APIs, Government and Metrics - Customer Contact Central

Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

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. This streamlines the ML workflows, enables better visibility and governance, and accelerates the adoption of ML models across the organization.

Government

Government Management APIs Accountability

Governing the ML lifecycle at scale: Centralized observability with Amazon SageMaker and Amazon CloudWatch

AWS Machine Learning

OCTOBER 29, 2024

This post is part of an ongoing series on governing the machine learning (ML) lifecycle at scale. To start from the beginning, refer to Governing the ML lifecycle at scale, Part 1: A framework for architecting ML workloads using Amazon SageMaker. Consolidate metrics across source accounts and build unified dashboards.

Government

Government Metrics Accountability APIs

Improve governance of models with Amazon SageMaker unified Model Cards and Model Registry

AWS Machine Learning

NOVEMBER 13, 2024

You can now register machine learning (ML) models in Amazon SageMaker Model Registry with Amazon SageMaker Model Cards , making it straightforward to manage governance information for specific model versions directly in SageMaker Model Registry in just a few clicks.

Government

Government Engineering Metrics APIs

Achieve operational excellence with well-architected generative AI solutions using Amazon Bedrock

AWS Machine Learning

OCTOBER 2, 2024

However, scaling up generative AI and making adoption easier for different lines of businesses (LOBs) comes with challenges around making sure data privacy and security, legal, compliance, and operational complexities are governed on an organizational level. In this post, we discuss how to address these challenges holistically.

Government

Government APIs Enterprise Best practices

Improve governance of your machine learning models with Amazon SageMaker

AWS Machine Learning

DECEMBER 1, 2022

Overview of model governance. Model governance is a framework that gives systematic visibility into model development, validation, and usage. Model governance is applicable across the end-to-end ML workflow, starting from identifying the ML use case to ongoing monitoring of a deployed model through alerts, reports, and dashboards.

Government

Government Metrics APIs Engineering

Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning

NOVEMBER 7, 2024

We also dive deeper into access patterns, governance, responsible AI, observability, and common solution designs like Retrieval Augmented Generation. 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.

Enterprise

Enterprise APIs Government Accountability

Considerations for addressing the core dimensions of responsible AI for Amazon Bedrock applications

AWS Machine Learning

NOVEMBER 15, 2024

For now, we consider eight key dimensions of responsible AI: Fairness, explainability, privacy and security, safety, controllability, veracity and robustness, governance, and transparency. Regular evaluations allow you to adjust and steer the AI’s behavior based on feedback and performance metrics.

APIs

APIs Government Best practices Metrics

Build an Amazon SageMaker Model Registry approval and promotion workflow with human intervention

AWS Machine Learning

JANUARY 10, 2024

The solution uses AWS Lambda , Amazon API Gateway , Amazon EventBridge , and SageMaker to automate the workflow with human approval intervention in the middle. The approver approves the model by following the link in the email to an API Gateway endpoint. API Gateway invokes a Lambda function to initiate model updates.

APIs

APIs Construction Engineering Analytics

Create a Generative AI Gateway to allow secure and compliant consumption of foundation models

AWS Machine Learning

SEPTEMBER 28, 2023

Regulated and compliance-oriented industries, such as financial services, healthcare and life sciences, and government institutes, face unique challenges in ensuring the secure and responsible consumption of these models. In addition, API Registries enabled centralized governance, control, and discoverability of APIs.

APIs

APIs Government Enterprise Engineering

How Veritone uses Amazon Bedrock, Amazon Rekognition, Amazon Transcribe, and information retrieval to update their video search pipeline

AWS Machine Learning

MAY 7, 2024

With a decade of enterprise AI experience, Veritone supports the public sector, working with US federal government agencies, state and local government, law enforcement agencies, and legal organizations to automate and simplify evidence management, redaction, person-of-interest tracking, and eDiscovery.

APIs

APIs Advertising Entertainment Metrics

Enhance conversational AI with advanced routing techniques with Amazon Bedrock

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

APIs Engineering Metrics Management

Modernizing data science lifecycle management with AWS and Wipro

AWS Machine Learning

JANUARY 5, 2024

MLOps – Model monitoring and ongoing governance wasn’t tightly integrated and automated with the ML models. Reusability – Without reusable MLOps frameworks, each model must be developed and governed separately, which adds to the overall effort and delays model operationalization.

Management

Management APIs Engineering Government

Unleashing the power of generative AI: Verisk’s journey to an Instant Insight Engine for enhanced customer support

AWS Machine Learning

MAY 9, 2024

Data governance – With a wide variety of users accessing the platform and with different users having access to different data, data governance and isolation was paramount. First, they used the Amazon Kendra Retrieve API to get multiple relevant passages and excerpts based on keyword search.

Engineering

Engineering Customer Support APIs Government

Metrics for evaluating an identity verification solution

AWS Machine Learning

DECEMBER 5, 2022

Then we dive into the two key metrics used to evaluate a biometric system’s accuracy: the false match rate (also known as false acceptance rate) and false non-match rate (also known as false rejection rate). We use FMR and FNMR as our two key metrics to evaluate facial biometric systems. False non-match rate. Conclusion.

Metrics

Metrics Best practices Banking APIs

Improve visibility into Amazon Bedrock usage and performance with Amazon CloudWatch

AWS Machine Learning

JUNE 25, 2024

A new automatic dashboard for Amazon Bedrock was added to provide insights into key metrics for Amazon Bedrock models. From here you can gain centralized visibility and insights to key metrics such as latency and invocation metrics. Optionally, you can select a specific model to isolate the metrics to one model.

Metrics

Metrics APIs Government Big data

Facebook’s Conversion API – what marketers need to know

Infinity

MARCH 3, 2022

So, in autumn 2021, when Facebook partnered up with Amazon and launched the Conversion API Gateway, it was a very exciting day for Facebook advertisers. When talking Facebook and data, you’re likely to come across two key models – the Conversion API Gateway and the Facebook Pixel, but what’s the difference?

APIs

APIs Marketing Advertising Government

Improving asset health and grid resilience using machine learning

AWS Machine Learning

SEPTEMBER 8, 2023

This goal will further help Duke Energy to improve grid resiliency and comply with government regulations by identifying the defects in a timely manner. Next, we present the key metrics used for evaluating the model performance along with the evaluation of our final models. While lower precision leads to wasted human effort.

Government

Government Metrics Analytics Technology

Principal Financial Group uses QnABot on AWS and Amazon Q Business to enhance workforce productivity with generative AI

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.

Chatbots

Chatbots Engineering Enterprise Feedback

Introducing self-service quota management and higher default service quotas for Amazon Textract

AWS Machine Learning

SEPTEMBER 27, 2022

In addition to viewing the default service quotas, you can now view your account’s applied custom quotas for a specific Region, view your historical utilization metrics per applied quota, set up alarms to notify when utilization approaches a threshold, and add tags to your quotas for easier organization. Synchronous Operations. US East (N.

Self service

Self service APIs Management Accountability

Overcome the machine learning cold start challenge in fraud detection using Amazon Fraud Detector

AWS Machine Learning

APRIL 17, 2023

To help you build the right expectation of model performance, besides model AUC, Amazon Fraud Detector also reports uncertainty range metrics. The following table defines these metrics. To update the event label call the update_event_label API: import boto3 def update_event_label(event, context): fraudDetector = boto3.client('frauddetector')

APIs

APIs Government Metrics Engineering

How Earth.com and Provectus implemented their MLOps Infrastructure with Amazon SageMaker

AWS Machine Learning

JUNE 27, 2023

Machine Learning Operations (MLOps) provides the technical solution to this issue, assisting organizations in managing, monitoring, deploying, and governing their models on a centralized platform. This step produces an expanded report containing the model’s metrics.

Engineering

Engineering APIs Scripts Entertainment

Securing MLflow in AWS: Fine-grained access control with AWS native services

AWS Machine Learning

MAY 8, 2023

It offers many native capabilities to help manage ML workflows aspects, such as experiment tracking, and model governance via the model registry. This can be a challenge for enterprises in regulated industries that need to keep strong model governance for audit purposes. Now let’s dive deeper into the details. Adds an IAM authorizer.

APIs

APIs Government Accountability Scripts

How to Successfully Implement Customer Journey Analytics – Part 1

Pointillist

JULY 25, 2018

Success Metrics for the Team. Ultimately, the biggest success metric for the Champion is to be able to show the Executive Sponsor and key Stakeholders that real business value has been gained through the use of customer journey analytics. Success Metrics for the Project. Success Metrics for the Business. Churn Rate.

Analytics

Analytics Government Metrics APIs

Elevate RAG for numerical analysis using Amazon Bedrock Knowledge Bases

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

APIs Call flow Accountability Technology

Enhance your media search experience using Amazon Q Business and Amazon Transcribe

AWS Machine Learning

JULY 30, 2024

The response from API calls are displayed to the end-user. Use metadata to assign values to index attributes for sorting, filtering, and faceting your search results, or to specify access control lists to govern access to the files. The Mediasearch indexer finds and transcribes audio and video files stored in an S3 bucket.

APIs

APIs Accountability Management Entertainment

Build a classification pipeline with Amazon Comprehend custom classification (Part I)

AWS Machine Learning

SEPTEMBER 14, 2023

Governance and policy enforcement – Setting up document categorization rules helps to ensure that documents are classified correctly according to an organization’s policies and governance standards. Subsequently, this function checks the status of the training job by invoking describe_document_classifier API.

APIs

APIs Government Accountability Engineering

Best practices for building robust generative AI applications with Amazon Bedrock Agents – Part 1

AWS Machine Learning

OCTOBER 2, 2024

In addition, they use the developer-provided instruction to create an orchestration plan and then carry out the plan by invoking company APIs and accessing knowledge bases using Retrieval Augmented Generation (RAG) to provide an answer to the user’s request. Valid government-issued ID (driver’s license, passport, etc.)

Best practices

Best practices APIs Metrics Benchmark

Philips accelerates development of AI-enabled healthcare solutions with an MLOps platform built on Amazon SageMaker

AWS Machine Learning

NOVEMBER 16, 2023

With SageMaker MLOps tools, teams can easily train, test, troubleshoot, deploy, and govern ML models at scale to boost productivity of data scientists and ML engineers while maintaining model performance in production. Regulations in the healthcare industry call for especially rigorous data governance.

Healthcare

Healthcare Government Engineering APIs

Detect fraud in mobile-oriented businesses using GrabDefence device intelligence and Amazon Fraud Detector

AWS Machine Learning

OCTOBER 10, 2022

To begin performing real-time predictions, you integrate Amazon Fraud Detector’s low-latency prediction API into your application and begin sending new mobile events to generate fraud predictions. This result is sent back to your mobile app via API Gateway. Collects the risk profile from the GD API.

APIs

APIs Accountability Metrics Government

How Yara is using MLOps features of Amazon SageMaker to scale energy optimization across their ammonia plants

AWS Machine Learning

NOVEMBER 17, 2022

Their production segment is therefore an integral building block for delivering on their mission—with a clearly stated ambition to become world-leading on metrics such as safety, environmental footprint, quality, and production costs. Yara has built APIs using Amazon API Gateway to expose the sensor data to applications such as ELC.

APIs

APIs Accountability Metrics Engineering

How Druva used Amazon Bedrock to address foundation model complexity when building Dru, Druva’s backup AI copilot

AWS Machine Learning

NOVEMBER 1, 2024

Customers use Druva Data Resiliency Cloud to simplify data protection, streamline data governance, and gain data visibility and insights. Dru on the backend decodes log data, deciphers error codes, and invokes API calls to troubleshoot. This approach allowed us to break the problem down into multiple steps: Identify the API route.

APIs

APIs Scripts Engineering Government

Implementing Knowledge Bases for Amazon Bedrock in support of GDPR (right to be forgotten) requests

AWS Machine Learning

MAY 31, 2024

Amazon Bedrock is a fully managed service that makes foundational models (FMs) from leading artificial intelligence (AI) companies and Amazon available through an API, so you can choose from a wide range of FMs to find the model that’s best suited for your use case. Only users who have the logs: Unmask IAM permission can view unmasked data.

Best practices

Best practices APIs Accountability Personalization

Your guide to generative AI and ML at AWS re:Invent 2024

AWS Machine Learning

NOVEMBER 19, 2024

Plus, learn how to evolve from data aggregation to data semantics to support data-driven applications while maintaining flexibility and governance. Gain insights into training strategies, productivity metrics, and real-world use cases to empower your developers to harness the full potential of this game-changing technology.

APIs

APIs Enterprise Best practices Government

Identify rooftop solar panels from satellite imagery using Amazon Rekognition Custom Labels

AWS Machine Learning

JULY 19, 2022

Governments in many countries are providing incentives and subsidies to households to install solar panels as part of small-scale renewable energy schemes. To test the model output, we use a Jupyter notebook to run Python code to detect custom labels in a supplied image by calling Amazon Rekognition APIs. Fine-tune the trained model.

APIs

APIs Metrics Enterprise Marketing

Orchestrate Ray-based machine learning workflows using Amazon SageMaker

AWS Machine Learning

SEPTEMBER 18, 2023

Trained models can be stored, versioned, and tracked in Amazon SageMaker Model Registry for governance and management. It has APIs for common ML data preprocessing operations like parallel transformations, shuffling, grouping, and aggregations. He works with government sponsored entities, helping them build AI/ML solutions using AWS.

Scripts

Scripts APIs Government Construction

Reduce food waste to improve sustainability and financial results in retail with Amazon Forecast

AWS Machine Learning

OCTOBER 27, 2022

With environmental, social, and governance (ESG) initiatives becoming more important for companies, our customer, one of Greater China region’s top convenience store chains, has been seeking a solution to reduce food waste (currently over $3.5 We use the AutoPredictor API, which is also accessible through the Forecast console.

APIs

APIs Best practices Metrics Government

Prevent account takeover at login with the new Account Takeover Insights model in Amazon Fraud Detector

AWS Machine Learning

OCTOBER 5, 2022

For a real-time prediction, you call the GetEventPrediction API after a user presents valid login credentials to quantify the risk of ATO. If you provide labels, Amazon Fraud Detector uses them to automatically calculate an Account Takeover Discovery Rate and display it in the model performance metrics. Category. Upload event data.

Accountability

Accountability APIs Metrics Engineering

Build well-architected IDP solutions with a custom lens – Part 1: Operational excellence

AWS Machine Learning

NOVEMBER 22, 2023

Pursue Metrics-Driven Quality and Continuous Improvement In IDP, what gets measured gets improved. Define and track key metrics related to document accuracy, processing times, and model efficacy. Defined metrics for IDP success – Establish and monitor clear metrics to measure the success and impact of the IDP operations.

Best practices

Best practices Metrics Feedback Enterprise

The Weather Company enhances MLOps with Amazon SageMaker, AWS CloudFormation, and Amazon CloudWatch

AWS Machine Learning

JULY 8, 2024

The monitoring results are stored in Amazon S3 and published as a CloudWatch metric , and can be used to set up an alarm. Boto3 SDK – The AWS SDK for Python (Boto3) provides a Python API for AWS infrastructure services. The alarm is used later to invoke training, send automatic emails, or any other desired action.

Engineering

Engineering Enterprise APIs Government

MLOps foundation roadmap for enterprises with Amazon SageMaker

AWS Machine Learning

JUNE 24, 2022

The data is cataloged via the AWS Glue Data Catalog and shared with other users and accounts via AWS Lake Formation (the data governance layer). Then the ML pipeline checks if the produced accuracy metrics (such as F1, precision, and gain deciles) pass the necessary thresholds. The following diagram shows this updated architecture.

Enterprise

Enterprise Engineering Accountability APIs

Detect real and live users and deter bad actors using Amazon Rekognition Face Liveness

AWS Machine Learning

APRIL 11, 2023

These customers verify user identity by matching the user’s face in a selfie captured by a device camera with a government-issued identity card photo or preestablished profile photo. Amazon Rekognition Face Liveness cloud APIs are available in the US East (N.

APIs

APIs Accountability Government Healthcare

The executive’s guide to generative AI for sustainability

AWS Machine Learning

APRIL 22, 2024

Organizations are facing ever-increasing requirements for sustainability goals alongside environmental, social, and governance (ESG) practices. Establish a metrics pipeline to provide insights into the sustainability contributions of your generative AI initiatives. A Gartner, Inc.

Best practices

Best practices Benchmark Transportation Engineering

Automate the deployment of an Amazon Forecast time-series forecasting model

AWS Machine Learning

MAY 4, 2023

During training, Forecast calculates accuracy metrics that you use to evaluate the predictor and decide whether to use the predictor to generate a forecast. CreateAutoPredictor PredictorForecastOptimizationMetric Defines the accuracy metric used to optimize the predictor. For more details, refer to Importing Datasets.

Metrics

Metrics APIs Management Government

FMOps/LLMOps: Operationalize generative AI and differences with MLOps

AWS Machine Learning

SEPTEMBER 1, 2023

The infrastructure code for all these accounts is versioned in a shared service account (advanced analytics governance account) that the platform team can abstract, templatize, maintain, and reuse for the onboarding to the MLOps platform of every new team. 15K available FM reference Step 1.

Engineering

Engineering Accountability Construction APIs

Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

Governing the ML lifecycle at scale: Centralized observability with Amazon SageMaker and Amazon CloudWatch

Trending Sources

Improve governance of models with Amazon SageMaker unified Model Cards and Model Registry

Achieve operational excellence with well-architected generative AI solutions using Amazon Bedrock

Improve governance of your machine learning models with Amazon SageMaker

Build a multi-tenant generative AI environment for your enterprise on AWS

Considerations for addressing the core dimensions of responsible AI for Amazon Bedrock applications

Build an Amazon SageMaker Model Registry approval and promotion workflow with human intervention

Create a Generative AI Gateway to allow secure and compliant consumption of foundation models

How Veritone uses Amazon Bedrock, Amazon Rekognition, Amazon Transcribe, and information retrieval to update their video search pipeline

Enhance conversational AI with advanced routing techniques with Amazon Bedrock

Modernizing data science lifecycle management with AWS and Wipro

Unleashing the power of generative AI: Verisk’s journey to an Instant Insight Engine for enhanced customer support

Metrics for evaluating an identity verification solution

Improve visibility into Amazon Bedrock usage and performance with Amazon CloudWatch

Facebook’s Conversion API – what marketers need to know

Improving asset health and grid resilience using machine learning

Principal Financial Group uses QnABot on AWS and Amazon Q Business to enhance workforce productivity with generative AI

Introducing self-service quota management and higher default service quotas for Amazon Textract

Overcome the machine learning cold start challenge in fraud detection using Amazon Fraud Detector

How Earth.com and Provectus implemented their MLOps Infrastructure with Amazon SageMaker

Securing MLflow in AWS: Fine-grained access control with AWS native services

How to Successfully Implement Customer Journey Analytics – Part 1

Elevate RAG for numerical analysis using Amazon Bedrock Knowledge Bases

Enhance your media search experience using Amazon Q Business and Amazon Transcribe

Build a classification pipeline with Amazon Comprehend custom classification (Part I)

Best practices for building robust generative AI applications with Amazon Bedrock Agents – Part 1

Philips accelerates development of AI-enabled healthcare solutions with an MLOps platform built on Amazon SageMaker

Detect fraud in mobile-oriented businesses using GrabDefence device intelligence and Amazon Fraud Detector

How Yara is using MLOps features of Amazon SageMaker to scale energy optimization across their ammonia plants

How Druva used Amazon Bedrock to address foundation model complexity when building Dru, Druva’s backup AI copilot

Implementing Knowledge Bases for Amazon Bedrock in support of GDPR (right to be forgotten) requests

Your guide to generative AI and ML at AWS re:Invent 2024

Identify rooftop solar panels from satellite imagery using Amazon Rekognition Custom Labels

Orchestrate Ray-based machine learning workflows using Amazon SageMaker

Reduce food waste to improve sustainability and financial results in retail with Amazon Forecast

Prevent account takeover at login with the new Account Takeover Insights model in Amazon Fraud Detector

Build well-architected IDP solutions with a custom lens – Part 1: Operational excellence

The Weather Company enhances MLOps with Amazon SageMaker, AWS CloudFormation, and Amazon CloudWatch

MLOps foundation roadmap for enterprises with Amazon SageMaker

Detect real and live users and deter bad actors using Amazon Rekognition Face Liveness

The executive’s guide to generative AI for sustainability

Automate the deployment of an Amazon Forecast time-series forecasting model

FMOps/LLMOps: Operationalize generative AI and differences with MLOps

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