Releases

Amazon released its lower-cost Titan text-generation model through Bedrock.

AWS launched managed retrieval-augmented generation for grounding foundation models in private data.

AWS made Amazon Bedrock generally available with managed access to Amazon and third-party foundation models.

Amazon agreed to invest up to $4 billion in Anthropic, with AWS becoming Anthropic's primary cloud provider and Trainium and Inferentia used for model development.

AWS introduced managed agents that orchestrate foundation models, enterprise data and API actions.

AWS introduced a generative-AI service for transcribing clinical conversations and drafting preliminary clinical notes.

AWS launched Inferentia2-powered EC2 instances for large-scale generative-AI inference.

Amazon introduced its first text embedding foundation model through the Bedrock preview.

AWS made its generative-AI coding assistant generally available, including a free individual tier and reference tracking.

AWS announced a managed service for building generative-AI applications with foundation models from Amazon and third parties.

AWS introduced Amazon Titan, its family of text generation and embedding foundation models available through Bedrock.

Amazon introduced an AI and computer-vision system able to identify and handle individual products.

AWS launched Trainium-powered EC2 instances for high-performance deep-learning training.

Amazon researchers published a 20-billion-parameter multilingual sequence-to-sequence teacher model.

AWS introduced its generative-AI coding companion in preview.

Amazon unveiled its first fully autonomous mobile robot for safely operating around employees.

AWS introduced a no-code visual interface for generating machine-learning predictions.

AWS founder Andy Jassy succeeded Jeff Bezos as Amazon's chief executive officer.

AWS introduced a HIPAA-eligible health data lake using FHIR and machine learning.

AWS introduced tools for bias detection and model explainability.

AWS introduced machine-learning-based anomaly detection for business and operational metrics.

AWS introduced an end-to-end condition-monitoring system using sensors and machine learning.

AWS introduced predictive maintenance from industrial sensor data.

AWS introduced a computer-vision service for visual defect and anomaly detection.

AWS introduced an ML-powered service for detecting abnormal operational behavior and recommending remediation.

AWS introduced pretrained models and solution templates to accelerate machine-learning deployment.

AWS announced its first custom chip purpose-built for high-performance machine-learning training.

AWS and Facebook jointly released TorchServe, an open-source model-serving library for PyTorch.

AWS launched automated model building with full visibility into generated models and notebooks.

AWS launched a web-based integrated development environment for machine learning.

AWS introduced managed human-review workflows for machine-learning predictions.

AWS introduced an intelligent enterprise-search service using machine learning and natural-language queries.

AWS introduced ML-powered code review and performance recommendations.

AWS made Inferentia-powered EC2 instances generally available for machine-learning inference.

AWS introduced a generative-AI learning service and musical keyboard.

AWS released optimized Docker images for deep-learning training and inference.

AWS launched attachable fractional GPU acceleration for EC2 and SageMaker inference workloads.

AWS announced its first custom machine-learning inference chip.

AWS launched a reinforcement-learning education platform built around an autonomous scale race car.

AWS introduced document AI for extracting text, handwriting, forms and tables.

AWS introduced a managed forecasting service based on technology used in Amazon's retail operations.

AWS introduced a managed service for building individualized recommendations using technology derived from Amazon.com.

AWS introduced a managed data-labeling service combining human annotation with active learning.

AWS launched a HIPAA-eligible NLP service for extracting medical entities and relationships from text.

AWS introduced managed natural-language processing for entity, sentiment, language and topic extraction.

AWS introduced a managed neural machine-translation service.

AWS introduced a managed automatic speech-recognition service.

AWS introduced a programmable deep-learning-enabled video camera for edge computer-vision development.

AWS launched an end-to-end managed platform for building, training and deploying machine-learning models.

Amazon unveiled a checkout-free store using computer vision, sensor fusion and deep learning.