AWS Machine Learning Blog Official Machine Learning Blog of Amazon Web Services
- Building an AIOps chatbot with Amazon Q Business custom pluginsby Upendra V on April 11, 2025 at 17:50
In this post, we demonstrate how you can use custom plugins for Amazon Q Business to build a chatbot that can interact with multiple APIs using natural language prompts. We showcase how to build an AIOps chatbot that enables users to interact with their AWS infrastructure through natural language queries and commands. The chatbot is capable of handling tasks such as querying the data about Amazon Elastic Compute Cloud (Amazon EC2) ports and Amazon Simple Storage Service (Amazon S3) buckets access settings.
- How TransPerfect Improved Translation Quality and Efficiency Using Amazon Bedrockby Peter Chung on April 11, 2025 at 17:25
This post describes how the AWS Customer Channel Technology – Localization Team worked with TransPerfect to integrate Amazon Bedrock into the GlobalLink translation management system, a cloud-based solution designed to help organizations manage their multilingual content and translation workflows. Organizations use TransPerfect’s solution to rapidly create and deploy content at scale in multiple languages using AI.
- Racing beyond DeepRacer: Debut of the AWS LLM Leagueby Vincent Oh on April 11, 2025 at 17:16
The AWS LLM League was designed to lower the barriers to entry in generative AI model customization by providing an experience where participants, regardless of their prior data science experience, could engage in fine-tuning LLMs. Using Amazon SageMaker JumpStart, attendees were guided through the process of customizing LLMs to address real business challenges adaptable to their domain.
- Reduce ML training costs with Amazon SageMaker HyperPodby Anoop Saha on April 10, 2025 at 20:11
In this post, we explore the challenges of large-scale frontier model training, focusing on hardware failures and the benefits of Amazon SageMaker HyperPod – a solution that minimizes disruptions, enhances efficiency, and reduces training costs.
- Model customization, RAG, or both: A case study with Amazon Novaby Flora Wang on April 10, 2025 at 16:50
The introduction of Amazon Nova models represent a significant advancement in the field of AI, offering new opportunities for large language model (LLM) optimization. In this post, we demonstrate how to effectively perform model customization and RAG with Amazon Nova models as a baseline. We conducted a comprehensive comparison study between model customization and RAG using the latest Amazon Nova models, and share these valuable insights.
MIT News – Artificial intelligence MIT news feed about: Artificial intelligence
- New method efficiently safeguards sensitive AI training databy Adam Zewe | MIT News on April 11, 2025 at 04:00
The approach maintains an AI model’s accuracy while ensuring attackers can’t extract secret information.
- Could LLMs help design our next medicines and materials?by Adam Zewe | MIT News on April 9, 2025 at 04:00
A new method lets users ask, in plain language, for a new molecule with certain properties, and receive a detailed description of how to synthesize it.
- New method assesses and improves the reliability of radiologists’ diagnostic reportsby Adam Zewe | MIT News on April 4, 2025 at 04:00
The framework helps clinicians choose phrases that more accurately reflect the likelihood that certain conditions are present in X-rays.
- Taking the “training wheels” off clean energyby Calvin Hennick | MIT Energy Initiative on April 3, 2025 at 20:35
At the 2025 MIT Energy Conference, energy leaders from around the world discussed how to make green technologies competitive with fossil fuels.
- Vana is letting users own a piece of the AI models trained on their databy Zach Winn | MIT News on April 3, 2025 at 04:00
More than 1 million people are contributing their data to Vana’s decentralized network, which started as an MIT class project.
Google DeepMind Blog Read the latest articles and stories from DeepMind and find out more about our latest breakthroughs in cutting-edge AI research.
- Taking a responsible path to AGIon April 2, 2025 at 13:31
We’re exploring the frontiers of AGI, prioritizing technical safety, proactive risk assessment, and collaboration with the AI community.
- Evaluating potential cybersecurity threats of advanced AIon April 2, 2025 at 13:30
Our framework enables cybersecurity experts to identify which defenses are necessary—and how to prioritize them
- Gemini 2.5: Our most intelligent AI modelon March 25, 2025 at 17:00
Gemini 2.5 is our most intelligent AI model, now with thinking built in.
- Gemini Robotics brings AI into the physical worldon March 12, 2025 at 15:00
Introducing Gemini Robotics and Gemini Robotics-ER, AI models designed for robots to understand, act and react to the physical world.
- Experiment with Gemini 2.0 Flash native image generationon March 12, 2025 at 14:58
Native image output is available in Gemini 2.0 Flash for developers to experiment with in Google AI Studio and the Gemini API.