Remove services start-up-acceleration
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35 Indicators that a Company Isn’t Customer-Centric

CX Accelerator

By Jeremy Watkin and the CX Accelerator Community I’ve got a big trip coming up, and in preparation, I needed to check my flight itinerary so I could book a rental car and long-term airport parking. After pushing a bit more for a supervisor, I was left with no choice but to hang up and try again. Again, huh?

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AI-Automated Fiber Customer Installation: A Seamless Self-Service Solution

TechSee

Fiber Customer Installation has Many Tied up in Knots  In today’s digital-first world, the demand for high-speed internet is more critical than ever. However, the installation process for fiber optic services, particularly for residential customers, often presents significant challenges.

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5 Top Customer Service Articles For the Week of November 9, 2020

ShepHyken

Each week I read a number of customer service and customer experience articles from various resources. The experience equation: Happy employees and customers accelerate growth by Vala Afshar. ZDNet) Research shows the relationship between employee experience (EX) and customer experience (CX) and its impact on accelerated growth.

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Building a Great CX Team

CX Accelerator

In this post, we want to delve into what those skills are and how we would prioritize each if we were building a CX team from the ground up. DESIGN THINKING Good service design is based on a deep understanding of customers in order to improve the quality of a service and the interactions between the service provider and their customers.

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Driving advanced analytics outcomes at scale using Amazon SageMaker powered PwC’s Machine Learning Ops Accelerator

AWS Machine Learning

To address these customer challenges, PwC Australia developed Machine Learning Ops Accelerator as a set of standardized process and technology capabilities to improve the operationalization of AI/ML models that enable cross-functional collaboration across teams throughout ML lifecycle operations.

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Amazon SageMaker model parallel library now accelerates PyTorch FSDP workloads by up to 20%

AWS Machine Learning

Highly accurate LLMs can require terabytes of training data and thousands or even millions of hours of accelerator compute time to achieve target accuracy. To complete training and launch products in a timely manner, customers rely on parallelism techniques to distribute this enormous workload across up to thousands of accelerator devices.

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Amazon EC2 DL2q instance for cost-efficient, high-performance AI inference is now generally available

AWS Machine Learning

Amazon Elastic Compute Cloud (Amazon EC2) DL2q instances, powered by Qualcomm AI 100 Standard accelerators, can be used to cost-efficiently deploy deep learning (DL) workloads in the cloud. New DL2q instance highlights Each DL2q instance incorporates eight Qualcomm Cloud AI100 accelerators, with an aggregated performance of over 2.8