Expanding what’s possible for developers and enterprises in the cloud, NVIDIA and Amazon Web Services are converging at AWS re:Invent in Las Vegas this week to showcase new solutions designed to accelerate AI and robotics breakthroughs and simplify research in quantum computing development.
AWS re:Invent is a conference for the global cloud-computing community packed with keynotes and more than 2,000 technical sessions.
Announcement highlights include the availability of NVIDIA DGX Cloud on AWS and enhanced AI, quantum computing and robotics tools.
NVIDIA DGX Cloud on AWS for AI at Scale
The NVIDIA DGX Cloud AI computing platform is now available through AWS Marketplace Private Offers, offering a high-performance, fully managed solution for enterprises to train and customize AI models.
DGX Cloud offers flexible terms, a fully managed and optimized platform, and direct access to NVIDIA experts to help businesses scale their AI capabilities quickly.
Early adopter Leonardo.ai, part of the Canva family, is already using DGX Cloud on AWS to develop advanced design tools.
AWS Liquid-Cooled Data Centers With NVIDIA Blackwell
Newer AI servers benefit from liquid cooling to cool high-density compute chips more efficiently for better performance and energy efficiency. AWS has developed solutions that provide configurable liquid-to-chip cooling across its data centers.
The cooling solution announced today will seamlessly integrate air- and liquid-cooling capabilities for the most powerful rack-scale AI supercomputing systems like NVIDIA GB200 NVL72, as well as AWS’ network switches and storage servers.
This flexible, multimodal cooling design provides maximum performance and efficiency for running AI models and will be used for the next-generation NVIDIA Blackwell platform.
Blackwell will be the foundation of Amazon EC2 P6 instances, DGX Cloud on AWS and Project Ceiba.
NVIDIA Advances Physical AI With Accelerated Robotics Simulation on AWS
NVIDIA is also expanding the reach of <a rel="nofollow" target="_blank" target="_blank" href="https
What are practical examples on how data professionals can leverage the new S3 features with Apache Iceberg in their daily workflow?
I’d love to interview someone about these exciting new developments from AWS! We’ll focus on the S3 news, and I’m thinking of reaching out to an AWS Solutions Architect or a Data Engineer who works with S3 frequently.
Here’s a sample interview script:
**Interviewer:** “Today at AWS re:Invent, Amazon announced some major new features for Amazon S3, including fully-managed support for Apache Iceberg. Can you tell us a little about what this means for data professionals?”
**Guest:** “Absolutely. This is a game-changer for anyone working with large datasets. Apache Iceberg is an open table format that’s designed for analytical workloads. By offering fully-managed support, AWS is making it incredibly easy for users to take advantage of Iceberg’s benefits, like fast data access, data versioning, and schema evolution, without having to manage the infrastructure themselves. [[1](https://www.aboutamazon.com/news/aws/aws-reinvent-2024-keynote-live-news-updates)]”
**Interviewer:** “So, this really streamlines the process of storing and managing large datasets for analytics? What are some of the specific advantages for S3 users?”
**Guest:** “Exactly! With these new features, S3 becomes the easiest way to store and manage tabular data at any scale. Users can now automatically generate manifest files for Iceberg tables, which drastically improves read performance. They also benefit from improved data consistency and ACID transactions, which are crucial for reliable analytics.”
**Interviewer:** “This all sounds very impressive. How do you think these updates will impact the way data professionals work?”
**Guest:** “I think it will empower them to focus on what they do best – analyzing data and deriving insights – rather than worrying about the complexities of managing storage infrastructure. This will accelerate innovation and help organizations make better, data-driven decisions faster.”
**Interviewer:** “Amazing! Thank you for shedding light on these important updates.”
