIDIA Corporation 2024. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

Learn how generative AI and large language models can be used in quantitative finance applications.(C) NVIDIA Corporation 2024. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

The rising popularity of generative AI, showcased by applications like ChatGPT, is reshaping how industries will create their products, provide their services, and run their operations. Yet, almost every organization faces challenges when integrating AI.NVIDIA’s accelerated computing systems with NVIDIA BlueField-3 data processing units (DPUs) provide the optimal infrastructure to develop, deploy, and scale generative AI applications.Join our live webinar to explore the role of BlueField DPUs in accelerated cloud computing in the era of generative AI.Webinar attendees will understand the:Difference between generative AI infrastructure and general-purpose cloud infrastructureFeatures and capabilities of BlueField-3 DPUs and how they power NVIDIA AI infrastructureBenefits of incorporating BlueField-3 DPUs into AI servers, including improved performance, efficiency, and security in AI cloud data centersDiscover more about NVIDIA BlueField-3 DPUs.(C) NVIDIA Corporation 2023. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

在市場極具競爭的環境下，效率與良率成為增強製造業核心競爭力的關鍵。使得企業開始思考透過如數位孿生這項新興數位轉型技術，可以提高效率、降低成本、改進生產過程、並提供更優質的產品品質。數位孿生是一種強大的工具，顧名思義是將虛擬模型和實際工廠環境結合起來，透過虛實模擬、監控、分析及優化廠房與產線，強化工廠效率與靈活彈性，可以更好地應對市場變化和挑戰。NVIDIA 強大的即時繪圖與模擬技術可以透過 NVIDIA Omniverse 與通用場景描述 (OpenUSD) 來實現，與業界知名 3D 模擬建模和分析工具 FlexSim 結合，能協助客戶根據客製化需求建立數位孿生協作平台，打破資訊孤島的限制，讓數位工廠的建立更有效率地完成。本次線上研討會將分享此改變遊戲規則的解決方案，實現數位孿生在製造業和工廠生產作業中，創造巨大的潛在價值，可以協助企業更靈活、敏捷地應對市場變化，提高競爭力。參與本次線上研討會您將能瞭解：製造業及生產規劃創新技術趨勢與市場挑戰全方位產業數位孿生技術與工具(C) NVIDIA Corporation 2023. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

To stay competitive in today's rapidly evolving tech landscape, integrating AI into business operations isn’t just a choice anymore—it’s become a necessity.Large language models (LLMs) have gained immense popularity, but they face challenges: They’re prone to hallucinations and have trouble understanding domain-specific topics. Retrieval-augmented generation (RAG) is a groundbreaking leap in AI technology that lets businesses leverage the power of domain-specific, real-time data like never before.By joining this webinar, you’ll learn:How chatbots, AI assistants, and copilots are transforming the way businesses operateThe basics of retrieval-augmented generation as a powerful technique driving enterprise generative AI applicationsKey use cases that are being accelerated with AI-powered assistantsConsiderations for building safe, secure AI chatbots that stay on task(C) NVIDIA Corporation 2023. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

Diffusion models have emerged as invaluable tools for modern-day Da Vinci’s, revolutionizing image generation by producing intricate, composable visual outputs. With a diverse array of over 100 diffusion models available, each possessing its unique stylistic prowess, creators can seamlessly choose a model and prompt it to generate their desired artwork. Given the computational intensity of diffusion models, they find a natural ally in GPUs, capitalizing on their processing power for enhanced performance.This enlightening session aims to delve into the art of optimizing the latest iteration of stable diffusion models, including SDXL-1.0, using the powerful capabilities of NVIDIA TensorRT. In the realm of image generation, achieving the desired output often necessitates multiple prompts. Moreover, in scenarios where numerous creators concurrently request multiple images, the imperative of optimizing comes to the forefront. By meticulously leveraging TensorRT's optimization techniques, attendees will witness a significant reduction in inference times for image generation in comparison to CPU-based execution and unoptimized models.Who should attend: A data scientist who is interested in developing and deploying large-scale SD modelsDesigners (2D/3D, interior designers) with the ability to quickly produce artifactsIn this webinar you will learn:Generating such realistic images requires a high level of computation, which explains the role of GPUs.Understand how GPUs can satisfy such compute requirements and generate images even more rapidly.Optimizing the existing models using Nvidia SDK so that it runs even faster on a single GPU or on hundreds of GPUs at once(C) NVIDIA Corporation 2023. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

이 세션에서는 규모 있는 LLM 서비스를 운영하는 조직을 대상으로 자체 관리 중인 하드웨어 - 클라우드 또는 온프레미스에서 LLM 최적화 및 배포 과정을 통해 가시적인 효율성, 데이터 거버넌스, 비용 개선 효과를 얻을 수 있다는 점을 보여드립니다. 이 세션에서는 일반적으로 사용 가능한 하드웨어에서 실행할 수 있는 상용 라이센스가 있는 개방형 LLM에 대해 논의하고, 옵티마이저를 사용하여 지연 시간을 단축하고 처리량을 높여 컴퓨팅 요구 사항을 줄이는 방법을 보여드립니다. 참석자들은 비즈니스 요구사항에 맞게 자체 관리형 LLM을 확장할 수 있는 능력을 갖추게 됩니다. 더불어, 사용자가 LLM을 정의하고 멀티 노드 GPU에서 추론 최적화 TensorRT 엔진을 빌드할 수 있는 TensorRT-LLM의 최신 기술 업데이트를 함께 살펴봅니다. 세션 관련 사전 질문은 다음 링크를 통해 제출을 부탁드립니다. -https://forms.gle/mcNP5TKRVMTPh6pV7(C) NVIDIA Corporation 2023. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

이번 세션에서는 LLM을 도메인별 애플리케이션에 맞게 튜닝하여 기성 API의 품질 한계를 뛰어넘을 수 있는 방법을 소개합니다. 데이터 세트를 준비하는 전략을 논의하고, 해당 데이터 세트에 대한 파인튜닝 방법을 비교하며, 파인튜닝이 NVIDIA 사용 사례에 미친 영향에 대한 예를 보여줄 것입니다. 참석자들은 API 기반 및 자체 관리형 LLM 모두에 적용할 수 있는 기술을 배우게 됩니다. 세션 관련 사전 질문은 다음 링크를 통해 제출을 부탁드립니다. -https://forms.gle/mcNP5TKRVMTPh6pV7(C) NVIDIA Corporation 2023. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

이 세션에서는 특정 하드웨어나 모델 학습, 까다로운 배포 없이도 바로 사용할 수 있는 대중적인 LLM API를 사용해 실제 비즈니스 데이터에서 LLM 기반 시스템을 설계하고 구현하는 구체적인 방법을 소개합니다. 모델에 대한 효과적인 입력("프롬프트")을 설계하는 기법과 비즈니스 데이터베이스를 포함한 다른 시스템과 LangChain과 같은 워크플로우 프레임워크를 통해 LLM을 활용하는 방법에 대해 논의할 것입니다. 참석자들은 실질적인 비즈니스 성과를 창출할 수 있는 LLM 시스템을 구축할 수 있는 실질적인 기술을 배우게 됩니다. 세션 관련 사전 질문은 다음 링크를 통해 제출을 부탁드립니다. -https://forms.gle/mcNP5TKRVMTPh6pV7(C) NVIDIA Corporation 2023. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

In today’s rapidly evolving world, generative AI is paving the way to enterprise innovation and success. Join this upcoming webinar to explore the art and science behind building generative AI applications. We’ll guide AI teams through the intricacies of data acquisition, highlight the pivotal role of data curation, and unveil key insights for effective model training.Attendees will learn:How to build generative AI applications, from data acquisition to model deployment, includingWhat AI teams need to know about data acquisitionWhat data curation does and why it’s necessaryKey concepts behind model trainingSizing considerations for model trainingVarying levels of model customization, top use cases for each customization technique, and how a business should evaluate and determine its solution.Explore the NVIDIA generative AI platform and sign up for generative AI news from NVIDIA.(C) NVIDIA Corporation 2023. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

これまで、シンクライアントの運用管理コストを低減したり、情報漏洩やマルウェア感染を防げたりといったメリットが注目され、多くの企業で導入されました。しかし、従来のシンクライアント (VDI、SBC方式) は物理PCに比べて動作が遅く、高度なグラフィックアプリケーションや何窓も開いたWebブラウザに耐えられないという弱点がありました。そこで、新たに脚光を浴びているのが『新(シン)・シンクライアント』です。このソリューションは、セキュリティを担保しながら、ビッグデータを利用した計算やグラフィックス処理といった業務も実施できるのが特徴です。Web会議・動画再生・3D CAD・解析・映像制作・レンダリング・生成AI・デジタルツインといった、時代の最先端を行くアプリケーションにも対応しています。謎のソリューション、『新(シン)・シンクライアント』の全貌とは？管理者やエンドユーザー、それぞれにとっての導入メリットとは？主な内容:『新(シン)・シンクライアント』が広げる働き方の可能性『新(シン)・シンクライアント』の導入メリット【対　象】 AI やメタバースを活用したビジネスや研究開発にご関心のある企業、組織、教育機関の方々​【主　催】 エヌビディア 合同会社​【参加費】 無料 / 事前登録制​【お問合わせ】 NVIDIA セミナー事務局 Email : GTC_Japan@nvidia.com(C) NVIDIA Corporation 2023. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

Dr. Tychele Turner, from the Washington University School of Medicine in St. Louis, will present her lab's development of a computational workflow, called HAT, to detect de novo variants from whole-exome and whole-genome sequencing datasets. She’ll detail the development of this hybrid CPU/GPU workflow and discuss the application to >6,000 parent-child sequenced families. Dr. Turner will also describe her lab’s utilization of GPUs in detecting variants from long-read sequencing data.Dr. Turner’s talk will focus on areas of particular utility of GPU-based acceleration of genomic tools, including her lab’s use of NVIDIA Parabricks®, a suite of GPU-accelerated and deep learning industry-standard genomics analysis tools for next-generation sequencing data.In this webinar you will:Understand what a de novo variant is and how it is detected from sequencing dataLearn key uses of deep learning-based variant calling to detect de novo variantsIdentify key differences between short- and long-read sequencingLearn key uses of GPU-based acceleration to assess long-read sequencing dataNVIDIA Parabricks is free for anyone. Download it today to try it out on your DNA and RNA data. (C) NVIDIA Corporation 2023. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

When customers reach out to telco contact centers, they expect prompt and efficient solutions delivered in their native languages. But communication challenges and a lack of helpful information often result in a stressful, frustrating experience for customers and agents. To address this challenge, telecommunication companies are implementing innovative speech and translation AI to improve agent assist solutions in multiple languages, empowering their contact center agents to deliver the best possible personalized customer experience.Join this webinar, featuring demos by Infosys, Quantiphi, and NVIDIA conversational AI experts, to learn:How to kickstart your journey with NVIDIA® Riva’s cutting-edge speech and translation AI and fully customize it to achieve the highest-accuracy agent assist solution Best practices for seamlessly integrating speech and translation AI into agent assist solutions, ensuring smooth and effective customer-agent communication Real-world examples showcasing successful implementations of multi-language, speech AI-customized agent assist solutions in telco contact centersClick here to register for part one of this webinar, How Telcos Transform Customer Experiences With Conversational AI, a high-level session with Quantiphi, Infosys, TalkMap, and NVIDIA on May 31.(C) NVIDIA Corporation 2023. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

Telcos are introducing speech AI-based applications such as agent assists, AI virtual assistants, and digital avatars to improve customer service, self-service, and satisfaction. But building highly scalable speech AI-based applications that learn from conversations, detect customer preferences, make personalized recommendations, and engage dynamically in real time isn’t easy. With NVIDIA® Riva, telcos can build accurate, real-time, conversational AI applications with customizable pipeline solutions that seamlessly integrate with telco service workflows. Join Infosys, Quantiphi, Talkmap, and NVIDIA to learn how telecommunications companies are using AI to improve operational efficiency and enhance customer engagement.By joining this webinar, you’ll learn:The state of the customer experience in telecommunicationsHow Riva can enhance customer experiences in contact centers with Infosys, Quantiphi, and Talkmap solutions The future of speech AI in telecommunications Click here to register for part two of this webinar, Empowering Telco Contact Center Agents With Multi-Language Speech AI-Customized Agent Assists, a technical webinar with Quantiphi, Infosys, and NVIDIA on June 7.(C) NVIDIA Corporation 2023. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

Apache Spark has become the leading framework for large-scale distributed data processing. Retailers are already using it for many core business functions, such as demand forecasting, price optimization, and sales performance analysis. Join the webinar “Improve Retail Business Outcomes With GPU-Accelerated Apache Spark” to learn how NVIDIA can help retailers run workloads 5X faster with up to 4X cost savings on leading platforms such as Google Cloud Dataproc, Amazon EMR, and Databricks. In this webinar you’ll learn:How NVIDIA technology accelerates Apache Spark—without code changes.How accelerated Spark enables leading retailers to transform their business by enabling workflows that were previously impossible.How to get started, including with an NVIDIA tool that estimates cost savings and the acceleration potential of Apache Spark workload(C) NVIDIA Corporation 2023. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

Robots are real-time systems which require complex graphs of heterogeneous computation to run applications deterministically. The ros2_benchmark provides tools for measuring the throughput, latency, and compute utilization of these complex graphs. Learn how to run and customize ros2_benchmark to measure your robotics application graphs of nodes.In this webinar we’ll cover: Introduction to ros2_benchmarkStandard data for benchmarking using rosbagRunning a ros2_benchmarkRunning an accelerated computing benchmark with Isaac ROSCreating a custom benchmark configuration(C) NVIDIA Corporation 2023. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

面對全球永續發展的趨勢，製造業的淨零碳排行動勢在必行。如何在設計流程中做碳足跡生命週期的評估，達到低碳設計製造的目標而使產品更具競爭優勢，是各大企業迫在眉睫要面對的。本次線上研討會將匯聚 NVIDIA 專業創新技術與達梭系統 3DEXPERIENCE® 平台，從人工智慧和虛擬實境到物理渲染、繪圖虛擬化與即時工程模擬等，協助製造業擺脫傳統產品開發工作流程，徹底改善設計團隊的協作方式。將透過逼真的模擬加快評估材料和產品的效能、可行性與可靠性，優化工程模擬與設計以加速實現淨零碳排的願景。參與本次線上研討會您將能瞭解：如何透過適當的工具與技術面對淨零碳排的挑戰結合 NVIDIA 最新 RTX Ada 世代技術與達梭系統平台的綜合效益(C) NVIDIA Corporation 2023. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

The promise of edge AI has many worthwhile benefits for your organization. Join NVIDIA and Lenovo to learn how we are enabling organizations to bring automation, efficiency and improved consumer experiences to their operations. While many organizations have edge computing strategies in place today, 75% of the edge AI projects in motion never make it to production.In this session, we’ll look at:• Key benefits driving growth of edge computing• Multi-Industry use cases for edge AI• How to build and complete your AI strategy with Lenovo from data center to the far edge• Tips for establishing a successful edge AI proof of concept(C) NVIDIA Corporation 2023. All rights reserved. No recording of this webinar should be made or reposted without the express written consent of NVIDIA Corporation.

In today's financial market, processing millions of packets per second at low latency gives organizations the ability to take decisive action at just the right time. Recent innovations in CUDA® and GPU architectures, along with NVIDIA DOCA™ and DPU processing, are making the concept of GPU-accelerated, low-latency applications a reality.Systems that are architected for low latency can exhibit spikes in latency when the consumer system's processing capability becomes saturated. GPUs provide new processing capabilities not previously exploited in these types of environments. Many financial Institutions like exchanges, hedge funds, or data providers can benefit from solutions that leverage NVIDIA networking and GPU technologies.Join our webinar to explore the hardware and software stacks that enable new workloads in this low-latency space.By attending this webinar, you'll:Learn about financial use cases, such as market data ingest, that can benefit from NVIDIA DPU and GPU accelerationUnderstand the benefits and capabilities of new NVIDIA converged accelerator hardwareUnderstand the role of software architectures, such as DOCA and CUDA, and components to build accelerated solutions

Complex workloads and extreme datasets are placing enormous demands on supercomputing infrastructures. In addition, cloud providers hosting scientific workloads require their infrastructures to deliver bare-metal performance. All of these complexities require a best-in-class networking platform, that’s programmable, and includes hardware acceleration engines to provide faster time to insight. Join Hyperion, NVIDIA and experts from Microsoft Azure, The Ohio State University and Max Planck Institute/Society for a live discussion on using InfiniBand, In-Network Computing and the capabilities of the DPU to boost performance and drive your scientific computing innovation. By attending this webinar, you will learn: How BlueField DPUs can offload communication frameworks and increase application performance How BlueField DPUs enable adaptive performance isolations, ensuring bare-metal performance for scientific workloadsHow the NVIDIA Quantum-2 InfiniBand networking platform empowers supercomputing and cloud data centers with advanced In-Network Computing acceleration engines, and the fastest speeds and feeds up to 400Gb/s

Complex workloads and extreme datasets are placing enormous demands on supercomputing infrastructures. In addition, cloud providers hosting scientific workloads require their infrastructures to deliver bare-metal performance. All of these complexities require a best-in-class networking platform, that’s programmable, and includes hardware acceleration engines to provide faster time to insight. Join Hyperion Research, NVIDIA and experts from Microsoft Azure, Ohio State University and Max Planck Computing and Data Facility (MPCDF) for a live discussion on using InfiniBand, In-Network Computing and the capabilities of the DPU to boost performance and drive your scientific computing innovation. By attending this webinar, you will learn: How BlueField DPUs can offload communication frameworks and increase application performance How BlueField DPUs enable adaptive performance isolations, ensuring bare-metal performance for scientific workloadsHow the NVIDIA Quantum-2 InfiniBand networking platform empowers supercomputing and cloud data centers with advanced In-Network Computing acceleration engines, and the fastest speeds and feeds up to 400Gb/s

Financial services companies are under pressure to provide efficient, personalized 24/7 customer service while enhancing their customers’ experience. To address these demands, businesses are deploying intelligent virtual assistants in the form of voice-enabled digital agents that save time for customers and human agents by offering effective customer self-service and improving customer satisfaction scores. Building a highly scalable intelligent virtual assistant with state-of-the-art speech recognition that learns from conversations with customers, detects customer preferences, makes personalized recommendations, and engages with customers in real time and with an expressive voice is not an easy task. NVIDIA’s Intelligent Virtual Assistant reference application, built with NVIDIA Riva and available with NVIDIA AI Enterprise, provides a flexible, fully customizable solution that seamlessly integrates with financial service workflows. By joining this webinar with hands-on demos, you’ll learn how to: Build a simple but complete voice-enabled, microservice-based intelligent virtual assistant for customer/employee workflows at contact centersCustomize speech recognition for your specific domain use case and speech synthesis for brand voice reflecting your company identityDeploy, scale, and monitor a fleet of intelligent virtual assistants on a cloud for efficient, high-quality, 24/7 service

Software-defined vehicles are transforming business models and the customer experience. To support this fundamental shift, metaverse applications for virtual collaboration and digital twin creation are helping automotive companies redesign the development process from vehicle design and visualization, manufacturing, to the dealership experience, and autonomous driving.In this webinar, you will learn how:DRIVE Sim provides the digital twin environment to train, test, and validate autonomous driving systemsNVIDIA Omniverse enables the development and operations of factory digital twins, harmonizes the flow of design data across the enterprise, and accelerates visualization for in-vehicle experiences, car configurators, and virtual showrooms

Software-defined vehicles are transforming business models and the customer experience. To support this fundamental shift, metaverse applications for virtual collaboration and digital twin creation are helping automotive companies redesign the development process from vehicle design and visualization, manufacturing, to the dealership experience, and autonomous driving.In this webinar, you will learn how:DRIVE Sim provides the digital twin environment to train, test, and validate autonomous driving systemsNVIDIA Omniverse enables the development and operations of factory digital twins, harmonizes the flow of design data across the enterprise, and accelerates visualization for in-vehicle experiences, car configurators, and virtual showrooms

To meet the demands of today’s architecture, engineering, construction, and operations (AECO) teams, firms now turn to virtual workstations to run resource-intensive applications and process large amounts of data. As one of the first NVIDIA virtual GPU (vGPU) customers, HFA, a leading architecture and engineering firm, has relied on NVIDIA vGPU technology to power demanding 3D design workflows while taking advantage of the IT and security benefits of virtualization. In this webinar, you will:Learn about HFA’s journey using NVIDIA technology, from an early-generation NVIDIA K1 to the latest NVIDIA A40 GPUsExplore how NVIDIA vGPU technology optimizes user experience and performance for graphics-intensive applications like Revit, Enscape, and SketchUp, as well as for productivity applications like Microsoft OfficeLearn how HFA enables its employees to work effectively on any device, from thin clients to workstations

Financial organizations are facing an ever-increasing pressure to digitize and modernize their front, middle, and back offices. Solutions such as natural language processing (NLP) for environmental, social, and governance (ESG) activity, trading, fraud detection, document digitization, and speech AI enable companies to increase revenues, reduce operational costs, and enhance customer experiences. Financial institutions are looking at unstructured data to develop application workflows in these solution areas, and AI is key to this digital transformation. Red Hat and NVIDIA are working together to help clients build an AI platform that can accelerate key use cases and be deployed at scale both on premise and in hybrid clouds. By attending this webinar, you will learn: How you can use deep learning at scale to address key unstructured data and real-time analyticsHow you can leverage an AI platform built for training, transfer learning, and inferencing, from proof of concept to production About an AI-as-a-service (AIaaS) platform that can support both build-your-own and partner solutions securely in compliance with industry regulations

NVIDIA License System (NLS) is a licensing solution to support the continued expansion of the NVIDIA enterprise software portfolio. As the legacy NVIDIA vGPU license server will reach end-of-life on July 31, 2023 and is no longer supported with the release of vGPU 15.0.starting your NVIDIA vGPU license migration to NLS is highly recommended. Join this webinar to learn more about NLS and the migration process.In this webinar, we will cover:NLS solutions and how to select the best one for your use caseMigration planning and best practicesLIVE demos of the migration processTraining and other resourcesQ&A

In the last decade, there have been dramatic advances in the field of computer-aided drug discovery. Researchers can now better understand causal biology, more effectively search through chemical space, and design de novo molecules that aim to treat disease. In this presentation, we will provide an inside look into: How Schrodinger uses NVIDIA-powered solutions to drive their in-silico drug discovery platform and recent NVIDIA optimizations to the Schrodinger suite. How organizations can easily implement the Schrodinger platform at scale, on premises, or in the cloud.

Investment banks, hedge funds, and asset management firms face one of their greatest computing challenges when it comes to large-scale risk simulations and derivative pricing. Whether looking backward or forward in time to realized and unrealized price scenarios for their trade portfolios, they’re beginning to turn to the natural parallelism of quantum computing to solve computational finance problems. While the field of quantum computing shows great promise for solving a broad range of problems within financial services, these applications and algorithms will require thousands, if not millions, of qubits. With physical quantum computers of this scale and quality far off, quantum circuit simulation is the best and only way to scale up algorithm and application design in the interim. With NVIDIA GPUs and cuQuantum, you can accelerate quantum circuit simulation, enabling you to experiment with more qubits (and gate depth) faster than ever before, so you can prepare for tomorrow, today.By attending this webinar, you'll learn:The history of quantum computing and how it has impacted the financial engineering world Fundamentals of NVIDIA GPUs and where they shine for quantum computing simulation Specifics about the NVIDIA cuQuantum package for state vector and tensor networks How to develop quantumaccelerated applications with QODA

Automotive OEMs, mapping companies, and ISVs are developing high-definition maps using an array of sensors to enable autonomous driving and open new business models. These companies are all working together to develop HD maps that will enable safe autonomous vehicle deployment and efficient transport of people and goods, creating new business models and services in mobility, delivery, and logistics markets.In this webinar, experts will provide an overview of how the new technologies, such as the NVIDIA RAPIDS set of GPU-accelerated libraries running on NVIDIA A100 GPUs, can help mapping and location-based service providers exponentially speed up their map-creation and location-based services workflows while reducing overall costs.

As the number of sensors in modern vehicles continues to grow, automotive OEMs, mapping companies, and ISVs are developing high-definition maps to enable autonomous driving and open new business models. Mapping companies, automotive OEMs, and ISVs are all working together to develop HD maps that will enable safe autonomous vehicle deployment and efficient transport of people and goods, creating new business models and services in mobility, delivery, and logistics markets.In this webinar, experts will provide an overview of how the new technologies, such as NVIDIA RAPIDS set of GPU-accelerated libraries running on NVIDIA A100 GPUs, can help mapping and location-based service providers exponentially speed up their map-creation and location-based services workflows while reducing overall costs.

Vision and conversational AI technologies are becoming ubiquitous, with countless applications taking advantage of object detection, image segmentation, action recognition, OCR, automatic speech recognition, natural language understanding, and speech synthesis coming to market. This webinar will present tools and technologies making the development of AI applications easier than ever.We will start with an overview of the conversational AI landscape, and how you can build and deploy accelerated applications with state-of-the-art models using RIVA and NeMo. Then we will present DeepStream, a complete streaming analytics toolkit for AI-based multi-sensor processing, video, audio and image understanding. Finally, we will also introduce the TAO toolkit and pre-trained models giving you a faster, easier way to accelerate training and quickly create highly accurate and performant, domain-specific AI models.By attending this webinar, you will:• Get started with speech and vision AIs• Learn Key components for building real-time AI applications• Train smarter with TAO Toolkit and finetuning

NVIDIA DRIVE Orin has now entered production, delivering a major leap in deep neural network (DNN) inference performance.In this webinar, we will cover DNN architectural designs, as well as the scope of NVIDIA TensorRT and real-world use cases to deliver optimized inference engines for production. We will also demonstrate how to obtain deterministic results as needed in production.In this webinar, you will learn:The newest features of TensorRT 8 on NVIDIA DRIVE OrinHow to optimize the performance of NVIDIA DRIVE OrinHow to apply TensorRT 8 to state-of-the-art DNNs, improving throughput and latency

NVIDIA DRIVE Orin has now entered production, delivering a major leap in deep neural network (DNN) inference performance.In this webinar, we will cover DNN architectural designs, as well as the scope of NVIDIA TensorRT and real-world use cases to deliver optimized inference engines for production. We will also demonstrate how to obtain deterministic results as needed in production.In this webinar, you will learn:The newest features of TensorRT 8 on NVIDIA DRIVE OrinHow to optimize the performance of NVIDIA DRIVE OrinHow to apply TensorRT 8 to state-of-the-art DNNs, improving throughput and latency

Join this webinar to find out how performance-optimized AI software from the NVIDIA NGC™ catalog helps companies build ML-powered applications faster.

AI Training and Inference applications have requirements that are unlike those of traditional business applications. Systems for training need to be carefully designed to maximize performance, and systems for Edge Inference have their own unique requirements due to their deployment location. By attending this webinar, you will learn how to configure servers for these workloads, and how NVIDIA makes it easy for enterprises to choose a full platform solution for these use cases.By attending this event you will learn:The hardware requirements of AI training and inference workloadsHow the NVIDIA-Certified Systems program offers enterprises an easy way to choose GPU-accelerated systems for AIThe NVIDIA platform for Enterprise AI, and how to get started

迎向智慧科技時代，製造業該如何搭上數位轉型熱潮，即時因應並布局成為探討重點。在面對各種產品生命周期越來越短、產品的少量多樣性等「內憂」製造挑戰時，以及市場上各種新興科技 AI 智慧製造、Metaverse、數位孿生 (Digital Twins) 等「外患」衝擊時，企業應該如何穩住陣腳並突破當前的「內憂外患」以提高生產力與產業競爭力。NVIDIA 聯手全球製造業電腦輔助設計 (CAD) 龍頭 PTC 期望透過完整且直觀的工具、AI 加值應用與數位體驗平台 Omniverse 三大面向提供製造業在產品設計、模擬與驗證等流程上的全新體驗。協助於您加速產品創新，進而更快地建構更多優秀的產品。參與本次線上研討會您將會瞭解：當製造業遇上數位轉型旅程之趨勢分析與各企業所面臨之挑戰如何運用適當的工具與新興科技提供製造業產品設計、模擬與驗證最佳解方

隨著 AI 與 5G 興起，各國半導體晶片需求日益擴大，且對於晶片設計的要求與複雜性也無止境的增加：希望新晶片設計可以不斷增加閘極數量、極小化晶片尺寸以及大幅縮短上市時間等。此時電子設計自動化 (EDA) 在其中扮演越來越吃重的腳色。從系統架構設計開始、落實到功能的定義與實現，以及最終實現整個晶片的設計與驗證，若沒有 EDA 輔助，設計這樣複雜的電路並同時保證良率是很難達到的。NVIDIA 作為全面整合的運算平台，與 Cadence 共同推動為積體電路設計 (IC design)、系統單晶片 (SoC) 以及印刷電路板 (PCB) 等提供完整的 EDA 工具，更以獨特的演算法利用大量高效運算 CPU 核數及 GPU 大幅減少求解時間。為台灣晶圓製程研發、製造與代工供應鏈提供最佳解，加快晶圓設計與驗證。參與本次線上研討會您將會：瞭解 IC 系統設計之現況與挑戰，並瞭解如何透過高效能運算 (HPC)、人工智慧 (AI) 及機器學習等技術解決此挑戰認識 Cadence 專為晶片、PCB到電路板設計提供完整策略工具，透過 GPU 平行運算協助工程師加快產品設計與上市