AWS Machine Learning

NOVEMBER 30, 2023

SageMaker makes it easy to deploy models into production directly through API calls to the service. It’s a low-level API available for Java, C++, Go, JavaScript, Node.js, PHP, Ruby, and Python. It’s a low-level API available for Java, C++, Go, JavaScript, Node.js, PHP, Ruby, and Python.

Benchmark 126

Benchmark APIs Scripts Engineering 126

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 119

Benchmark Scripts Metrics APIs 119

AWS Machine Learning

FEBRUARY 12, 2025

Amazon Bedrock , a fully managed service offering high-performing foundation models from leading AI companies through a single API, has recently introduced two significant evaluation capabilities: LLM-as-a-judge under Amazon Bedrock Model Evaluation and RAG evaluation for Amazon Bedrock Knowledge Bases. 0]}-{evaluator_model.split('.')[0]}-{datetime.now().strftime('%Y-%m-%d-%H-%M-%S')}"

Metrics 100

Metrics Engineering APIs Benchmark 100

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. This value range is 0–100%.

Benchmark 102

Benchmark Metrics APIs Engineering 102

AWS Machine Learning

JUNE 15, 2023

It features interactive Jupyter notebooks with self-contained code in PyTorch, JAX, TensorFlow, and MXNet, as well as real-world examples, exposition figures, and math. ACT allows you to customize translation output on the fly by providing tailored translation examples in the form of parallel data.

APIs 102

APIs Benchmark Best practices Engineering 102

AWS Machine Learning

JANUARY 28, 2025

For example, a prompt that generates 100 tokens in one model might generate 150 tokens in another. Consider benchmarking your user experience to find the best latency for your use case, considering that most humans cant read faster than 225 words per minute and therefore extremely fast response can hinder user experience.

Benchmark 75

Benchmark APIs Engineering Metrics 75

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. A prompt has three main types of content: input, context, and examples.

Healthcare 134

Healthcare Engineering APIs Benchmark 134

AWS Machine Learning

APRIL 22, 2024

It provides examples of use cases and best practices for using generative AI’s potential to accelerate sustainability and ESG initiatives, as well as insights into the main operational challenges of generative AI for sustainability. Figure 1 illustrates selected examples of use cases of generative AI for sustainability across the value chain.

Best practices 138

Best practices Benchmark Transportation Engineering 138

AWS Machine Learning

NOVEMBER 26, 2024

For example, we could use Instruction fine-tuning to increase the model performance on an incident classification or summarization. Tasks We will showcase three example tasks to delve into using LLMs in the context of an SOC. Following these examples, the model is then prompted to generate the SQL query for a question of interest.

APIs 101

APIs Metrics SaaS Engineering 101

Lumoa

DECEMBER 8, 2022

How to add your competitors’ public reviews to the mix, so you can get a reliable benchmark and win in the market. There are many ways to use the integration function, and this is just one example. Lumoa has very clear open APIs and based on your goals, integrations can serve various purposes.

Customer Experience 88

Customer Experience APIs Benchmark Marketing 88

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

AWS Machine Learning

MARCH 13, 2024

You will also find a Deploy button, which takes you to a landing page where you can test inference with an example payload. Deploy Gemma with SageMaker Python SDK You can find the code showing the deployment of Gemma on JumpStart and an example of how to use the deployed model in this GitHub notebook. This looks pretty good!

Benchmark 133

Benchmark Scripts APIs Feedback 133

AWS Machine Learning

NOVEMBER 18, 2024

Sonnet, also newly released, setting new industry benchmarks for graduate-level reasoning and improvements in grasping complex instructions. It exposes an API endpoint through Amazon API Gateway that proxies the initial prompt request to a Python-based AWS Lambda function, which calls Amazon Bedrock twice. Choose Next again.

APIs 105

APIs Entertainment Benchmark Advertising 105

Spearline

FEBRUARY 3, 2020

With such a rise in popularity of mobile usage around the world, we are delighted to announce that from February 2020, our customers will be able to test the sending of an SMS message to a destination specified by them, via the Spearline API. Access real-time reporting and analytics via Spearline API polling.

Telecommunications 92

Telecommunications APIs Benchmark Enterprise 92

AWS Machine Learning

JULY 10, 2024

Red-teaming engages human testers to probe an AI system for flaws in an adversarial style, and complements our other testing techniques, which include automated benchmarking against publicly available and proprietary datasets, human evaluation of completions against proprietary datasets, and more.

Government 135

Government Education Best practices APIs 135

AWS Machine Learning

JUNE 13, 2023

For example, in order to share expensive GPU resources between multiple models, we were responsible for allocating rigid memory fractions to models that were specified during deployment. In addition, deployments are now as simple as calling Boto3 SageMaker APIs and attaching the proper auto scaling policies.

APIs 95

APIs Benchmark Engineering Management 95

AWS Machine Learning

APRIL 20, 2023

The majority of data is non-fraudulent (284,315 samples), with only 492 samples corresponding to fraudulent examples. 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. Running Advanced job.

APIs 101

APIs Metrics Benchmark Engineering 101

AWS Machine Learning

SEPTEMBER 12, 2024

On Hugging Face, the Massive Text Embedding Benchmark (MTEB) is provided as a leaderboard for diverse text embedding tasks. It currently provides 129 benchmarking datasets across 8 different tasks on 113 languages. medium instance to demonstrate deploying the model as an API endpoint using an SDK through SageMaker JumpStart.

APIs 132

APIs Benchmark Enterprise Construction 132

AWS Machine Learning

OCTOBER 31, 2022

For example, 8 V100 GPUs (32GB each) are sufficient to hold the model states replica of a 10B-parameter model which needs about 200GB of memory when training with Adam optimizer using mixed-precision. To get started, follow Modify a PyTorch Training Script to adapt SMPs’ APIs in your training script. Benchmarking performance.

Scripts 94

Scripts Benchmark APIs Engineering 94

AWS Machine Learning

AUGUST 22, 2024

Snowflake Arctic is a family of enterprise-grade large language models (LLMs) built by Snowflake to cater to the needs of enterprise users, exhibiting exceptional capabilities (as shown in the following benchmarks ) in SQL querying, coding, and accurately following instructions. To learn more, refer to API documentation.

Enterprise 127

Enterprise APIs Benchmark Scripts 127

AWS Machine Learning

JANUARY 10, 2023

We first benchmark the performance of our model on a single instance to identify the TPS it can handle per our acceptable latency requirements. The entire set of code for the example is available in the following GitHub repository. Overview of solution. For CPUUtilization , you may see percentages above 100% at first in CloudWatch.

Best practices 100

Best practices Scripts APIs Metrics 100

AWS Machine Learning

MARCH 14, 2024

By the end, you will have solid guidelines and a helpful flow chart for determining the best method to develop your own FM-powered applications, grounded in real-life examples. The following screenshot shows an example of a zero-shot prompt with the Anthropic Claude 2.1 In these instructions, we didn’t provide any examples.

Best practices 133

Best practices Engineering Chatbots Enterprise 133

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. Sampling configuration and benchmarking process. Dataset preparation.

Benchmark 96

Benchmark APIs Metrics Scripts 96

AWS Machine Learning

JUNE 6, 2024

Jina Embeddings v2 is the preferred choice for experienced ML scientists for the following reasons: State-of-the-art performance – We have shown on various text embedding benchmarks that Jina Embeddings v2 models excel on tasks such as classification, reranking, summarization, and retrieval.

Benchmark 117

Benchmark Enterprise Construction APIs 117

AWS Machine Learning

DECEMBER 16, 2022

Finally, we’ll benchmark performance of 13B, 50B, and 100B parameter auto-regressive models and wrap up with future work. For training a different model type, you can follow the API document to learn about how to apply SMP APIs. You can find an example in the same training script train_gpt_simple.py. 50B parameter Bloom.

Benchmark 97

Benchmark Engineering APIs Scripts 97

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 97

Best practices APIs Metrics Accountability 97

AWS Machine Learning

APRIL 27, 2023

In this post, we cover the benefits of CustomOps, their efficient implementation on Trainium, and examples to get you started with CustomOps on Trainium-powered Trn1 instances. Take for example operators such as TopK, LayerNorm, or ZeroCompression, which read data from memory and only use it for a minimal number of ALU calculations.

APIs 98

APIs Engineering Scripts Benchmark 98

AWS Machine Learning

JULY 25, 2024

Although existing large language model (LLM) benchmarks like MT-bench evaluate model capabilities, they lack the ability to validate the application layers. In the following example test plan, you have a claim with the ID claim-006 in your test system. Configure the target, which should be a type that Agent Evaluation supports.

APIs 132

APIs Engineering Best practices Virtual Agent 132

AWS Machine Learning

FEBRUARY 12, 2025

Amazon Bedrock is a fully managed service that makes FMs from leading AI startups and Amazon available through an API, so you can choose from a wide range of FMs to find the model that is best suited for your use case. Solution overview The solution comprises two main steps: Generate synthetic data using the Amazon Bedrock InvokeModel API.

APIs 74

APIs Management Benchmark Scripts 74

AWS Machine Learning

JUNE 12, 2024

Amazon Bedrock is a fully managed service that makes foundation models (FMs) from leading artificial intelligence (AI) startups and Amazon available through an API, so you can choose from a wide range of FMs to find the model that is best suited for your use case. The following screenshot shows an example email.

APIs 127

APIs Accountability Benchmark Government 127

AWS Machine Learning

NOVEMBER 30, 2023

When ML models deployed on instances receive API calls from a large number of clients, a random distribution of requests can work very well when there is not a lot of variability in your requests and responses. The endpoint uniformly distributes incoming requests to ML instances using a round-robin algorithm.

Engineering 119

Engineering APIs Benchmark Enterprise 119

AWS Machine Learning

JUNE 21, 2024

The application’s frontend is accessible through Amazon API Gateway , using both edge and private gateways. Amazon Bedrock offers a practical environment for benchmarking and a cost-effective solution for managing workloads due to its serverless operation. The following diagram visualizes the architecture diagram and workflow.

Engineering 124

Engineering Construction APIs Benchmark 124

AWS Machine Learning

JULY 26, 2023

We have examples available for Stable Diffusion 2.1 This notebook presents an end-to-end example of how to compile a Stable Diffusion model, save the compiled Neuron models, and load it into the runtime for inference. The emb tensor is used as example input for the torch_neuronx.trace function. model on the GitHub repo.

Scripts 98

Scripts APIs Benchmark Engineering 98

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. For example, by storing a document in the different processed phases, you can reverse processing to the previous step if needed.

APIs 116

APIs Metrics Benchmark Enterprise 116

AWS Machine Learning

NOVEMBER 1, 2024

As part of this post, we first introduce general best practices for fine-tuning Anthropic’s Claude 3 Haiku on Amazon Bedrock, and then present specific examples with the TAT- QA dataset (Tabular And Textual dataset for Question Answering). This comparison can help you understand when and how to apply these different techniques effectively.

Best practices 96

Best practices APIs Finance Engineering 96

AWS Machine Learning

DECEMBER 1, 2022

JumpStart also offers example notebooks that use Amazon SageMaker features like spot instance training and experiments over a large variety of model types and use cases. These example notebooks contain code that shows how to apply ML solutions by using SageMaker and JumpStart. This is called zero-shot in-context learning.

APIs 117

APIs Benchmark Advertising Banking 117

AWS Machine Learning

JULY 18, 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.

APIs 128

APIs Technology Analytics Benchmark 128