AWS Machine Learning

OCTOBER 9, 2024

Amazon Lookout for Metrics is a fully managed service that uses machine learning (ML) to detect anomalies in virtually any time-series business or operational metrics—such as revenue performance, purchase transactions, and customer acquisition and retention rates—with no ML experience required. To learn more, see the documentation.

Metrics 82

Metrics APIs Engineering Accountability 82

AWS Machine Learning

AUGUST 7, 2024

To find an answer, RAG takes an approach that uses vector search across the documents. Rather than scanning every single document to find the answer, with the RAG approach, you turn the texts (knowledge base) into embeddings and store these embeddings in the database. Generate questions from the document using an Amazon Bedrock LLM.

APIs 122

APIs Chatbots Metrics Education 122

AWS Machine Learning

APRIL 19, 2023

The ability to effectively handle and process enormous amounts of documents has become essential for enterprises in the modern world. Due to the continuous influx of information that all enterprises deal with, manually classifying documents is no longer a viable option.

APIs 87

APIs Metrics Enterprise Best practices 87

AWS Machine Learning

OCTOBER 12, 2022

A massive amount of business documents are processed daily across industries. Many of these documents are paper-based, scanned into your system as images, or in an unstructured format like PDF. Each company may apply unique rules associated with its business background while processing these documents.

APIs 84

APIs Construction Metrics Engineering 84

AWS Machine Learning

JUNE 5, 2024

You can use Amazon Comprehend to identify the language of the text; extract key phrases, places, people, brands, or events; understand sentiment about products or services; and identify the main topics from a library of documents. For minimum training requirements, see General quotas for document classification.

APIs 103

APIs Metrics Accountability Enterprise 103

AWS Machine Learning

NOVEMBER 3, 2022

In Part 1 of this series, we discussed intelligent document processing (IDP), and how IDP can accelerate claims processing use cases in the insurance industry. We discussed how we can use AWS AI services to accurately categorize claims documents along with supporting documents. Part 1: Classification and extraction of documents.

Analytics 78

Analytics APIs Healthcare Big data 78

AWS Machine Learning

DECEMBER 29, 2022

Documents are a primary tool for record keeping, communication, collaboration, and transactions across many industries, including financial, medical, legal, and real estate. The millions of mortgage applications and hundreds of millions of W2 tax forms processed each year are just a few examples of such documents.

APIs 105

APIs Banking Real estate Healthcare 105

AWS Machine Learning

MAY 9, 2024

It is designed to be deeply integrated into the FAST platform and use all of Verisk’s documentation, training materials, and collective expertise. Having that transparency helped Verisk identify areas of the system where their documents were lacking and needed some restructuring.

Engineering 130

Engineering Customer Support APIs Government 130

AWS Machine Learning

NOVEMBER 21, 2022

Organizations across industries such as retail, banking, finance, healthcare, manufacturing, and lending often have to deal with vast amounts of unstructured text documents coming from various sources, such as news, blogs, product reviews, customer support channels, and social media. Extract and analyze data from documents.

Scripts 74

Scripts Metrics APIs Healthcare 74

AWS Machine Learning

MARCH 27, 2024

This requires carefully combining applications and metrics to provide complete awareness, accuracy, and control. The zAdviser uses Amazon Bedrock to provide summarization, analysis, and recommendations for improvement based on the DORA metrics data. It’s also vital to avoid focusing on irrelevant metrics or excessively tracking data.

Enterprise 106

Enterprise APIs Metrics Engineering 106

AWS Machine Learning

NOVEMBER 22, 2023

When a customer has a production-ready intelligent document processing (IDP) workload, we often receive requests for a Well-Architected review. To follow along with this post, you should be familiar with the previous posts in this series ( Part 1 and Part 2 ) and the guidelines in Guidance for Intelligent Document Processing on AWS.

APIs 111

APIs Metrics Benchmark Enterprise 111

AWS Machine Learning

NOVEMBER 7, 2024

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. API Gateway is serverless and hence automatically scales with traffic. API Gateway also provides a WebSocket API. Incoming requests to the gateway go through this point.

Enterprise 106

Enterprise APIs Government Accountability 106

AWS Machine Learning

JULY 3, 2024

This new functionality offers industry-leading safety measures that filter harmful content and protect sensitive information in your documents, improving user experience and aligning with organizational standards. The query is then augmented to have the retrieved document chunks, prompt, and guardrails configuration.

APIs 118

APIs Banking Metrics Management 118

AWS Machine Learning

APRIL 24, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon using a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI.

APIs 120

APIs Engineering Metrics Management 120

AWS Machine Learning

SEPTEMBER 25, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing FMs from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

APIs 114

APIs Call flow Accountability Technology 114

AWS Machine Learning

NOVEMBER 15, 2024

Principal wanted to use existing internal FAQs, documentation, and unstructured data and build an intelligent chatbot that could provide quick access to the right information for different roles. Model monitoring of key NLP metrics was incorporated and controls were implemented to prevent unsafe, unethical, or off-topic responses.

Chatbots 122

Chatbots Engineering Enterprise Feedback 122

AWS Machine Learning

MAY 5, 2023

Using architecture diagrams as an example, the solution needs to search through reference links and technical documents for architecture diagrams and identify the services present. Therefore, users without ML expertise can enjoy the benefits of a custom labels model through an API call, because a significant amount of overhead is reduced.

Engineering 109

Engineering APIs Scripts Enterprise 109

AWS Machine Learning

OCTOBER 29, 2024

Observability refers to the ability to understand the internal state and behavior of a system by analyzing its outputs, logs, and metrics. For a detailed breakdown of the features and implementation specifics, refer to the comprehensive documentation in the GitHub repository.

Best practices 103

Best practices Feedback Metrics APIs 103

AWS Machine Learning

JUNE 20, 2024

In addition, RAG architecture can lead to potential issues like retrieval collapse , where the retrieval component learns to retrieve the same documents regardless of the input. This makes it difficult to apply standard evaluation metrics like BERTScore ( Zhang et al.

Metrics 121

Metrics Engineering Accountability Benchmark 121

AWS Machine Learning

MAY 30, 2024

To serve their customers, Vitech maintains a repository of information that includes product documentation (user guides, standard operating procedures, runbooks), which is currently scattered across multiple internal platforms (for example, Confluence sites and SharePoint folders).

Chatbots 119

Chatbots Engineering APIs Technology 119

AWS Machine Learning

JANUARY 12, 2023

Amazon Comprehend is a fully managed and continuously trained natural language processing (NLP) service that can extract insight about the content of a document or text. The overriding goal for The Very Group’s engineering team was to prevent any PII data from reaching documents within Elasticsearch. Overview of solution.

Engineering 124

Engineering APIs Accountability Metrics 124

AWS Machine Learning

MAY 30, 2024

AWS Prototyping successfully delivered a scalable prototype, which solved CBRE’s business problem with a high accuracy rate (over 95%) and supported reuse of embeddings for similar NLQs, and an API gateway for integration into CBRE’s dashboards. The following diagram illustrates the web interface and API management layer.

Real estate 121

Real estate APIs Metrics Construction 121

AWS Machine Learning

NOVEMBER 20, 2024

By narrowing down the search space to the most relevant documents or chunks, metadata filtering reduces noise and irrelevant information, enabling the LLM to focus on the most relevant content. This approach narrows down the search space to the most relevant documents or passages, reducing noise and irrelevant information.

Construction 110

Construction APIs Metrics Accountability 110

AWS Machine Learning

APRIL 17, 2024

Metrics allow teams to understand workload behavior and optimize resource allocation and utilization, diagnose anomalies, and increase overall infrastructure efficiency. Metrics are exposed to Amazon Managed Service for Prometheus by the neuron-monitor DaemonSet, which deploys a minimal container, with the Neuron tools installed.

APIs 114

APIs Metrics Accountability Management 114

AWS Machine Learning

SEPTEMBER 14, 2023

Document categorization or classification has significant benefits across business domains – Improved search and retrieval – By categorizing documents into relevant topics or categories, it makes it much easier for users to search and retrieve the documents they need. politics, sports) that a document belongs to.

APIs 114

APIs Government Accountability Engineering 114

AWS Machine Learning

APRIL 23, 2024

Here are some features which we will cover: AWS CloudFormation support Private network policies for Amazon OpenSearch Serverless Multiple S3 buckets as data sources Service Quotas support Hybrid search, metadata filters, custom prompts for the RetreiveAndGenerate API, and maximum number of retrievals.

APIs 122

APIs Enterprise Scripts Accountability 122

AWS Machine Learning

DECEMBER 4, 2024

Document summarization : Process vast amounts of business content in real time, such as summarizing thousands of customer call transcripts daily, enabling insights at a scale previously limited by latency constraints. You can optionally add request metadata to these inference requests to filter your invocation logs for specific use cases.

APIs 111

APIs Metrics Healthcare Chatbots 111

AWS Machine Learning

NOVEMBER 15, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

APIs 105

APIs Government Best practices Metrics 105

AWS Machine Learning

OCTOBER 29, 2024

All of this data is centralized and can be used to improve metrics in scenarios such as sales or call centers. For integration between services, we use API Gateway as an event trigger for our Lambda function, and DynamoDB as a highly scalable database to store our customer details.

Engineering 105

Engineering APIs Sales Enterprise 105

AWS Machine Learning

SEPTEMBER 8, 2023

Amazon Rekognition makes it easy to add image analysis capability to your applications without any machine learning (ML) expertise and comes with various APIs to fulfil use cases such as object detection, content moderation, face detection and analysis, and text and celebrity recognition, which we use in this example.

APIs 114

APIs Scripts Entertainment Personalization 114

AWS Machine Learning

MAY 2, 2024

As new embedding models are released with incremental quality improvements, organizations must weigh the potential benefits against the associated costs of upgrading, considering factors like computational resources, data reprocessing, integration efforts, and projected performance gains impacting business metrics.

Benchmark 119

Benchmark Metrics Enterprise APIs 119

AWS Machine Learning

JUNE 20, 2024

The idea is to use metrics to compare experiments during development. Running predictions on the test set records results with the metrics needed to compare experiments. A common metric is the accuracy, which is the percentage of the correct results. Each document holds an example question and information about it.

Construction 101

Construction APIs Metrics Engineering 101

AWS Machine Learning

NOVEMBER 22, 2023

The IDP Well-Architected Lens is intended for all AWS customers who use AWS to run intelligent document processing (IDP) solutions and are searching for guidance on how to build secure, efficient, and reliable IDP solutions on AWS. This post focuses on the Operational Excellence pillar of the IDP solution.

Best practices 102

Best practices Metrics Feedback Enterprise 102

AWS Machine Learning

NOVEMBER 14, 2024

Customers can use the SageMaker Studio UI or APIs to specify the SageMaker Model Registry model to be shared and grant access to specific AWS accounts or to everyone in the organization. With this launch, customers can now seamlessly share and access ML models registered in SageMaker Model Registry between different AWS accounts.

Government 87

Government Management APIs Accountability 87

AWS Machine Learning

SEPTEMBER 5, 2023

Earlier this year, we announced Amazon Bedrock , a serverless API to access foundation models from Amazon and our generative AI partners. Although it’s currently in Private Preview, its serverless API allows you to use foundation models from Amazon, Anthropic, Stability AI, and AI21, without having to deploy any endpoints yourself.

APIs 111

APIs Metrics Chatbots Engineering 111

AWS Machine Learning

SEPTEMBER 20, 2024

Use cases overview Some key use cases for Amazon Q Business for organizations include: Providing grounded responses to employees: An organization can deploy Amazon Q Business on their internal data, documents, products, and services. The web experience can be created using either the AWS Management Console or the Amazon Q Business APIs.

Wireless 93

Wireless Enterprise APIs Chatbots 93

AWS Machine Learning

AUGUST 15, 2024

Lastly, if you don’t want to set up custom integrations with large data sources, you can simply upload your documents and support multi-turn conversations. After authentication, Amazon API Gateway and Amazon S3 deliver the contents of the Content Designer UI. input – A placeholder for the current user utterance or question.

Chatbots 120

Chatbots Banking APIs Enterprise 120