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Fine-tune multimodal models for vision and text use cases on Amazon SageMaker JumpStart

AWS Machine Learning

Vision Instruct models demonstrated impressive performance on the challenging DocVQA benchmark for visual question answering. ANLS is a metric used to evaluate the performance of models on visual question answering tasks, which measures the similarity between the model’s predicted answer and the ground truth answer. The Meta Llama 3.2

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A review of purpose-built accelerators for financial services

AWS Machine Learning

in 2012 is now widely referred to as ML’s “Cambrian Explosion.” Accelerator benchmarking When considering compute services, users benchmark measures such as price-performance, absolute performance, availability, latency, and throughput. There are various types of representative benchmark commonly seen.

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What the Subscription Economy Teaches Us About Kick-Ass Customer Experience

BlueOcean

The pandemic only accelerated the growth of the subscription economy, which has seen an incredible 437% growth since 2012—and a 66% increase from 2019 to 2020. That means sharing policy changes, marketing or sales objectives, goals, and metrics, and ensuring the team understands how their roles impact each of these things.

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Machine learning with decentralized training data using federated learning on Amazon SageMaker

AWS Machine Learning

The evaluation takes place on a testing dataset existing only on the server, and the new improved accuracy metrics are produced. She is also part of the Technical Field Community dedicated to hardware acceleration and helps with testing and benchmarking AWS Inferentia and AWS Trainium workloads.

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What the Subscription Economy Teaches Us About Kick-Ass Customer Experience

BlueOcean

The pandemic only accelerated the growth of the subscription economy, which has seen an incredible 437% growth since 2012—and a 66% increase from 2019 to 2020. That means sharing policy changes, marketing or sales objectives, goals, and metrics, and ensuring the team understands how their roles impact each of these things.

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Generation Disruptor: Optimizing the Influence of Gen Z on Your Contact Center

Serenova

We’ve shared before that Millennial (born between 1981 and 1996) and Gen Z (born between 1997 and 2012) agents are having major impact on the way today’s contact centers operate. By giving agents visibility into their performance, they can benchmark their efforts against other agents and themselves. billion total people).

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What Is a Knowledge Base and Why Is It Useful?

Comm100

Forrester has found that FAQ page use is on the rise, increasing from 67% to 76% between 2012 and 2014. Free Download] Live Chat Benchmark Report 2018. The latest version of live chat benchmark report is based on real world data and with suggestions from customer service experts. Let us know in the comments below. Download Now.