AWS Machine Learning

MAY 15, 2024

Next, we present the solution architecture and process flows for machine learning (ML) model building, deployment, and inferencing. Acting as a model hub, JumpStart provided a large selection of foundation models and the team quickly ran their benchmarks on candidate models. The Amazon API Gateway receives the PUT request (step 1).

Advertising 132

Advertising APIs Engineering Benchmark 132

AWS Machine Learning

MARCH 27, 2025

These include metrics such as ROUGE or cosine similarity for text similarity, and specific benchmarks for assessing toxicity (Detoxify), prompt stereotyping (cross-entropy loss), or factual knowledge (HELM, LAMA). Refer to Getting started with the API to set up your environment to make Amazon Bedrock requests through the AWS API.

Education 111

Education Engineering APIs Enterprise 111

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

CSM Magazine

DECEMBER 27, 2023

Automated API testing stands as a cornerstone in the modern software development cycle, ensuring that applications perform consistently and accurately across diverse systems and technologies. Continuous learning and adaptation are essential, as the landscape of API technology is ever-evolving.

APIs 52

APIs Benchmark Best practices Technology 52

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. The answer should only use the presented context.

Benchmark 119

Benchmark Enterprise Construction APIs 119

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. 4525) attained with the fine-tuned FLAN-T5 XL model presented in part 1 of this blog series.

Healthcare 136

Healthcare Engineering APIs Benchmark 136

AWS Machine Learning

JUNE 15, 2023

In this post, we present a solution that D2L.ai We demonstrate how to use the AWS Management Console and Amazon Translate public API to deliver automatic machine batch translation, and analyze the translations between two language pairs: English and Chinese, and English and Spanish.

APIs 103

APIs Benchmark Best practices Engineering 103

AWS Machine Learning

AUGUST 2, 2024

To overcome this limitation and provide dynamism and adaptability to knowledge base changes, we decided to follow a Retrieval Augmented Generation (RAG) approach, in which the LLMs are presented with relevant information extracted from external data sources to provide up-to-date data without the need to retrain the models.

APIs 127

APIs Analytics Chatbots Engineering 127

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

JUNE 13, 2023

In addition, deployments are now as simple as calling Boto3 SageMaker APIs and attaching the proper auto scaling policies. We already had an API layer on top of our models for model management and inference. Autocomplete The autocomplete models (sequence to sequence) presented a distinct set of requirements. 2xlarge instances.

APIs 95

APIs Benchmark Engineering Management 95

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 134

APIs Benchmark Enterprise Construction 134

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

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

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. Finally, we present a comparative analysis of latency improvements with LOR over the default routing strategy of random routing.

Engineering 121

Engineering Benchmark APIs Enterprise 121

AWS Machine Learning

DECEMBER 16, 2022

In this blog post, we’ll first present our latest performance improvements in the SageMaker model parallel library. Finally, we’ll benchmark performance of 13B, 50B, and 100B parameter auto-regressive models and wrap up with future work. Benchmarking performance. . — Emad Mostaque, Founder and CEO of Stability AI.

Benchmark 97

Benchmark Engineering APIs Scripts 97

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 tool is able to correlate multiple datasets and present a response.

Engineering 126

Engineering Construction Benchmark Advertising 126

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 130

APIs Technology Analytics Benchmark 130

AWS Machine Learning

APRIL 22, 2024

The typical ESG workflow consists of multiple phases, each presenting unique pain points. Consider the following guidelines: Implement real-time monitoring – Set up monitoring systems to track generative AI performance against sustainability benchmarks, focusing on efficiency and environmental impact.

Best practices 139

Best practices Benchmark Transportation Engineering 139

AWS Machine Learning

APRIL 27, 2023

Similar to the process of PyTorch integration with C++ code, Neuron CustomOps requires a C++ implementation of an operator via a NeuronCore-ported subset of the Torch C++ API. Finally, the custom library is built by calling the load API. It only defines the shape of the output tensor but not the actual values.

APIs 98

APIs Engineering Scripts Benchmark 98

AWS Machine Learning

JUNE 12, 2023

An extensible retrieval system enabling you to augment bot responses with information from a document repository, API, or other live-updating information source at inference time. The increasing scale and size of deep learning models present obstacles to successfully deploy these models in generative AI applications.

Chatbots 98

Chatbots APIs Engineering Enterprise 98

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

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. For example, you can look for specific keys in the document.

APIs 129

APIs Accountability Benchmark Government 129

AWS Machine Learning

JULY 26, 2023

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. We compile the UNet for one batch (by using input tensors with one batch), then use the torch_neuronx.DataParallel API to load this single batch model onto each core.

Scripts 98

Scripts APIs Benchmark Engineering 98

AWS Machine Learning

MAY 22, 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, Stability AI, and Amazon through a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI.

Scripts 136

Scripts Engineering Accountability Benchmark 136

AWS Machine Learning

AUGUST 26, 2024

Prospecting, opportunity progression, and customer engagement present exciting opportunities to utilize generative AI, using historical data, to drive efficiency and effectiveness. It focuses on precision, measuring how much of the generated content is present in the reference data. The following diagram illustrates this architecture.

Sales 128

Sales Accountability Feedback Metrics 128

AWS Machine Learning

DECEMBER 1, 2022

They show the usage of various SageMaker and JumpStart APIs. This notebook demonstrates how to deploy AlexaTM 20B through the JumpStart API and run inference. This notebook presents how to overcome this problem by using SageMaker and fair algorithms in the context of linear learners. This is called zero-shot in-context learning.

APIs 119

APIs Benchmark Advertising Banking 119

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

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).

Best practices 97

Best practices APIs Finance Metrics 97

AWS Machine Learning

JULY 24, 2023

as_trt_engine(output_fpath=trt_path, profiles=profiles) gpt2_trt = GPT2TRTDecoder(gpt2_engine, metadata, config, max_sequence_length=42, batch_size=10) Latency comparison: PyTorch vs. TensorRT JMeter is used for performance benchmarking in this project. implement the model and the inference API. model_fp16.onnx gpt2 and predictor.py

APIs 96

APIs Engineering Construction Benchmark 96

AWS Machine Learning

APRIL 8, 2024

In this post, we explore the latest features introduced in this release, examine performance benchmarks, and provide a detailed guide on deploying new LLMs with LMI DLCs at high performance. Before introducing this API, the KV cache was recomputed for any newly added requests. get('text') !=

Engineering 115

Engineering Calibration APIs Enterprise 115

AWS Machine Learning

OCTOBER 24, 2022

In this post, we present a new open-source library that takes a different stand on DL training: MosaicML Composer is a speed-centric library whose primary objective is to make neural network training scripts faster via algorithmic innovation. Speedup techniques implemented in Composer can be accessed with its functional API.

Scripts 98

Scripts Enterprise Benchmark APIs 98

RichCall

SEPTEMBER 13, 2017

Check out what recent reports and experts suggest, and take part in a contact center benchmarking survey to get more accurate data on the current contact center trends. Global Contact Centre Benchmarking Report, Dimension Data 2017. Dimension Data’s 2016 Global Contact Centre Benchmarking Report, © Dimension Data 2013-2016.

Contact Center 64

Contact Center Technology Benchmark Chatbots 64

AWS Machine Learning

NOVEMBER 22, 2023

Model choices – SageMaker JumpStart offers a selection of state-of-the-art ML models that consistently rank among the top in industry-recognized HELM benchmarks. However, off-the-shelf LLMs present limitations: Their offline training renders them unaware of up-to-date information. Lewis et al.

Engineering 125

Engineering Chatbots Benchmark APIs 125

AWS Machine Learning

JANUARY 19, 2024

Solution overview In this section, we present the overall workflow and explain the approach. We use the Recognizing Textual Entailment dataset from the GLUE benchmarking suite. Then the payload is passed to the SageMaker endpoint invoke API via the BotoClient to simulate real user requests. training.py ).

Metrics 131

Metrics Scripts Benchmark Enterprise 131

AWS Machine Learning

NOVEMBER 30, 2023

Customers have to leave their development environment to use academic tools and benchmarking sites, which require highly-specialized knowledge. We surveyed existing open-source evaluation frameworks and designed FMEval evaluation API with extensibility in mind. We use datasets such as BoolQ , NaturalQuestions , and TriviaQA.

Construction 113

Construction Metrics industry standards Benchmark 113

AWS Machine Learning

NOVEMBER 17, 2022

In this post, we provide an overview of how to deploy and run inference with the AlexaTM 20B model programmatically through JumpStart APIs, available in the SageMaker Python SDK. Note that we need to pass Predictor class when we deploy model through Model class, #for being able to run inference through the sagemaker API.

Scripts 101

Scripts APIs Government Engineering 101

Enghouse Interactive

OCTOBER 21, 2020

As noted in the 2019 Dimension Data Customer Experience (CX) Benchmarking report: 88% of contact center decision-makers expect self-service volumes to increase over the next 12 months. Agents will be presented with increasingly more complex situations which will require more engagement, insight and analysis.

Self service 79

Self service Contact Center Benchmark Chatbots 79