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

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 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

NOVEMBER 26, 2024

Figure 1 presents the confusion matrix of the model’s responses. The analysts investigating the incident are presented with a series of events that occurred on the endpoint at the time the suspicious activity was detected. We used the InvokeModel API to interact with the model with minimal latency.

APIs 101

APIs Metrics SaaS Engineering 101

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

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 138

Best practices Benchmark Transportation Engineering 138

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

Engineering 124

Engineering Construction APIs Benchmark 124

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

AWS Machine Learning

JANUARY 14, 2025

We also go deeper into our evaluation methodology and present insights from our studies. We refer to this approach as assertion-based benchmarking. Upon analysis, we found that when presented with many tools, a single agent tended to hallucinate tool calls and failed to reject some out-of-scope requests.

Finance 116

Finance Benchmark Construction Enterprise 116

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

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

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

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 127

APIs Accountability Benchmark Government 127

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 134

Scripts Engineering Accountability APIs 134

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 113

Engineering Calibration APIs Enterprise 113

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 126

Sales Accountability Feedback Metrics 126

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 117

APIs Benchmark Advertising Banking 117

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 136

Metrics Engineering Accountability Benchmark 136

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

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 96

Best practices APIs Finance Engineering 96

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 APIs Benchmark 98

AWS Machine Learning

NOVEMBER 15, 2024

An alternative approach to routing is to use the native tool use capability (also known as function calling) available within the Bedrock Converse API. In this scenario, each category or data source would be defined as a ‘tool’ within the API, enabling the model to select and use these tools as needed.

APIs 116

APIs Engineering Chatbots Construction 116

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 123

Engineering Chatbots APIs Benchmark 123

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 129

Metrics Scripts Benchmark Enterprise 129

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 78

Self service Contact Center Benchmark Chatbots 78

Amity

JUNE 12, 2017

Every CS team measures it and every Customer Success Management (CSM) platform solution presents it at the top of their dashboard. This is especially true, and much more actionable, if you can create benchmarks for each segment and the data can identify trends over time. Your CHS is Insufficient to Define Your Playbooks!

APIs 54

APIs Automotive Enterprise Benchmark 54

AWS Machine Learning

SEPTEMBER 20, 2022

As is explained in the post Amazon SageMaker JumpStart models and algorithms now available via API , the following artifacts are required to train a pre-built algorithm via the SageMaker SDK: Its framework-specific container image, containing all the required dependencies for training and inference. Benchmarking the trained models.

Scripts 97

Scripts Metrics Telecommunications APIs 97

Hodusoft

NOVEMBER 27, 2020

They can optimize and monitor the performance of their team with real-time customizable API based wallboards and dashboards. Employee Workflow Effectiveness: Every agent has a different set of skills and Real-time call monitoring presents a true picture of how an agent is performing and contributing to the success of the company.

Contact Center 52

Contact Center Analytics Contact center software APIs 52

Netomi

FEBRUARY 10, 2023

Semi-open Typically, these models can be used for training and inference through APIs. They are also benchmarked against the latest state-of-the-art models, such as DialoGPT, Godel, DeBERTa from Microsoft, RoBERTa from Facebook, and BERT from Google. Examples include the GPT-3.5

Chatbots 59

Chatbots APIs Benchmark Technology 59

AWS Machine Learning

MAY 31, 2023

In this post, we present a comprehensive guide of deploying a multiple-choice quiz solution for the FAQ pages of any AWS service, based on the AI21 Jurassic-2 Jumbo Instruct foundation model on Amazon SageMaker Jumpstart. Actually, you can develop such a system using state-of-the-art language models and a few lines of Python.

Scripts 98

Scripts Engineering Accountability APIs 98

AWS Machine Learning

JUNE 29, 2022

This necessitates the requirement for a fully managed service that can be integrated into applications using API calls without the need for extensive machine learning (ML) expertise. In this post, we presented two text classification approaches for online conversations using AWS ML services. Set up the AWS CLI and AWS SDKs. Conclusion.

Metrics 100

Metrics Telecommunications APIs Benchmark 100

AWS Machine Learning

DECEMBER 13, 2024

Crystal shares CWICs core functionalities but benefits from broader data sources and API access. RAG benchmark Compare the fine-tuned models performance against a RAG system using a pre-trained model. Crystal Clearwaters advanced AI assistant with expanded capabilities that empower internal teams operations.

Analytics 93

Analytics Management Accountability Engineering 93

JustCall

FEBRUARY 13, 2023

Provides additional features like calendar management and benchmarking. month for up to 40k emails WhatsApp Business API – Starting at $0.0042 per WhatsApp Template message and $0.005 for session messages SMS, WhatsApp, Chat, and MMS – Starting at $0.05 5 Capterra– 4.1/5 5 TrustRadius– 7.7/10 10 Trustpilot– 3.3/5

Interactive Voice Response 52

Interactive Voice Response voip Enterprise call center software 52

JustCall

JANUARY 31, 2023

per user per month Premium – Message, video, and phone features and an open API at $33.74 per user per month Ultimate – Message, video, and phone features and an open API at $44.99 per user per month Standard – Message, video, and phone features at $28.49 per user, per month Professional – $21.95

voip 52

voip Enterprise Interactive Voice Response CRM 52