AWS Machine Learning Blog Official Machine Learning Blog of Amazon Web Services
- Import data from Google Cloud Platform BigQuery for no-code machine learning with Amazon SageMaker Canvasby Amit Gautam on October 28, 2024 at 18:38
This post presents an architectural approach to extract data from different cloud environments, such as Google Cloud Platform (GCP) BigQuery, without the need for data movement. This minimizes the complexity and overhead associated with moving data between cloud environments, enabling organizations to access and utilize their disparate data assets for ML projects. We highlight the process of using Amazon Athena Federated Query to extract data from GCP BigQuery, using Amazon SageMaker Data Wrangler to perform data preparation, and then using the prepared data to build ML models within Amazon SageMaker Canvas, a no-code ML interface.
- Customized model monitoring for near real-time batch inference with Amazon SageMakerby Joe King on October 28, 2024 at 17:22
In this post, we present a framework to customize the use of Amazon SageMaker Model Monitor for handling multi-payload inference requests for near real-time inference scenarios. SageMaker Model Monitor monitors the quality of SageMaker ML models in production. Early and proactive detection of deviations in model quality enables you to take corrective actions, such as retraining models, auditing upstream systems, or fixing quality issues without having to monitor models manually or build additional tooling.
- How Planview built a scalable AI Assistant for portfolio and project management using Amazon Bedrockby Sunil Ramachandra on October 25, 2024 at 16:51
In this post, we explore how Planview was able to develop a generative AI assistant to address complex work management process by adopting Amazon Bedrock.
- Super charge your LLMs with RAG at scale using AWS Glue for Apache Sparkby Noritaka Sekiyama on October 24, 2024 at 18:09
In this post, we will explore building a reusable RAG data pipeline on LangChain—an open source framework for building applications based on LLMs—and integrating it with AWS Glue and Amazon OpenSearch Serverless. The end solution is a reference architecture for scalable RAG indexing and deployment.
- From RAG to fabric: Lessons learned from building real-world RAGs at GenAIIC – Part 1by Aude Genevay on October 24, 2024 at 18:04
In this post, we cover the core concepts behind RAG architectures and discuss strategies for evaluating RAG performance, both quantitatively through metrics and qualitatively by analyzing individual outputs. We outline several practical tips for improving text retrieval, including using hybrid search techniques, enhancing context through data preprocessing, and rewriting queries for better relevance.
MIT News – Artificial intelligence MIT news feed about: Artificial intelligence
- A faster, better way to train general-purpose robotsby Adam Zewe | MIT News on October 28, 2024 at 04:00
Inspired by large language models, researchers develop a training technique that pools diverse data to teach robots new skills.
- Making it easier to verify an AI model’s responsesby Adam Zewe | MIT News on October 21, 2024 at 15:40
By allowing users to clearly see data referenced by a large language model, this tool speeds manual validation to help users spot AI errors.
- Combining next-token prediction and video diffusion in computer vision and roboticsby Alex Shipps | MIT CSAIL on October 16, 2024 at 20:10
A new method can train a neural network to sort corrupted data while anticipating next steps. It can make flexible plans for robots, generate high-quality video, and help AI agents navigate digital environments.
- Equipping doctors with AI co-pilotsby Zach Winn | MIT News on October 16, 2024 at 04:00
Alumni-founded Ambience Healthcare automates routine tasks for clinicians before, during, and after patient visits.
- Artificial intelligence meets “blisk” in new DARPA-funded collaborationby Janine Liberty | Anne Wilson | Department of Aeronautics and Astronautics | Department of Mechanical Engineering on October 8, 2024 at 19:30
Collaborative multi-university team will pursue new AI-enhanced design tools and high-throughput testing methods for next-generation turbomachinery.
Google DeepMind Blog Read the latest articles and stories from DeepMind and find out more about our latest breakthroughs in cutting-edge AI research.
- New generative AI tools open the doors of music creationon October 23, 2024 at 16:53
Our latest AI music technologies are now available in MusicFX DJ, Music AI Sandbox and YouTube Shorts
- Demis Hassabis & John Jumper awarded Nobel Prize in Chemistryon October 9, 2024 at 11:45
The award recognizes their work developing AlphaFold, a groundbreaking AI system that predicts the 3D structure of proteins from their amino acid sequences.
- How AlphaChip transformed computer chip designon September 26, 2024 at 14:08
Our AI method has accelerated and optimized chip design, and its superhuman chip layouts are used in hardware around the world.
- Updated production-ready Gemini models, reduced 1.5 Pro pricing, increased rate limits, and moreon September 24, 2024 at 16:03
We’re releasing two updated production-ready Gemini models
- Empowering YouTube creators with generative AIon September 18, 2024 at 14:30
New video generation technology in YouTube Shorts will help millions of people realize their creative vision