AWS Architecture Blog

Category: Artificial Intelligence

Notional architecture for Serverless Bot Framework & Salesforce Integration

Build Chatbots using Serverless Bot Framework with Salesforce Integration

Conversational interfaces have become increasingly popular, both on web and mobile. Businesses realize these interactions are resulting in quicker resolutions of customer concerns than a more traditional approach of agent interactions. An intelligent chatbot on top of customer-facing platforms comes with inherent benefits. Among these are 24/7 customer support with no agent wait-times, improved operational […]

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Architecture from admin perspective

Field Notes: Accelerate Research with Managed Jupyter on Amazon SageMaker

Research organizations across industry verticals have unique needs. These include facilitating stakeholder collaboration, setting up compute environments for experimentation, handling large datasets, and more. In essence, researchers want the freedom to focus on their research, without the undifferentiated heavy-lifting of managing their environments. In this blog, I show you how to set up a managed […]

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Figure 3: Overall Architecture

Scaling up a Serverless Web Crawler and Search Engine

Introduction Building a search engine can be a daunting undertaking. You must continually scrape the web and index its content so it can be retrieved quickly in response to a user’s query. The goal is to implement this in a way that avoids infrastructure complexity while remaining elastic. However, the architecture that achieves this is […]

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2020

Top 15 Architecture Blog Posts of 2020

The goal of the AWS Architecture Blog is to highlight best practices and provide architectural guidance. We publish thought leadership pieces that encourage readers to discover other technical documentation, such as solutions and managed solutions, other AWS blogs, videos, reference architectures, whitepapers, and guides, Training & Certification, case studies, and the AWS Architecture Monthly Magazine. […]

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Video Redaction - Multiprocessing

Field Notes: Speed Up Redaction of Connected Car Data by Multiprocessing Video Footage with Amazon Rekognition

In the blog, Redacting Personal Data from Connected Cars Using Amazon Rekognition, we demonstrated how you can redact personal data such as human faces using Amazon Rekognition. Traversing the video, frame by frame, and identifying personal information in each frame takes time. This solution is great for small video clips, where you do not need […]

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Field Notes: Improving Call Center Experiences with Iterative Bot Training Using Amazon Connect and Amazon Lex

This post was co-written by Abdullah Sahin, senior technology architect at Accenture, and Muhammad Qasim, software engineer at Accenture.  Organizations deploying call-center chat bots are interested in evolving their solutions continuously, in response to changing customer demands. When developing a smart chat bot, some requests can be predicted (for example following a new product launch […]

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Amazon Personalize: from datasets to a recommendation API

Automating Recommendation Engine Training with Amazon Personalize and AWS Glue

Customers from startups to enterprises observe increased revenue when personalizing customer interactions. Still, many companies are not yet leveraging the power of personalization, or, are relying solely on rule-based strategies. Those strategies are effort-intensive to maintain and not effective. Common reasons for not launching machine learning (ML) based personalization projects include: the complexity of aggregating […]

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Field Notes: Applying Machine Learning to Vegetation Management using Amazon SageMaker

This post was co-written by Louis Lim, a manager in Accenture AWS Business Group, and Soheil Moosavi, a data scientist consultant in Accenture Applied Intelligence (AAI) team. Virtually every electric customer in the US and Canada has, at one time or another, experienced a sustained electric outage as a direct result of a tree and […]

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Field Notes: Comparing Algorithm Performance Using MLOps and the AWS Cloud Development Kit

Comparing machine learning algorithm performance is fundamental for machine learning practitioners, and data scientists. The goal is to evaluate the appropriate algorithm to implement for a known business problem. Machine learning performance is often correlated to the usefulness of the model deployed. Improving the performance of the model typically results in an increased accuracy of […]

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Olympus Tower - Grov Technologies

Building a Controlled Environment Agriculture Platform

This post was co-written by Michael Wirig, Software Engineering Manager at Grōv Technologies. A substantial percentage of the world’s habitable land is used for livestock farming for dairy and meat production. The dairy industry has leveraged technology to gain insights that have led to drastic improvements and are continuing to accelerate. A gallon of milk […]

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