AWS Machine Learning Blog

Unlocking Innovation: AWS and Anthropic push the boundaries of generative AI together

Amazon Bedrock is the best place to build and scale generative AI applications with large language models (LLM) and other foundation models (FMs). It enables customers to leverage a variety of high-performing FMs, such as the Claude family of models by Anthropic, to build custom generative AI applications. Looking back to 2021, when Anthropic first started […]

Achieve DevOps maturity with BMC AMI zAdviser Enterprise and Amazon Bedrock

This blog post discusses how BMC Software added AWS Generative AI capabilities to its product BMC AMI zAdviser Enterprise. The zAdviser uses Amazon Bedrock to provide summarization, analysis, and recommendations for improvement based on the DORA metrics data.

Fine-tune your Amazon Titan Image Generator G1 model using Amazon Bedrock model customization

Amazon Titan lmage Generator G1 is a cutting-edge text-to-image model, available via Amazon Bedrock, that is able to understand prompts describing multiple objects in various contexts and captures these relevant details in the images it generates. It is available in US East (N. Virginia) and US West (Oregon) AWS Regions and can perform advanced image […]

Build a receipt and invoice processing pipeline with Amazon Textract

In today’s business landscape, organizations are constantly seeking ways to optimize their financial processes, enhance efficiency, and drive cost savings. One area that holds significant potential for improvement is accounts payable. On a high level, the accounts payable process includes receiving and scanning invoices, extraction of the relevant data from scanned invoices, validation, approval, and […]

Best practices for building secure applications with Amazon Transcribe

Amazon Transcribe is an AWS service that allows customers to convert speech to text in either batch or streaming mode. It uses machine learning–powered automatic speech recognition (ASR), automatic language identification, and post-processing technologies. Amazon Transcribe can be used for transcription of customer care calls, multiparty conference calls, and voicemail messages, as well as subtitle […]

Boost your content editing with Contentful and Amazon Bedrock

This post is co-written with Matt Middleton from Contentful. Today, jointly with Contentful, we are announcing the launch of the AI Content Generator powered by Amazon Bedrock. The AI Content Generator powered by Amazon Bedrock is an app available on the Contentful Marketplace that allows users to create, rewrite, summarize, and translate content using cutting-edge […]

Unlock the potential of generative AI in industrial operations

In this post, multi-shot prompts are retrieved from an embedding containing successful Python code run on a similar data type (for example, high-resolution time series data from Internet of Things devices). The dynamically constructed multi-shot prompt provides the most relevant context to the FM, and boosts the FM’s capability in advanced math calculation, time series data processing, and data acronym understanding. This improved response facilitates enterprise workers and operational teams in engaging with data, deriving insights without requiring extensive data science skills.

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

With the batch inference API, you can use Amazon Bedrock to run inference with foundation models in batches and get responses more efficiently. This post shows how to implement self-consistency prompting via batch inference on Amazon Bedrock to enhance model performance on arithmetic and multiple-choice reasoning tasks.

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 […]

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 […]

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, […]