Tag: Channy Yun (윤석찬)

At re:Invent 2024, we launched Amazon S3 Tables, the first cloud object store with built-in Apache Iceberg support to streamline storing tabular data at scale, and Amazon SageMaker Lakehouse to simplify analytics and AI with a unified, open, and secure data lakehouse. We also previewed S3 Tables integration with Amazon Web Services (AWS) analytics services for you to stream, query, and visualize S3 Tables data using Amazon Athena, Amazon Data Firehose, Amazon EMR, AWS Glue, Amazon Redshift, and Amazon QuickSight. Our customers wanted to simplify the management and optimization of their Apache Iceberg storage, which led to the development of S3 Tables. They were simultaneously working to break down data silos that impede analytics collaboration and insight generation using the…

As of January 30, DeepSeek-R1 models became available in Amazon Bedrock through the Amazon Bedrock Marketplace and Amazon Bedrock Custom Model Import. Since then, thousands of customers have deployed these models in Amazon Bedrock. Customers value the robust guardrails and comprehensive tooling for safe AI deployment. Today, we’re making it even easier to use DeepSeek in Amazon Bedrock through an expanded range of options, including a new serverless solution. The fully managed DeepSeek-R1 model is now generally available in Amazon Bedrock. Amazon Web Services (AWS) is the first cloud service provider (CSP) to deliver DeepSeek-R1 as a fully managed, generally available model. You can accelerate innovation and deliver tangible business value with DeepSeek on AWS without having to manage infrastructure…

Join us for the AWS Developer Day on February 20! This virtual event is designed to help developers and teams incorporate cutting-edge yet responsible generative AI across their development lifecycle to accelerate innovation. In his keynote, Jeff Barr, Vice President of AWS Evangelism, shares his thoughts on the next generation of software development based on generative AI, the skills needed to thrive in this changing environment, and how he sees it evolving in the future. Get a first look at exciting technical deep-dive and product updates about Amazon Q Developer, AWS Amplify, and GitLab Duo with Amazon Q. You get the chance to explore real-world use cases, live coding demos, interactive sessions, and community spotlight sessions with Christian Bonzelet (AWS…

During this past AWS re:Invent, Amazon CEO Andy Jassy shared valuable lessons learned from Amazon’s own experience developing nearly 1,000 generative AI applications across the company. Drawing from this extensive scale of AI deployment, Jassy offered three key observations that have shaped Amazon’s approach to enterprise AI implementation. First is that as you get to scale in generative AI applications, the cost of compute really matters. People are very hungry for better price performance. The second is actually quite difficult to build a really good generative AI application. The third is the diversity of the models being used when we gave our builders freedom to pick what they want to do. It doesn’t surprise us, because we keep learning the…