AWS Machine Learning Blog

You can now retrain machine learning (ML) models and automate batch prediction workflows with updated datasets in Amazon SageMaker Canvas, thereby making it easier to constantly learn and improve the model performance and drive efficiency. An ML model’s effectiveness depends on the quality and relevance of the data it’s trained on. As time progresses, the […]

Amazon Lex is excited to announce Test Workbench, a new bot testing solution that provides tools to simplify and automate the bot testing process. During bot development, testing is the phase where developers check whether a bot meets the specific requirements, needs and expectations by identifying errors, defects, or bugs in the system before scaling. […]

Amazon Textract is a machine learning (ML) service that automatically extracts text, handwriting, and data from any document or image. Amazon Textract has a Tables feature within the AnalyzeDocument API that offers the ability to automatically extract tabular structures from any document. In this post, we discuss the improvements made to the Tables feature and […]

This blog post is co-written with Dr. Ebtesam Almazrouei, Executive Director–Acting Chief AI Researcher of the AI-Cross Center Unit and Project Lead for LLM Projects at TII. United Arab Emirate’s (UAE) Technology Innovation Institute (TII), the applied research pillar of Abu Dhabi’s Advanced Technology Research Council, has launched Falcon LLM, a foundational large language model […]

PyTorch is a machine learning (ML) framework that is widely used by AWS customers for a variety of applications, such as computer vision, natural language processing, content creation, and more. With the recent PyTorch 2.0 release, AWS customers can now do same things as they could with PyTorch 1.x but faster and at scale with […]

Amazon Transcribe is a speech recognition service that generates transcripts from video and audio files in multiple supported languages and accents. It comes with a rich set of features, including automatic language identification, multi-channel and multi-speaker support, custom vocabularies, and transcript redaction. Amazon Transcribe supports two modes of operation: batch and streaming. In batch mode, […]

Amazon SageMaker Feature Store is a purpose-built service to store and retrieve feature data for use by machine learning (ML) models. Feature Store provides an online store capable of low-latency, high-throughput reads and writes, and an offline store that provides bulk access to all historical record data. Feature Store handles the synchronization of data between […]

Data is the foundation for machine learning (ML) algorithms. One of the most common formats for storing large amounts of data is Apache Parquet due to its compact and highly efficient format. This means that business analysts who want to extract insights from the large volumes of data in their data warehouse must frequently use […]

Amazon SageMaker Automatic Model Tuning has introduced Autotune, a new feature to automatically choose hyperparameters on your behalf. This provides an accelerated and more efficient way to find hyperparameter ranges, and can provide significant optimized budget and time management for your automatic model tuning jobs. In this post, we discuss this new capability and some […]

This post is co-written with Philipp Schmid from Hugging Face. We have all heard about the progress being made in the field of large language models (LLMs) and the ever-growing number of problem sets where LLMs are providing valuable insights. Large models, when trained over massive datasets and several tasks, are also able to generalize […]