Unlock the potential of generative AI in industrial operations

In the evolving landscape of manufacturing, the transformative power of AI and machine learning (ML) is evident, driving a digital revolution that streamlines operations and boosts productivity. However, this progress introduces unique challenges for enterprises navigating data-driven solutions. Industrial facilities grapple with vast volumes of unstructured data, sourced from sensors, telemetry systems, and equipment dispersed … Read more

Enhance performance of generative language models with self-consistency prompting on Amazon Bedrock

Generative language models have proven remarkably skillful at solving logical and analytical natural language processing (NLP) tasks. Furthermore, the use of prompt engineering can notably enhance their performance. For example, chain-of-thought (CoT) is known to improve a model’s capacity for complex multi-step problems. To additionally boost accuracy on tasks that involve reasoning, a self-consistency prompting … Read more

Optimize price-performance of LLM inference on NVIDIA GPUs using the Amazon SageMaker integration with NVIDIA NIM Microservices

NVIDIA NIM microservices now integrate with Amazon SageMaker, allowing you to deploy industry-leading large language models (LLMs) and optimize model performance and cost. You can deploy state-of-the-art LLMs in minutes instead of days using technologies such as NVIDIA TensorRT, NVIDIA TensorRT-LLM, and NVIDIA Triton Inference Server on NVIDIA accelerated instances hosted by SageMaker. NIM, part … Read more

Fine-tune Code Llama on Amazon SageMaker JumpStart

Today, we are excited to announce the capability to fine-tune Code Llama models by Meta using Amazon SageMaker JumpStart. The Code Llama family of large language models (LLMs) is a collection of pre-trained and fine-tuned code generation models ranging in scale from 7 billion to 70 billion parameters. Fine-tuned Code Llama models provide better accuracy … Read more

Transform one-on-one customer interactions: Build speech-capable order processing agents with AWS and generative AI

In today’s landscape of one-on-one customer interactions for placing orders, the prevailing practice continues to rely on human attendants, even in settings like drive-thru coffee shops and fast-food establishments. This traditional approach poses several challenges: it heavily depends on manual processes, struggles to efficiently scale with increasing customer demands, introduces the potential for human errors, … Read more

Federated learning on AWS using FedML, Amazon EKS, and Amazon SageMaker

This post is co-written with Chaoyang He, Al Nevarez and Salman Avestimehr from FedML. Many organizations are implementing machine learning (ML) to enhance their business decision-making through automation and the use of large distributed datasets. With increased access to data, ML has the potential to provide unparalleled business insights and opportunities. However, the sharing of … Read more

Enable data sharing through federated learning: A policy approach for chief digital officers

This is a guest blog post written by Nitin Kumar, a Lead Data Scientist at T and T Consulting Services, Inc. In this post, we discuss the value and potential impact of federated learning in the healthcare field. This approach can help heart stroke patients, doctors, and researchers with faster diagnosis, enriched decision-making, and more … Read more

The journey of PGA TOUR’s generative AI virtual assistant, from concept to development to prototype

This is a guest post co-written with Scott Gutterman from the PGA TOUR. Generative artificial intelligence (generative AI) has enabled new possibilities for building intelligent systems. Recent improvements in Generative AI based large language models (LLMs) have enabled their use in a variety of applications surrounding information retrieval. Given the data sources, LLMs provided tools … Read more

Enhance code review and approval efficiency with generative AI using Amazon Bedrock

In the world of software development, code review and approval are important processes for ensuring the quality, security, and functionality of the software being developed. However, managers tasked with overseeing these critical processes often face numerous challenges, such as the following: Lack of technical expertise – Managers may not have an in-depth technical understanding of … Read more

Best practices to build generative AI applications on AWS

Generative AI applications driven by foundational models (FMs) are enabling organizations with significant business value in customer experience, productivity, process optimization, and innovations. However, adoption of these FMs involves addressing some key challenges, including quality output, data privacy, security, integration with organization data, cost, and skills to deliver. In this post, we explore different approaches … Read more

Moderate audio and text chats using AWS AI services and LLMs

Online gaming and social communities offer voice and text chat functionality for their users to communicate. Although voice and text chat often support friendly banter, it can also lead to problems such as hate speech, cyberbullying, harassment, and scams. Today, many companies rely solely on human moderators to review toxic content. However, verifying violations in … Read more

Inference Llama 2 models with real-time response streaming using Amazon SageMaker

With the rapid adoption of generative AI applications, there is a need for these applications to respond in time to reduce the perceived latency with higher throughput. Foundation models (FMs) are often pre-trained on vast corpora of data with parameters ranging in scale of millions to billions and beyond. Large language models (LLMs) are a … Read more

Create a document lake using large-scale text extraction from documents with Amazon Textract

AWS customers in healthcare, financial services, the public sector, and other industries store billions of documents as images or PDFs in Amazon Simple Storage Service (Amazon S3). However, they’re unable to gain insights such as using the information locked in the documents for large language models (LLMs) or search until they extract the text, forms, … Read more

Modernizing data science lifecycle management with AWS and Wipro

This post was written in collaboration with Bhajandeep Singh and Ajay Vishwakarma from Wipro’s AWS AI/ML Practice. Many organizations have been using a combination of on-premises and open source data science solutions to create and manage machine learning (ML) models. Data science and DevOps teams may face challenges managing these isolated tool stacks and systems. … Read more

Generating value from enterprise data: Best practices for Text2SQL and generative AI

Generative AI has opened up a lot of potential in the field of AI. We are seeing numerous uses, including text generation, code generation, summarization, translation, chatbots, and more. One such area that is evolving is using natural language processing (NLP) to unlock new opportunities for accessing data through intuitive SQL queries. Instead of dealing … Read more

Amazon SageMaker model parallel library now accelerates PyTorch FSDP workloads by up to 20%

Large language model (LLM) training has surged in popularity over the last year with the release of several popular models such as Llama 2, Falcon, and Mistral. Customers are now pre-training and fine-tuning LLMs ranging from 1 billion to over 175 billion parameters to optimize model performance for applications across industries, from healthcare to finance … Read more

Mixtral-8x7B is now available in Amazon SageMaker JumpStart

Today, we are excited to announce that the Mixtral-8x7B large language model (LLM), developed by Mistral AI, is available for customers through Amazon SageMaker JumpStart to deploy with one click for running inference. The Mixtral-8x7B LLM is a pre-trained sparse mixture of expert model, based on a 7-billion parameter backbone with eight experts per feed-forward … Read more

Deploy foundation models with Amazon SageMaker, iterate and monitor with TruEra

This blog is co-written with Josh Reini, Shayak Sen and Anupam Datta from TruEra Amazon SageMaker JumpStart provides a variety of pretrained foundation models such as Llama-2 and Mistal 7B that can be quickly deployed to an endpoint. These foundation models perform well with generative tasks, from crafting text and summaries, answering questions, to producing … Read more

Build generative AI agents with Amazon Bedrock, Amazon DynamoDB, Amazon Kendra, Amazon Lex, and LangChain

Generative AI agents are capable of producing human-like responses and engaging in natural language conversations by orchestrating a chain of calls to foundation models (FMs) and other augmenting tools based on user input. Instead of only fulfilling predefined intents through a static decision tree, agents are autonomous within the context of their suite of available … Read more

Overcoming common contact center challenges with generative AI and Amazon SageMaker Canvas

Great customer experience provides a competitive edge and helps create brand differentiation. As per the Forrester report, The State Of Customer Obsession, 2022, being customer-first can make a sizable impact on an organization’s balance sheet, as organizations embracing this methodology are surpassing their peers in revenue growth. Despite contact centers being under constant pressure to … Read more

Llama Guard is now available in Amazon SageMaker JumpStart

Today we are excited to announce that the Llama Guard model is now available for customers using Amazon SageMaker JumpStart. Llama Guard provides input and output safeguards in large language model (LLM) deployment. It’s one of the components under Purple Llama, Meta’s initiative featuring open trust and safety tools and evaluations to help developers build … Read more

Identify cybersecurity anomalies in your Amazon Security Lake data using Amazon SageMaker

Customers are faced with increasing security threats and vulnerabilities across infrastructure and application resources as their digital footprint has expanded and the business impact of those digital assets has grown. A common cybersecurity challenge has been two-fold: Consuming logs from digital resources that come in different formats and schemas and automating the analysis of threat … Read more

Driving advanced analytics outcomes at scale using Amazon SageMaker powered PwC’s Machine Learning Ops Accelerator

This post was written in collaboration with Ankur Goyal and Karthikeyan Chokappa from PwC Australia’s Cloud & Digital business. Artificial intelligence (AI) and machine learning (ML) are becoming an integral part of systems and processes, enabling decisions in real time, thereby driving top and bottom-line improvements across organizations. However, putting an ML model into production … Read more

ISO 42001: A new foundational global standard to advance responsible AI

Artificial intelligence (AI) is one of the most transformational technologies of our generation and provides opportunities to be a force for good and drive economic growth. The growth of large language models (LLMs), with hundreds of billions of parameters, has unlocked new generative AI use cases to improve customer experiences, boost employee productivity, and so … Read more

Accelerating time-to-insight with MongoDB time series collections and Amazon SageMaker Canvas

This is a guest post co-written with Babu Srinivasan from MongoDB. As industries evolve in today’s fast-paced business landscape, the inability to have real-time forecasts poses significant challenges for industries heavily reliant on accurate and timely insights. The absence of real-time forecasts in various industries presents pressing business challenges that can significantly impact decision-making and … Read more

Use Amazon DocumentDB to build no-code machine learning solutions in Amazon SageMaker Canvas

We are excited to announce the launch of Amazon DocumentDB (with MongoDB compatibility) integration with Amazon SageMaker Canvas, allowing Amazon DocumentDB customers to build and use generative AI and machine learning (ML) solutions without writing code. Amazon DocumentDB is a fully managed native JSON document database that makes it straightforward and cost-effective to operate critical … Read more

Boost productivity on Amazon SageMaker Studio: Introducing JupyterLab Spaces and generative AI tools

Amazon SageMaker Studio offers a broad set of fully managed integrated development environments (IDEs) for machine learning (ML) development, including JupyterLab, Code Editor based on Code-OSS (Visual Studio Code Open Source), and RStudio. It provides access to the most comprehensive set of tools for each step of ML development, from preparing data to building, training, … Read more

How AWS Prototyping enabled ICL-Group to build computer vision models on Amazon SageMaker

This is a customer post jointly authored by ICL and AWS employees. ICL is a multi-national manufacturing and mining corporation based in Israel that manufactures products based on unique minerals and fulfills humanity’s essential needs, primarily in three markets: agriculture, food, and engineered materials. Their mining sites use industrial equipment that has to be monitored … Read more