APIs, Best practices, Big data and Document

Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning

JANUARY 26, 2024

The goal of this post is to empower AI and machine learning (ML) engineers, data scientists, solutions architects, security teams, and other stakeholders to have a common mental model and framework to apply security best practices, allowing AI/ML teams to move fast without trading off security for speed.

Best practices

Best practices Government Engineering Accountability

Automate caption creation and search for images at enterprise scale using generative AI and Amazon Kendra

AWS Machine Learning

AUGUST 2, 2023

Amazon Kendra supports a variety of document formats , such as Microsoft Word, PDF, and text from various data sources. In this post, we focus on extending the document support in Amazon Kendra to make images searchable by their displayed content. This means you can manipulate and ingest your data as needed.

Enterprise

Enterprise Healthcare APIs Big data

Identify objections in customer conversations using Amazon Comprehend to enhance customer experience without ML expertise

AWS Machine Learning

APRIL 24, 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 steps are as follows: The client side calls Amazon API Gateway as the entry point to provide a client message as input. API Gateway bypasses the request to Lambda.

APIs

APIs Customer Experience Feedback Chatbots

The IoT Chronicles Part 2: Three Big Security Threats—and How to Solve Them

Avaya

NOVEMBER 16, 2016

Open APIs: An open API model is advantageous in that it allows developers outside of companies to easily access and use APIs to create breakthrough innovations. At the same time, however, publicly available APIs are also exposed ones. billion GB of data were being produced every day in 2012 alone!)

APIs

APIs Transportation Enterprise Healthcare

Enable fully homomorphic encryption with Amazon SageMaker endpoints for secure, real-time inferencing

AWS Machine Learning

MARCH 23, 2023

Applications and services can call the deployed endpoint directly or through a deployed serverless Amazon API Gateway architecture. To learn more about real-time endpoint architectural best practices, refer to Creating a machine learning-powered REST API with Amazon API Gateway mapping templates and Amazon SageMaker.

Scripts

Scripts APIs Government Analytics

Localize content into multiple languages using AWS machine learning services

AWS Machine Learning

JULY 19, 2022

Synchronous translation has limits on the document size it can translate; as of this writing, it’s set to 5,000 bytes. For larger document sizes, consider using an asynchronous route of creating the job using start_text_translation_job and checking the status via describe_text_translation_job.

Engineering

Engineering APIs Education Best practices

Designing generative AI workloads for resilience

AWS Machine Learning

FEBRUARY 1, 2024

This pipeline could be a batch pipeline if you prepare contextual data in advance, or a low-latency pipeline if you’re incorporating new contextual data on the fly. In the batch case, there are a couple challenges compared to typical data pipelines. He entered the big data space in 2013 and continues to explore that area.

Best practices

Best practices Engineering SaaS APIs

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

AWS Machine Learning

MAY 8, 2023

In this post, we address these limitations by implementing the access control outside of the MLflow server and offloading authentication and authorization tasks to Amazon API Gateway , where we implement fine-grained access control mechanisms at the resource level using Identity and Access Management (IAM). Adds an IAM authorizer.

APIs

APIs Government Accountability Scripts

Use Amazon SageMaker Model Card sharing to improve model governance

AWS Machine Learning

AUGUST 31, 2023

One of the tools available as part of the ML governance is Amazon SageMaker Model Cards , which has the capability to create a single source of truth for model information by centralizing and standardizing documentation throughout the model lifecycle. They provide a fact sheet of the model that is important for model governance.

Government

Government Accountability Enterprise Engineering

Use Amazon SageMaker Model Cards sharing to improve model governance

AWS Machine Learning

AUGUST 31, 2023

One of the tools available as part of the ML governance is Amazon SageMaker Model Cards , which has the capability to create a single source of truth for model information by centralizing and standardizing documentation throughout the model lifecycle. They provide a fact sheet of the model that is important for model governance.

Government

Government Accountability Enterprise Engineering

Define customized permissions in minutes with Amazon SageMaker Role Manager

AWS Machine Learning

DECEMBER 1, 2022

You can change the existing policies here by selecting the policy and editing the document. This role can also be recreated via Infrastructure as Code (IaC) by simply taking the contents of the policy documents and inserting them into your existing solution. Note that the following policy locks down Studio domain creation to VPC only.

Management

Management Government Enterprise APIs

Use streaming ingestion with Amazon SageMaker Feature Store and Amazon MSK to make ML-backed decisions in near-real time

AWS Machine Learning

APRIL 19, 2023

This example notebook demonstrates the pattern of using Feature Store as a central repository from which data scientists can extract training datasets. In addition to creating a training dataset, we use the PutRecord API to put the 1-week feature aggregations into the online feature store nightly. Nov-01,22:01:00 1 74.99 …9843 99.50

Engineering

Engineering Analytics APIs Enterprise

Call Center Reporting - A New Paradigm

Xaqt

JUNE 22, 2020

Despite significant advancements in big data and open source tools, niche Contact Center Business Intelligence providers are still wed to their own proprietary tools leaving them saddled with technical debt and an inability to innovate from within. Together, we can develop best practices and sharable templates for the entire industry.

Call Center

Call Center Contact Center Analytics Engineering

Build repeatable, secure, and extensible end-to-end machine learning workflows using Kubeflow on AWS

AWS Machine Learning

SEPTEMBER 9, 2022

In the artificial intelligence (AI) space, athenahealth uses data science and machine learning (ML) to accelerate business processes and provide recommendations, predictions, and insights across multiple services. Each project maintained detailed documentation that outlined how each script was used to build the final model.

Engineering

Engineering Healthcare APIs Scripts

Senior back-end software engineer

Stratifyd

JANUARY 3, 2019

The Senior Back-End Software Engineer will have demonstrated practical experience in building high-performance and reliable systems and possess a love for Git and all that version control provides (we can also accept a love/hate relationship with Git). Maintain and develop Stratifyd’s API layer and/or analytics pipeline.

Engineering

Engineering APIs Analytics Healthcare

Customer Contact Central

Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

Automate caption creation and search for images at enterprise scale using generative AI and Amazon Kendra

Trending Sources

Identify objections in customer conversations using Amazon Comprehend to enhance customer experience without ML expertise

The IoT Chronicles Part 2: Three Big Security Threats—and How to Solve Them

Enable fully homomorphic encryption with Amazon SageMaker endpoints for secure, real-time inferencing

Localize content into multiple languages using AWS machine learning services

Designing generative AI workloads for resilience

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

Use Amazon SageMaker Model Card sharing to improve model governance

Use Amazon SageMaker Model Cards sharing to improve model governance

Define customized permissions in minutes with Amazon SageMaker Role Manager

Use streaming ingestion with Amazon SageMaker Feature Store and Amazon MSK to make ML-backed decisions in near-real time

Call Center Reporting - A New Paradigm

Build repeatable, secure, and extensible end-to-end machine learning workflows using Kubeflow on AWS

Senior back-end software engineer

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