Favorite Generative artificial intelligence (AI) has gained significant momentum with organizations actively exploring its potential applications. As successful proof-of-concepts transition into production, organizations are increasingly in need of enterprise scalable solutions. However, to unlock the long-term success and viability of these AI-powered solutions, it is crucial to align them with
Favorite We introduced Amazon Bedrock to the world a little over a year ago, delivering an entirely new way to build generative artificial intelligence (AI) applications. With the broadest selection of first- and third-party foundation models (FMs) as well as user-friendly capabilities, Amazon Bedrock is the fastest and easiest way
Favorite We are excited to announce two new capabilities in Amazon SageMaker Studio that will accelerate iterative development for machine learning (ML) practitioners: Local Mode and Docker support. ML model development often involves slow iteration cycles as developers switch between coding, training, and deployment. Each step requires waiting for remote
Favorite With version 0.0.7 of the Open Source AI Definition just published, we are getting very close to a release candidate version in June, as planned. We’ve covered a lot of ground since FOSDEM 2024, where we presented draft 0.0.4. This month we presented at Open Source Summit North America
Favorite Organizations are facing ever-increasing requirements for sustainability goals alongside environmental, social, and governance (ESG) practices. A Gartner, Inc. survey revealed that 87 percent of business leaders expect to increase their organization’s investment in sustainability over the next years. This post serves as a starting point for any executive seeking
Favorite Amazon SageMaker HyperPod is purpose-built to accelerate foundation model (FM) training, removing the undifferentiated heavy lifting involved in managing and optimizing a large training compute cluster. With SageMaker HyperPod, you can train FMs for weeks and months without disruption. Typically, HyperPod clusters are used by multiple users: machine learning
Favorite Comments on the forum A user added in the forum that there is an issue as traditional copyright protection might not apply to weight models because they are essentially mathematical calculations. “ licensing them through any kind of copyright license will not be enforceable !! and this means that
Favorite This is a guest post co-written with the leadership team of Iambic Therapeutics. Iambic Therapeutics is a drug discovery startup with a mission to create innovative AI-driven technologies to bring better medicines to cancer patients, faster. Our advanced generative and predictive artificial intelligence (AI) tools enable us to search
Favorite In Part 1 of this series, we presented a solution that used the Amazon Titan Multimodal Embeddings model to convert individual slides from a slide deck into embeddings. We stored the embeddings in a vector database and then used the Large Language-and-Vision Assistant (LLaVA 1.5-7b) model to generate text
Favorite We are excited to announce a new version of the Amazon SageMaker Operators for Kubernetes using the AWS Controllers for Kubernetes (ACK). ACK is a framework for building Kubernetes custom controllers, where each controller communicates with an AWS service API. These controllers allow Kubernetes users to provision AWS resources
Shared by AWS Machine Learning April 24, 2024
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