AWS Machine Learning

SEPTEMBER 28, 2023

In this post, we describe the enhancements to the forecasting capabilities of SageMaker Canvas and guide you on using its user interface (UI) and AutoML APIs for time-series forecasting. While the SageMaker Canvas UI offers a code-free visual interface, the APIs empower developers to interact with these features programmatically.

APIs 119

APIs Construction Finance Enterprise 119

AWS Machine Learning

DECEMBER 2, 2024

This integration provides a powerful multilingual model that excels in reasoning benchmarks. The integration offers enterprise-grade features including model evaluation metrics, fine-tuning and customization capabilities, and collaboration tools, all while giving customers full control of their deployment.

Enterprise 111

Enterprise Benchmark Technology APIs 111

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 94

APIs Enterprise Benchmark Feedback 94

AWS Machine Learning

MARCH 27, 2025

Where discrete outcomes with labeled data exist, standard ML methods such as precision, recall, or other classic ML metrics can be used. These metrics provide high precision but are limited to specific use cases due to limited ground truth data. If the use case doesnt yield discrete outputs, task-specific metrics are more appropriate.

Education 111

Education Engineering APIs Enterprise 111

AWS Machine Learning

NOVEMBER 19, 2024

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. Discover how to create and manage evaluation jobs, use automatic and human reviews, and analyze critical metrics like accuracy, robustness, and toxicity.

APIs 107

APIs Enterprise Best practices Government 107

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 128

Benchmark Metrics Enterprise APIs 128

AWS Machine Learning

JULY 2, 2024

You can see that for the 45 models we benchmarked, there is a 1.35x latency improvement (geomean for the 45 models). You can see that for the 33 models we benchmarked, there is around 2x performance improvement (geomean for the 33 models). We benchmarked 45 models using the scripts from the TorchBench repo.

Benchmark 121

Benchmark Scripts Metrics APIs 121

AWS Machine Learning

MARCH 3, 2025

They enable applications requiring very low latency or local data processing using familiar APIs and tool sets. Through comparative benchmarking tests, we illustrate how deploying FMs in Local Zones closer to end users can significantly reduce latencya critical factor for real-time applications such as conversational AI assistants.

APIs 83

APIs Benchmark Metrics Healthcare 83

AWS Machine Learning

FEBRUARY 8, 2023

Although you can integrate the model directly into an application, the approach that works well for production-grade applications is to deploy the model behind an endpoint and then invoke the endpoint via a RESTful API call to obtain the inference. However, you can use any other benchmarking tool.

Benchmark 103

Benchmark Metrics APIs Engineering 103

AWS Machine Learning

OCTOBER 18, 2023

The solution uses the following services: Amazon API Gateway is a fully managed service that makes it easy for developers to publish, maintain, monitor, and secure APIs at any scale. Purina’s solution is deployed as an API Gateway HTTP endpoint, which routes the requests to obtain pet attributes.

APIs 127

APIs Metrics Consulting Consulting 127

AWS Machine Learning

JULY 29, 2024

You can also either use the SageMaker Canvas UI, which provides a visual interface for building and deploying models without needing to write any code or have any ML expertise, or use its automated machine learning (AutoML) APIs for programmatic interactions.

APIs 118

APIs Scripts Benchmark Metrics 118

ChurnZero

MARCH 18, 2022

With so many SaaS metrics floating around, and even more opinions on when and how to use them, it can be hard to know if you’re measuring what really matters. Leading SaaS expert, Dave Kellogg, and ChurnZero CEO, You Mon Tsang, sat down to answer all the questions you want to know about SaaS metrics like ARR, NRR, GRR, LTV, and CAC (i.e.,

SaaS 98

SaaS Metrics Surveys Enterprise 98

AWS Machine Learning

FEBRUARY 6, 2023

The former question addresses model selection across model architectures, while the latter question concerns benchmarking trained models against a test dataset. This post provides details on how to implement large-scale Amazon SageMaker benchmarking and model selection tasks. swin-large-patch4-window7-224 195.4M efficientnet-b5 29.0M

APIs 98

APIs Scripts Metrics Benchmark 98

Interaction Metrics

APRIL 17, 2025

At Interaction Metrics, we help organizations of all sizes improve how they collect and use feedback. Ill get to the top 17 Qualtrics alternatives in just a minute, but first, a shameless plug for Interaction Metrics. It supports SMS/MMS and offline collection, with exportable reports (XLS, CSV, PDF) and HRIS integration via API.

Surveys 48

Surveys Enterprise B2B Analytics 48

AWS Machine Learning

JULY 18, 2024

The ingestion workflow transforms these curated questions into vector embeddings using Amazon Titan Text Embeddings model API. The system first converts the query into a vector embedding using the Amazon Titan Text Embeddings model API, which is accessed securely through PrivateLink.

Chatbots 134

Chatbots APIs Accountability Finance 134

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

AWS Machine Learning

NOVEMBER 22, 2023

You can save time, money, and labor by implementing classifications in your workflow, and documents go to downstream applications and APIs based on document type. This helps you avoid throttling limits on API calls due to polling the Get* APIs. Model monitoring The performance of ML models is monitored for degradation over time.

APIs 117

APIs Metrics Benchmark Enterprise 117

AWS Machine Learning

JANUARY 10, 2023

From there, we dive into how you can track and understand the metrics and performance of the SageMaker endpoint utilizing Amazon CloudWatch metrics. We first benchmark the performance of our model on a single instance to identify the TPS it can handle per our acceptable latency requirements. Metrics to track.

Best practices 100

Best practices Scripts APIs Metrics 100

Spearline

JULY 21, 2022

Consequently, no other testing solution can provide the range and depth of testing metrics and analytics. And testingRTC offers multiple ways to export these metrics, from direct collection from webhooks, to downloading results in CSV format using the REST API. Happy days! You can check framerate information for video here too.

Scripts 98

Scripts APIs Metrics Analytics 98

AWS Machine Learning

AUGUST 3, 2022

For example, you can immediately start detecting entities such as people, places, commercial items, dates, and quantities via the Amazon Comprehend console , AWS Command Line Interface , or Amazon Comprehend APIs. In this post, we walk you through the benchmarking process and the results we obtained while working on subsampled datasets.

Benchmark 96

Benchmark APIs Metrics Scripts 96

AWS Machine Learning

JUNE 20, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

Metrics 137

Metrics Engineering Accountability Benchmark 137

AWS Machine Learning

JUNE 13, 2023

In addition, all SageMaker real-time endpoints benefit from built-in capabilities to manage and monitor models, such as including shadow variants , auto scaling , and native integration with Amazon CloudWatch (for more information, refer to CloudWatch Metrics for Multi-Model Endpoint Deployments ).

APIs 95

APIs Benchmark Engineering Management 95

AWS Machine Learning

MARCH 19, 2024

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models from leading AI companies and Amazon via a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI. A limitation of the approach is its larger computational cost.

APIs 135

APIs Benchmark SaaS Engineering 135

AWS Machine Learning

SEPTEMBER 18, 2024

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. From our experience, artifact server has some limitations, such as limits on artifact size (because of sending it using REST API).

APIs 121

APIs Engineering Analytics Marketing 121

AWS Machine Learning

AUGUST 2, 2024

Queries are sent to the backend using a REST API defined in Amazon API Gateway , a fully managed service that makes it straightforward for developers to create, publish, maintain, monitor, and secure APIs at any scale, and implemented through an API Gateway private integration.

APIs 127

APIs Analytics Chatbots Engineering 127

AWS Machine Learning

APRIL 12, 2023

All the training and evaluation metrics were inspected manually from Amazon Simple Storage Service (Amazon S3). For every epoch in our training, we were already sending our training metrics through stdOut in the script. This allows us to compare training metrics like accuracy and precision across multiple runs as shown below.

Scripts 108

Scripts APIs Metrics Best practices 108

AWS Machine Learning

OCTOBER 2, 2024

In addition, they use the developer-provided instruction to create an orchestration plan and then carry out the plan by invoking company APIs and accessing knowledge bases using Retrieval Augmented Generation (RAG) to provide an answer to the user’s request. In Part 1, we focus on creating accurate and reliable agents.

Best practices 98

Best practices APIs Metrics Accountability 98

AWS Machine Learning

MAY 13, 2024

This is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading artificial intelligence (AI) companies like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon through a single API. These metrics will assess how well a machine-generated summary compares to one or more reference summaries.

Healthcare 136

Healthcare Engineering APIs Benchmark 136

AWS Machine Learning

SEPTEMBER 21, 2023

Use managed services – Depending on your expertise and specific use case, weigh the options between opting for Amazon Bedrock , a serverless, fully managed service that provides access to a diverse range of foundation models through an API, or deploying your models on a fully managed infrastructure by using Amazon SageMaker.

Best practices 133

Best practices Engineering Metrics Benchmark 133

AWS Machine Learning

SEPTEMBER 11, 2024

In terms of resulting speedups, the approximate order is programming hardware, then programming against PBA APIs, then programming in an unmanaged language such as C++, then a managed language such as Python. The CUDA API and SDK were first released by NVIDIA in 2007. GPU PBAs, 4% other PBAs, 4% FPGA, and 0.5%

Benchmark 113

Benchmark Banking Analytics Big data 113

AWS Machine Learning

JANUARY 19, 2024

The goal of NAS is to find the optimal architecture for a given problem by searching over a large set of candidate architectures using techniques such as gradient-free optimization or by optimizing the desired metrics. The performance of the architecture is typically measured using metrics such as validation loss. training.py ).

Metrics 131

Metrics Scripts Benchmark Enterprise 131

Pointillist

JULY 25, 2018

Success Metrics for the Team. Ultimately, the biggest success metric for the Champion is to be able to show the Executive Sponsor and key Stakeholders that real business value has been gained through the use of customer journey analytics. Success Metrics for the Project. Success Metrics for the Business. Churn Rate.

Analytics 93

Analytics Government Metrics APIs 93

AWS Machine Learning

NOVEMBER 1, 2024

We also provide insights on how to achieve optimal results for different dataset sizes and use cases, backed by experimental data and performance metrics. Tools and APIs – For example, when you need to teach Anthropic’s Claude 3 Haiku how to use your APIs well. We focus on the task of answering questions about the table.

Best practices 97

Best practices APIs Finance Metrics 97

AWS Machine Learning

JUNE 29, 2022

Syne Tune allows us to find a better hyperparameter configuration that achieves a relative improvement between 1-4% compared to default hyperparameters on popular GLUE benchmark datasets. Furthermore, we add another callback function to Hugging Face’s Trainer API that reports the validation performance after each epoch back to Syne Tune.

Benchmark 101

Benchmark Metrics APIs Scripts 101

AWS Machine Learning

APRIL 22, 2024

Examples of tools you can use to advance sustainability initiatives are: Amazon Bedrock – a fully managed service that provides access to high-performing FMs from leading AI companies through a single API, enabling you to choose the right model for your sustainability use cases.

Best practices 139

Best practices Benchmark Transportation Engineering 139

AWS Machine Learning

AUGUST 26, 2024

This involves benchmarking new models against our current selections across various metrics, running A/B tests, and gradually incorporating high-performing models into our production pipeline. API design Account summary generation requests are handled asynchronously to eliminate client wait times for responses.

Sales 128

Sales Accountability Feedback Metrics 128

AWS Machine Learning

NOVEMBER 22, 2023

Define goals and metrics – The function needs to deliver value to the organization in different ways. Establish regular cadence – The group should come together regularly to review their goals and metrics. This allows the workload to be implemented to achieve the desired goals of the organization.

Finance 113

Finance Best practices APIs Accountability 113