Name: Generative AI: Optimizing Deployment with NVIDIA NIM on AWS
Start: 2025-03-12T13:44:00Z
End: 2025-03-12T13:44:56.000Z
Location: BrightTALK

Amazon Web Services (AWS) and NVIDIA have collaborated since 2010 to continually deliver large-scale, cost-effective, and flexible GPU-accelerated services for customers. Explore the interview and webinar resources in this channel to discover how their collaboration empowers millions of developers to access cutting-edge technologies essential for driving rapid innovation in generative AI.

Digital fraud is evolving rapidly, becoming more complex and harder to detect. Recent estimates forecast that payment fraud will exceed $362 billion between 2023 and 2028, with remote purchases of physical goods accounting for over 47 percent of fraud losses. 

By 2026, financial losses from global credit card transaction fraud alone are expected to reach $43 billion. This is just one of the many threats financial institutions must address, others include identity theft, account takeovers, authorized push payment fraud, check scams, and more. 

Traditional methods of fraud detection, including rules-based systems, statistical modeling, and manual reviews, struggle to keep pace with the scale and sophistication of modern threats. Fraud detection powered by artificial intelligence (AI) offers a transformative solution, enabling financial institutions to stay ahead of evolving fraud tactics. 

During this discussion, AWS and NVIDIA industry experts will share insights on how financial institutions can harness AI to strengthen fraud detection. Learn how to: 
● Identify subtle patterns and anomalies in transaction data based on user behavior to improve detection accuracy and reduce false positives
● Deploy accelerated computing infrastructure to manage increasing data volumes
● Utilize modern technologies, like graph neural networks and transformer architectures, to further enhance AI-powered fraud detection systems 

Discover how AI-driven solutions can help financial institutions detect fraud in real-time, enhance security, and build greater customer trust.

Using AI for scalable, accelerated fraud detection in financial services

In this Bio-IT World session we explore how ConcertAI—a leading oncology-focused AI technology company—is accelerating clinical trials and research through its proprietary platform, CARA.ai Powered by advanced generative AI, CARA integrates ConcertAI’s proprietary AI solutions with AWS Cloud and NVIDIA microservices, including NIM and BioNeMo, to enable a scalable, multi-agent framework development. CARAai supports the processing of large-scale clinical data, management of predictive models, and rapid product development. By leveraging NVIDIA’s tools on AWS infrastructure, ConcertAI efficiently builds comprehensive knowledge graphs and develops applications that address critical components of clinical solution development—from optimizing eligibility criteria and site strategy to improving patient matching, enrolment forecasting, and trial execution.

Harnessing the power of generative AI with CARA, ConcertAI’s clinical and research accelerator platform

This session details how AWS and NVIDIA are working together to accelerate Drug Discovery workloads. Learn how biopharma solutions like NVIDIA BioNeMo, NVIDIA NIM and NIM Agent Blueprints on AWS, can help companies discover and develop drugs faster—and at a lower cost. We will cover joint solutions for common drug discovery workloads like running large scale omics using AWS HealthOmics with NVIDIA NIM, streamlining AI workload and GPU orchestration using Run.ai and Amazon SageMaker HyperPod, and training protein and fine-tuning frontier language models (fLMs) using DGX Cloud on AWS. Learn from real-world success stories, such as Amgen and the Arc Institute, who leverage these technologies to train state-of-the-art protein language models (pLMs) and BioLLMs, driving innovation in drug discovery.

AI-powered drug discovery and clinical applications

Evozyne is a biotechnology startup based in Chicago that combines deep learning and the principles of evolution to design novel protein therapeutics.  Evozyne will discuss the development of a generative AI model built on NVIDIA’s BioNeMo platform running on AWS to create two new proteins with supernatural function and potential in therapeutics and sustainability. The developed large language models (LLMs) outperform traditional protein engineering approaches, such as directed evolution, by enabling the production of functional synthetic molecules with hundreds of mutations in a single round. In this webinar, the essential role of large, pre-trained models and libraries provided by BioNeMo to unlock such generative design will be reviewed, as well as the benefits cloud computing has provided in storage, automation, and parallelization over on-premises options.

Utilizing generative AI for drug discovery in the cloud

Discover how biopharma researchers can deploy large language models for generative biology and chemistry through an easy-to-use interface.

NVIDIA BioNeMo, a generative AI platform for drug discovery that simplifies and accelerates training models, on AWS ParallelCluster cluster management tool for high performance computing and Amazon SageMaker for machine learning, enables researchers access to BioNeMo’s collection of containers used for generative AI and protein structure visualization.

Generative AI distributed training for drug discovery workloads with AWS and NVIDIA

With global credit card transaction fraud anticipated to cost $43 billion by 2026, financial institutions are turning to advanced AI to boost transaction security and strengthen fraud prevention. By identifying subtle patterns and anomalies in transaction data rooted in user behavior, AI improves detection accuracy and reduces false positives compared to traditional methods.

In this webinar, Financial Services industry experts from Amazon Web Services (AWS) and NVIDIA will explore how financial institutions can utilize advanced AI models, like graph neural networks and transformers, to build and deploy fraud detection models that offer scalable, low-latency, and high-throughput predictions, ensuring the safety of customers’ money, identities, and digital accounts. 

Key Takeaways: 
• Understand cost-savings associated with scaling large AI models for improved fraud detection
• Mitigate risk with fewer false positives and real-time decisions
• Adapt AI workflows for use cases such as account takeover and money laundering

Watch this webinar to learn how AI-powered solutions from AWS and NVIDIA can help you quickly detect and prevent fraud to increase customer trust and improve service quality.

Enhance Fraud Detection with AI and Accelerated Computing

It can take years, and cost billions, to get new drugs approved for clinical use but technological advances are transforming drug discovery and development. 

The growing shift towards artificial intelligence (AI), including generative and predictive AI, can reduce the amount of time and money it takes to develop new drugs. It offers the potential to drastically shorten the early stages of drug discovery and help identify future drug candidates faster.

Hear from AWS and NVIDIA experts and discover how high performance computing (HPC) and AI are being used to screen out potentially dangerous drugs, improve identification of drug candidates, and develop new therapeutic compounds.

Learn how:
• To overcome common challenges from data quality, managing multi-modal data, and limited computational resources
• Generative AI is impacting and accelerating the drug discovery process
• Accelerated compute and purpose-built tools can help build, run, and train generative AI workloads

The benefits of generative AI in every stage of drug discovery

In this webinar, AWS and NVIDIA explore how NVIDIA NIM on AWS is revolutionizing the deployment of generative AI models for tech start-ups and enterprises. As the demand for generative AI-driven solutions in areas like chatbots, document analysis, and video generation surges, the complexity of deploying large-scale generative AI models presents significant challenges. 

This discussion will focus on what these challenges are and how NVIDIA NIM microservices can solve various pain points. Find out what the strategic advantages of adopting NVIDIA NIM on AWS are and how enhanced infrastructure efficiency, robust security measures, and reduced operational costs can empower tech leaders to accelerate innovation and maintain a competitive edge in the rapidly evolving generative AI landscape. We'll also demonstrate how to deploy an audio bot to Amazon Elastic Compute Cloud (Amazon EC2) using NIM.

Join our presenters, Court Schuett from AWS and Abhishek Sawarkar from NVIDIA, to discover how NVIDIA NIM on AWS can unlock new possibilities for your organization's generative AI initiatives.

Generative AI model deployment: How tech innovators can optimize inference

In this exclusive webcast with MIT Technology Review, we delve into the transformative potential of portable microservices for the deployment of generative AI models. We explore how startups and large organizations are leveraging this technology to streamline generative AI deployment, enhance customer service, and drive innovation across domains, including chatbots, document analysis, and video generation. Our discussion focuses on overcoming key challenges such as deployment complexity, security, and cost management. We also discuss how microservices can help executives realize business value with generative AI while maintaining control over data and intellectual property.

Accelerating generative AI deployment with microservices

As funding and projected revenues increase, the fintech sector is rapidly evolving, largely fuelled by advancements in artificial intelligence (AI) and machine learning.

Join industry experts from AWS and NVIDIA and explore how generative AI enables fintechs to innovate quickly and stay one step ahead of the competition. Discover how EMEA fintechs use generative AI to drive digital transformation, enhance customer experiences, and make better, smarter data-driven decisions.

During the webinar we discuss:
• An overview of generative AI in fintech and the segments that benefit most from AI
• Key generative AI use cases including risk management, fraud detection, AI chatbots, personalised recommendations, algorithmic trading, and model backtesting
• Key challenges faced such as managing complex data securely and scaling AI solutions
• How to harness AI for smarter decision-making and enhance security with initiatives such as Open Banking which has made vast datasets accessible
• How to bring community-built AI models into production using microservices
• How accelerated compute from AWS and NVIDIA enables generative AI adoption

Who should watch:
• Fintech companies looking to start or optimise the use of generative AI
• Cloud native startups that want to scale AI adoption
• Financial firms who want to leverage their data and offer better customer service

Benefits of watching:
• Learn how generative AI is being used in fintechs today
• Discover the benefits of running generative AI in the cloud
• Understand how AWS and NVIDIA work together, with joint customer examples

EMEA fintechs: unlock innovation with generative AI with AWS and NVIDIA

Join us for an engaging BrightTALK fireside chat that examines how NVIDIA NIM inference microservices on AWS is transforming the landscape of self-hosted generative AI deployment for businesses. NIM provides optimized, containerized microservices that integrate with large language models and custom AI models, allowing customers to deploy high performance, scalable generative AI solutions quickly. As organizations increasingly recognize the critical role of generative AI in driving innovation and enhancing customer experiences, the complexity of deployment can pose significant challenges.

In this session we will highlight how NVIDIA NIM:

• Simplifies the deployment of large language models and generative AI applications
• Enables organizations to achieve faster inference and improved performance
• Delivers robust security and data protection

Attendees will gain insights into optimizing generative AI operations, reducing costs, and ensuring compliance with industry standards, empowering IT leaders and business decision-makers to harness the full potential of generative AI in their organizations.

Optimizing generative AI deployment: unleashing business potential with NVIDIA NIM on AWS

Series 1- Optimizing generative AI deployment

In this exclusive AI Business webinar, we offer strategies and insights for streamlined deployment processes, enhanced data protection measures and optimized infrastructure utilization for generative AI projects. It provides essential knowledge for IT decision-makers and business leaders looking to leverage generative AI for competitive advantage in today's rapidly evolving technological landscape. 

Experts from AWS and NVIDIA will detail how using NVIDIA NIM inference microservices on AWS addresses critical hurdles in AI deployment, including complexity, security and cost management, and how it optimizes generative AI for forward-thinking organizations.

We'll also walk you through the process of deploying the Llama 3.1 405B model with NVIDIA NIM on Amazon SageMaker in just a few steps. Tune into this episode to learn more.

Generative AI: Optimizing Deployment with NVIDIA NIM on AWS

Artificial Intelligence

AIOps

Application Development

Inference

Deployment

LLMs

Generative AI

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Generative AI: Optimizing Deployment with NVIDIA NIM on AWS

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Generative AI with AWS and NVIDIA