AWSML

Structured data, defined as data following a fixed pattern such as information stored in columns within databases, and unstructured data, which lacks a specific form or pattern like text, images, or social media posts, both continue to grow as they are produced and consumed by various organizations. For instance, according to International Data Corporation (IDC), … Read more

This post is written in collaboration with Balaji Chandrasekaran, Jennifer Cwagenberg and Andrew Sansom and Eiman Ebrahimi from Protopia AI. New and powerful large language models (LLMs) are changing businesses rapidly, improving efficiency and effectiveness for a variety of enterprise use cases. Speed is of the essence, and adoption of LLM technologies can make or … Read more

This is a guest post co-authored by Nafi Ahmet Turgut, Hasan Burak Yel, and Damla Şentürk from Getir. Established in 2015, Getir has positioned itself as the trailblazer in the sphere of ultrafast grocery delivery. This innovative tech company has revolutionized the last-mile delivery segment with its compelling offering of “groceries in minutes.” With a … Read more

The ability to quickly build and deploy machine learning (ML) models is becoming increasingly important in today’s data-driven world. However, building ML models requires significant time, effort, and specialized expertise. From data collection and cleaning to feature engineering, model building, tuning, and deployment, ML projects often take months for developers to complete. And experienced data … Read more

Launched in 2019, Amazon SageMaker Studio provides one place for all end-to-end machine learning (ML) workflows, from data preparation, building and experimentation, training, hosting, and monitoring. As we continue to innovate to increase data science productivity, we’re excited to announce the improved SageMaker Studio experience, which allows users to select the managed Integrated Development Environment (IDE) … Read more

As organizations scale the adoption of machine learning (ML), they are looking for efficient and reliable ways to deploy new infrastructure and onboard teams to ML environments. One of the challenges is setting up authentication and fine-grained permissions for users based on their roles and activities. For example, MLOps engineers typically perform model deployment activities, … Read more

We believe generative AI has the potential over time to transform virtually every customer experience we know. The number of companies launching generative AI applications on AWS is substantial and building quickly, including adidas, Booking.com, Bridgewater Associates, Clariant, Cox Automotive, GoDaddy, and LexisNexis Legal & Professional, to name just a few. Innovative startups like Perplexity … Read more

Amazon SageMaker is a fully managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning (ML) models at scale. SageMaker makes it easy to deploy models into production directly through API calls to the service. Models are packaged into containers for robust and scalable deployments. SageMaker provides … Read more

Amazon SageMaker is a fully managed service that enables developers and data scientists to quickly and effortlessly build, train, and deploy machine learning (ML) models at any scale. SageMaker makes it straightforward to deploy models into production directly through API calls to the service. Models are packaged into containers for robust and scalable deployments. Although … Read more

Today, we are excited to announce support for Code Editor, a new integrated development environment (IDE) option in Amazon SageMaker Studio. Code Editor is based on Code-OSS, Visual Studio Code Open Source, and provides access to the familiar environment and tools of the popular IDE that machine learning (ML) developers know and love, fully integrated … Read more

As democratization of foundation models (FMs) becomes more prevalent and demand for AI-augmented services increases, software as a service (SaaS) providers are looking to use machine learning (ML) platforms that support multiple tenants—for data scientists internal to their organization and external customers. More and more companies are realizing the value of using FMs to generate … Read more

As organizations deploy models to production, they are constantly looking for ways to optimize the performance of their foundation models (FMs) running on the latest accelerators, such as AWS Inferentia and GPUs, so they can reduce their costs and decrease response latency to provide the best experience to end-users. However, some FMs don’t fully utilize … Read more

Amazon SageMaker makes it straightforward to deploy machine learning (ML) models for real-time inference and offers a broad selection of ML instances spanning CPUs and accelerators such as AWS Inferentia. As a fully managed service, you can scale your model deployments, minimize inference costs, and manage your models more effectively in production with reduced operational … Read more

Amazon SageMaker Canvas is a no-code workspace that enables analysts and citizen data scientists to generate accurate machine learning (ML) predictions for their business needs. Starting today, SageMaker Canvas supports advanced model build configurations such as selecting a training method (ensemble or hyperparameter optimization) and algorithms, customizing the training and validation data split ratio, and … Read more

Amazon Textract is a machine learning (ML) service that automatically extracts text, handwriting, and data from any document or image. AnalyzeDocument Layout is a new feature that allows customers to automatically extract layout elements such as paragraphs, titles, subtitles, headers, footers, and more from documents. Layout extends Amazon Textract’s word and line detection by automatically … Read more

Retrieval Augmented Generation (RAG) allows you to provide a large language model (LLM) with access to data from external knowledge sources such as repositories, databases, and APIs without the need to fine-tune it. When using generative AI for question answering, RAG enables LLMs to answer questions with the most relevant, up-to-date information and optionally cite … Read more

KT Corporation is one of the largest telecommunications providers in South Korea, offering a wide range of services including fixed-line telephone, mobile communication, and internet, and AI services. KT’s AI Food Tag is an AI-based dietary management solution that identifies the type and nutritional content of food in photos using a computer vision model. This … Read more

Amazon Interactive Video Service (Amazon IVS) is a managed live streaming solution that is designed to provide a quick and straightforward setup to let you build interactive video experiences and handles interactive video content from ingestion to delivery. With the increased usage of live streaming, the need for effective content moderation becomes even more crucial. … Read more

Generative AI models have the potential to revolutionize enterprise operations, but businesses must carefully consider how to harness their power while overcoming challenges such as safeguarding data and ensuring the quality of AI-generated content. The Retrieval-Augmented Generation (RAG) framework augments prompts with external data from multiple sources, such as document repositories, databases, or APIs, to … Read more

From enhancing the conversational experience to agent assistance, there are plenty of ways that generative artificial intelligence (AI) and foundation models (FMs) can help deliver faster, better support. With the increasing availability and diversity of FMs, it’s difficult to experiment and keep up-to-date with the latest model versions. Amazon Bedrock is a fully managed service … Read more

This is a joint blog with AWS and Philips. Philips is a health technology company focused on improving people’s lives through meaningful innovation. Since 2014, the company has been offering customers its Philips HealthSuite Platform, which orchestrates dozens of AWS services that healthcare and life sciences companies use to improve patient care. It partners with … Read more

Whisper is an Automatic Speech Recognition (ASR) model that has been trained using 680,000 hours of supervised data from the web, encompassing a range of languages and tasks. One of its limitations is the low-performance on low-resource languages such as Marathi language and Dravidian languages, which can be remediated with fine-tuning. However, fine-tuning a Whisper … Read more

Photo by Scott Webb on Unsplash Determining the value of housing is a classic example of using machine learning (ML). A significant influence was made by Harrison and Rubinfeld (1978), who published a groundbreaking paper and dataset that became known informally as the Boston housing dataset. This seminal work proposed a method for estimating housing … Read more

AutoML allows you to derive rapid, general insights from your data right at the beginning of a machine learning (ML) project lifecycle. Understanding up front which preprocessing techniques and algorithm types provide best results reduces the time to develop, train, and deploy the right model. It plays a crucial role in every model’s development process … Read more

Llama 2 stands at the forefront of AI innovation, embodying an advanced auto-regressive language model developed on a sophisticated transformer foundation. It’s tailored to address a multitude of applications in both the commercial and research domains with English as the primary linguistic concentration. Its model parameters scale from an impressive 7 billion to a remarkable … Read more

An established financial services firm with over 140 years in business, Principal is a global investment management leader and serves more than 62 million customers around the world. Principal is conducting enterprise-scale near-real-time analytics to deliver a seamless and hyper-personalized omnichannel customer experience on their mission to make financial security accessible for all. They are … Read more

Prompt engineering has become an essential skill for anyone working with large language models (LLMs) to generate high-quality and relevant texts. Although text prompt engineering has been widely discussed, visual prompt engineering is an emerging field that requires attention. Visual prompts can include bounding boxes or masks that guide vision models in generating relevant and … Read more

Online communities are driving user engagement across industries like gaming, social media, ecommerce, dating, and e-learning. Members of these online communities trust platform owners to provide a safe and inclusive environment where they can freely consume content and contribute. Content moderators are often employed to review user-generated content and check that it’s safe and compliant … Read more

Today, we are excited to announce the capability to fine-tune the Mistral 7B model using Amazon SageMaker JumpStart. You can now fine-tune and deploy Mistral text generation models on SageMaker JumpStart using the Amazon SageMaker Studio UI with a few clicks or using the SageMaker Python SDK. Foundation models perform very well with generative tasks, … Read more

Fake news, defined as news that conveys or incorporates false, fabricated, or deliberately misleading information, has been around as early as the emergence of the printing press. The rapid spread of fake news and disinformation online is not only deceiving to the public, but can also have a profound impact on society, politics, economy, and … Read more