AWS Partner Network (APN) Blog

Category: Artificial Intelligence

Accenture-APN-Blog-102022

Realizing Your Clean Energy Goals with Accenture’s Data-Led Transformation on AWS

While utilities have historically been rich with data from customers, programs, and assets, many organizations often manage data in siloes. Source data can also be disorganized, with deficiencies in defined quality assurance and quality control processes. Learn how utilities are successfully embracing Accenture’s data-led transformation (DLT) and leveraging accelerators powered by AWS to reach their business objectives and meet regulatory obligations.

Capgemini-APN-Blog-092122

Capgemini’s Edge-Capable Targeted Campaigns for Popup Stores Using Deep Learning

As direct to customer (D2C) gains popularity among retailers, there’s an increasing need to mix online and offline experiences to improve customer engagements and sentiment. One such popular channel is popup stores. This post explores a Capgemini solution that uses Amazon Web Services (AWS) to help retailers engage with customers in a smart way. The solution leverages deep learning to enhance the customer experience through gamification and provides key insights and marketing leads to retailers.

ClearScale-APN-Blog-080222

PBS Provides Tailored Experiences for Viewers with Amazon Personalize

Like many of today’s leading media and streaming platforms, PBS wanted to take its overall user experience to the next level. That’s why PBS approached AWS Premier Tier Consulting Partner ClearScale, a leader in machine learning. ClearScale came up with a detailed roadmap for tackling PBS’s recommendation system project that included data operations, MLOps, and demonstrational user interface. Together, PBS and ClearScale decided to move forward with an AWS-powered solution on top of Amazon Personalize.

Nuvalence-APN-Blog-072122

Aligning Business Intelligence and AI/ML with a Data Mesh Platform on AWS

Data mesh is emerging as a paradigm for generating data-driven value and is gaining real-world adoption within industries like financial services and automotive. Learn about the user journeys of two types of data consumers in a mesh platform: business intelligence and data scientists. Explore how BI and AI/ML overlap within a set of data domains, and how a platform architecture further enables the desired experiences within a data mesh.

OctoML-APN-Blog-071922

Deploy Accelerated ML Models to Amazon Elastic Kubernetes Service Using OctoML CLI

Deploying machine learning (ML) models as a packaged container with hardware-optimized acceleration, without compromising accuracy and while being financially feasible, can be challenging. As machine learning models become the brains of modern applications, developers need a simpler way to deploy trained ML models to live endpoints for inference. This post explores how a ML engineer can take a trained model, optimize and containerize the model using OctoML CLI, and deploy it to Amazon EKS.

Gartner-AWS-CAIDS-2022-thumbnail

AWS Named a Leader in 2022 Gartner Magic Quadrant for Cloud AI Developer Services

Industry analyst firm Gartner has published its annual report evaluating cloud AI developer services, the 2022 Magic Quadrant for Cloud AI Developer Services (CAIDS). AWS was once again named a Leader and placed highest among 13 recognized vendors for “Ability to Execute.” Choosing the right provider for cloud AI developer services is critically important right now. AWS Partners can leverage this report with their customers to showcase the value that AWS will bring to them.

Personalize Your Customers’ Experience with Easy-Access AWS AI Services

AWS artificial intelligence services can serve as a kind of ready-made building block that enable companies of all sizes and sectors to gain experience and create their own AI services, without having to build the fundamental functions from the bottom up. Via the cloud, companies can access AWS AI services and create their own chatbots, image analysis, or personalization tools, for example. To implement and customize these services, companies can draw on the expertise of Trivadis – Part of Accenture.

Snowflake-APN-Blog-062722

Enabling Data-Centric Artificial Intelligence Through Snowflake and Amazon SageMaker

Data-centric AI (DCAI) has been described as the discipline of systematically engineering the data used to build an AI system. It prescribes prioritizing improving data quality over tweaking algorithms to improve machine learning models. In this post, explore a DCAI solution built on Snowflake and Amazon SageMaker to serve as a factory for predictive analytics solutions. Learn about Snowflake’s integrations with SageMaker and get hands-on resources to help you put these capabilities into practice.

Infosys-APN-Blog-042022

Delivering Closed Loop Assurance with Infosys Digital Operations Ecosystem Platform on AWS

A closed loop assurance system predicts network events, such as faults and congestions, that are highly probable of causing service degradation or interruption, and automatically take preventive actions to avert service disruptions. Learn how Infosys leveraged AWS data streaming, data analytics, and machine learning services to ingest, process, and analyze high volumes of data from disparate sources; and to build ML models to predict network events that cause service degradation.

Provectus-APN-Blog-041322

Machine Learning Infrastructure for Commercial Real Estate Insights Platform

Learn now Provectus looked into how machine learning models were prototyped and evaluated at VTS, and then delivered a template-based solution enabling their data scientists to more easily create Amazon SageMaker jobs, pipelines, endpoints, and other AWS resources. The resulting coherent set of templates, with usage cookbook and extension guidelines, was applied successfully on an ML model that predicted leasing outcomes.