AWS Machine Learning

MARCH 6, 2025

Current RAG pipelines frequently employ similarity-based metrics such as ROUGE , BLEU , and BERTScore to assess the quality of the generated responses, which is essential for refining and enhancing the models capabilities. More sophisticated metrics are needed to evaluate factual alignment and accuracy.

Metrics 120

Metrics Enterprise APIs Engineering 120

AWS Machine Learning

NOVEMBER 15, 2024

All text-to-image benchmarks are evaluated using Recall@5 ; text-to-text benchmarks are evaluated using NDCG@10. Text-to-text benchmark accuracy is based on BEIR, a dataset focused on out-of-domain retrievals (14 datasets). Generic text-to-image benchmark accuracy is based on Flickr and CoCo.

Benchmark 109

Benchmark Enterprise Construction Engineering 109

AWS Machine Learning

APRIL 24, 2024

The Amazon EU Design and Construction (Amazon D&C) team is the engineering team designing and constructing Amazon warehouses. The Amazon D&C team implemented the solution in a pilot for Amazon engineers and collected user feedback. of overall responses) can be addressed by user education and prompt engineering.

Engineering 133

Engineering Feedback Construction Analytics 133

AWS Machine Learning

MARCH 27, 2025

This requirement translates into time and effort investment of trained personnel, who could be support engineers or other technical staff, to review tens of thousands of support cases to arrive at an even distribution of 3,000 per category. If the use case doesnt yield discrete outputs, task-specific metrics are more appropriate.

Education 112

Education Engineering APIs Enterprise 112

Callminer

AUGUST 1, 2017

Metrics, Measure, and Monitor – Make sure your metrics and associated goals are clear and concise while aligning with efficiency and effectiveness. Make each metric public and ensure everyone knows why that metric is measured. Jeff Greenfield is the co-founder and chief operating officer of C3 Metrics.

Contact Center 334

Contact Center Call Center Average Handle Time Real estate 334

Joe Rawlinson

MAY 17, 2022

To get the most return out of their pay-per-click (PPC) campaign, businesses should learn which metrics to focus on and exert the most of their efforts. Now, the question is—what are the metrics and figures to benchmark for every industry? CPC is a metric that measures the cost an advertiser pays to the publisher (e.g.,

Benchmark 15

Benchmark Advertising Entertainment Real estate 15

AWS Machine Learning

MAY 2, 2024

As new embedding models are released with incremental quality improvements, organizations must weigh the potential benefits against the associated costs of upgrading, considering factors like computational resources, data reprocessing, integration efforts, and projected performance gains impacting business metrics.

Benchmark 129

Benchmark Metrics Enterprise APIs 129

Amity

NOVEMBER 21, 2016

Customer benchmarking — the practice of identifying where a customer can improve or is already doing well by comparing to other customers – helps Customer Success Managers to deliver unique value to their customers. I’ve found that SaaS vendors use seven distinct strategies to empower CSMs with customer benchmarking.

Benchmark 59

Benchmark SaaS Best practices Metrics 59

AWS Machine Learning

JUNE 20, 2024

Additionally, evaluation can identify potential biases, hallucinations, inconsistencies, or factual errors that may arise from the integration of external sources or from sub-optimal prompt engineering. This makes it difficult to apply standard evaluation metrics like BERTScore ( Zhang et al.

Metrics 138

Metrics Engineering Accountability Benchmark 138

CSM Magazine

MARCH 26, 2025

Continuous education involves more than glancing at release announcements it includes testing beta features, benchmarking real world results, and actively sharing insights. Engineers versed in the OWASP Top 10 address common security weaknesses with minimal fuss. This method can save hours of coding time and avoid technical debt.

Finance 52

Finance Benchmark Enterprise Surveys 52

AWS Machine Learning

SEPTEMBER 6, 2024

This post focuses on evaluating and interpreting metrics using FMEval for question answering in a generative AI application. FMEval is a comprehensive evaluation suite from Amazon SageMaker Clarify , providing standardized implementations of metrics to assess quality and responsibility. Question Answer Fact Who is Andrew R.

Best practices 93

Best practices Metrics Sales Benchmark 93

AWS Machine Learning

FEBRUARY 12, 2025

As a next step, you can explore fine-tuning your own LLM with Medusa heads on your own dataset and benchmark the results for your specific use case, using the provided GitHub repository. About the authors Daniel Zagyva is a Senior ML Engineer at AWS Professional Services.

Scripts 79

Scripts Metrics Engineering Accountability 79

CX Global Media

SEPTEMBER 17, 2018

They Leverage Their Data : The best performing contact centers leverage their operational and quality metrics in concert with their customer satisfaction scores and customer comments. They Avoid Benchmarking: High-performing contact center leaders do not waste a lot of time benchmarking their contact center performance.

Contact Center 113

Contact Center Benchmark Surveys Coaching 113

AWS Machine Learning

FEBRUARY 8, 2023

In this option, you select an ideal value of an Amazon CloudWatch metric of your choice, such as the average CPU utilization or throughput that you want to achieve as a target, and SageMaker will automatically scale in or scale out the number of instances to achieve the target metric. However, you can use any other benchmarking tool.

Benchmark 104

Benchmark Metrics APIs Engineering 104

AWS Machine Learning

MAY 9, 2024

Benchmarking and metrics – Defining standardized metrics and benchmarking to measure and compare the performance of AI models, and the business value derived. Setting KPIs and metrics is pivotal to gauge effectiveness. Performance management Setting KPIs and metrics is pivotal to gauge effectiveness.

Government 133

Government Best practices Benchmark Metrics 133

AWS Machine Learning

DECEMBER 5, 2023

Model training benchmarks In large-scale training jobs where GPU communication is a significant bottleneck, SMDDP can markedly improve training speeds, as measured by model TFLOPS/GPU. Karan Dhiman is a Software Development Engineer at AWS, based in Toronto, Canada. 24xlarge nodes (512 NVIDIA A100 GPUs) PyTorch FSDP 97.89

Benchmark 122

Benchmark Engineering Scripts Metrics 122

AWS Machine Learning

SEPTEMBER 21, 2023

In particular, we provide practical best practices for different customization scenarios, including training models from scratch, fine-tuning with additional data using full or parameter-efficient techniques, Retrieval Augmented Generation (RAG), and prompt engineering.

Best practices 134

Best practices Engineering Metrics Benchmark 134

AWS Machine Learning

NOVEMBER 19, 2024

Leave the session inspired to bring Amazon Q Apps to supercharge your teams’ productivity engines. Gain insights into training strategies, productivity metrics, and real-world use cases to empower your developers to harness the full potential of this game-changing technology.

APIs 109

APIs Enterprise Best practices Government 109

AWS Machine Learning

MAY 13, 2024

In this part of the blog series, we review techniques of prompt engineering and Retrieval Augmented Generation (RAG) that can be employed to accomplish the task of clinical report summarization by using Amazon Bedrock. Prompt engineering helps to effectively design and improve prompts to get better results on different tasks with LLMs.

Healthcare 136

Healthcare Engineering APIs Benchmark 136

AWS Machine Learning

FEBRUARY 24, 2025

Performance metrics and benchmarks According to Mistral, the instruction-tuned version of the model achieves over 81% accuracy on Massive Multitask Language Understanding (MMLU) with 150 tokens per second latency, making it currently the most efficient model in its category.

APIs 97

APIs Enterprise Benchmark Feedback 97

AWS Machine Learning

JULY 24, 2024

This post is a joint collaboration between Salesforce and AWS and is being cross-published on both the Salesforce Engineering Blog and the AWS Machine Learning Blog. To get started, see this guide. __ About the Authors Pawan Agarwal is the Senior Director of Software Engineering at Salesforce. Salesforce, Inc.

Engineering 130

Engineering CRM SaaS Sales 130

AWS Machine Learning

OCTOBER 4, 2022

With G5 instances, ML customers get high performance and a cost-efficient infrastructure to train and deploy larger and more sophisticated models for natural language processing (NLP), computer vision (CV), and recommender engine use cases. Benchmarking approach. We also study the impact of full precision vs. mixed precision.

Benchmark 96

Benchmark Engineering Metrics Technology 96

AWS Machine Learning

FEBRUARY 24, 2023

In addition, load testing can help guide the auto scaling strategies using the right metrics rather than iterative trial and error methods. For the context of load testing in this post, you can download our sample code from the GitHub repo to reproduce the results or use it as a template to benchmark your own models.

Benchmark 104

Benchmark Metrics Enterprise Advertising 104

AWS Machine Learning

JUNE 20, 2023

Machine learning (ML) engineers have traditionally focused on striking a balance between model training and deployment cost vs. performance. The Carbontracker study estimates that training GPT-3 from scratch may emit up to 85 metric tons of CO2 equivalent, using clusters of specialized hardware accelerators.

Benchmark 98

Benchmark Engineering Banking Chatbots 98

AWS Machine Learning

APRIL 20, 2023

Each machine learning (ML) system has a unique service level agreement (SLA) requirement with respect to latency, throughput, and cost metrics. An advanced job is a custom load test job that allows you to perform extensive benchmarks based on your ML application SLA requirements, such as latency, concurrency, and traffic pattern.

APIs 101

APIs Metrics Benchmark Engineering 101

Totango

JULY 17, 2024

Chris Dishman Stop guessing, start growing: The customer success metrics that matter If you’re only tracking metrics like usage or churn, then you’re only seeing a small piece of the puzzle. When you track outcome-based metrics that help prove value to your customers, then you can proactively identify areas for growth and expansion.

Sales 100

Sales Metrics Accountability Benchmark 100

AWS Machine Learning

SEPTEMBER 18, 2024

The backbone of these advancements is ZOE, Zeta’s Optimization Engine. Together, these AI-driven tools and technologies aren’t just reshaping how brands perform marketing tasks; they’re setting new benchmarks for what’s possible in customer engagement. Saurabh Gupta is a Principal Engineer at Zeta Global.

APIs 122

APIs Engineering Analytics Marketing 122

AWS Machine Learning

JANUARY 19, 2024

The concepts illustrated in this post can be applied to applications that use PLM features, such as recommendation systems, sentiment analysis, and search engines. The performance of the architecture is typically measured using metrics such as validation loss. training.py ).

Metrics 132

Metrics Scripts Benchmark Enterprise 132

AWS Machine Learning

JUNE 13, 2023

This post is co-written with Jad Chamoun, Director of Engineering at Forethought Technologies, Inc. and Salina Wu, Senior ML Engineer at Forethought Technologies, Inc. Forethought had to manage model inference on Amazon EKS ourselves, which was a burden on engineering efficiency. 2xlarge instances. seconds Large (550 tokens) 12.7

APIs 97

APIs Benchmark Engineering Management 97

AWS Machine Learning

SEPTEMBER 11, 2024

Each GPC has a raster engine for graphics and several TPCs. The NeuronCores contain four engines : the first three include a ScalarEngine for scalar calculations, a VectorEngine for vector calculations, and a TensorEngine for matrix calculations. And finally, there is a C++ programmable GPSIMD-engine allowing for custom operations.

Benchmark 115

Benchmark Banking Analytics Big data 115

Totango

APRIL 11, 2019

An illuminated “check engine” light is scary because it doesn’t offer any solution. For many, “check engine” may as well just say “car broken”—and that’s terrifying. These categories are also represented numerically as a relative rating out of 100 based on a combination of established metric thresholds.

Metrics 90

Metrics Upselling Accountability Enterprise 90

AWS Machine Learning

AUGUST 3, 2022

To showcase how this reduction can help you getting started with the creation of a custom entity recognizer, we ran some tests on a few open-source datasets and collected performance metrics. In this post, we walk you through the benchmarking process and the results we obtained while working on subsampled datasets. Dataset preparation.

Benchmark 97

Benchmark APIs Metrics Scripts 97

AWS Machine Learning

NOVEMBER 22, 2023

As data and system conditions change, the model performance and efficiency metrics are tracked to ensure retraining is performed when needed. Your organization can choose the retraining mechanism—it can be quarterly, monthly, or based on science metrics, such as when accuracy drops below a given threshold.

APIs 118

APIs Metrics Benchmark Enterprise 118

AWS Machine Learning

MAY 30, 2023

Benchmarks We benchmarked evaluation metrics to ensure that the model quality didn’t deteriorate with the multi-GPU training path compared to single-GPU training. We also benchmarked on large datasets to ensure that our distributed GPU setups were performant and scalable. 8xlarge 15 1679 15.22 17 1509 15.51 19 1326 15.22

Benchmark 98

Benchmark Metrics Engineering Enterprise 98

AWS Machine Learning

APRIL 22, 2024

Figure 5 offers an overview on generative AI modalities and optimization strategies, including prompt engineering , Retrieval Augmented Generation , and fine-tuning or continued pre-training. Establish a metrics pipeline to provide insights into the sustainability contributions of your generative AI initiatives.

Best practices 140

Best practices Benchmark Transportation Engineering 140

AWS Machine Learning

JUNE 17, 2024

PrestoDB is an open source SQL query engine that is designed for fast analytic queries against data of any size from multiple sources. For more information on the TPC-H data, its database entities, relationships, and characteristics, refer to TPC Benchmark H. Twilio needed to implement an MLOps pipeline that queried data from PrestoDB.

Scripts 122

Scripts Engineering Metrics Big data 122

ChurnZero

AUGUST 25, 2021

It will help you set benchmarks to get a clear picture of your performance with your customers. A Net Promoter Score (NPS) is a customer satisfaction benchmark that measures how likely your customers are to recommend you to a friend or colleague. Keeping track of this metric can also help reduce support possibly needed in the future.

Journey mapping 98

Journey mapping Benchmark Feedback Metrics 98