AWS Machine Learning

APRIL 29, 2024

In recent years, large language models (LLMs) have gained attention for their effectiveness, leading various industries to adapt general LLMs to their data for improved results, making efficient training and hardware availability crucial. In this post, we show you how efficient we make our continual pre-training by using Trainium chips.

APIs 114

APIs Healthcare Scripts Enterprise 114

AWS Machine Learning

APRIL 29, 2024

This often means the method of using a third-party LLM API won’t do for security, control, and scale reasons. First, the AWS Trainium accelerator provides a high-performance, cost-effective, and readily available solution for training and fine-tuning large models. The following figure illustrates this workflow.

APIs 112

APIs Engineering Scripts Management 112

CCNG

JUNE 7, 2023

Language Support : Chat GPT can be trained in multiple languages, enabling contact centers to provide support to customers globally without the need for multilingual agents. In the end, writing scripts, using it for marketing or content and other simple tasks appear to be the main use cases right now.” says Fred.

Contact Center 195

Contact Center CCNG APIs Scripts 195

AWS Machine Learning

MAY 31, 2024

In this blog post and open source project , we show you how you can pre-train a genomics language model, HyenaDNA , using your genomic data in the AWS Cloud. Amazon SageMaker Amazon SageMaker is a fully managed ML service offered by AWS, designed to reduce the time and cost associated with training and tuning ML models at scale.

Biotechnology 94

Biotechnology Scripts Healthcare APIs 94

AWS Machine Learning

FEBRUARY 15, 2023

Amazon SageMaker JumpStart is the machine learning (ML) hub of SageMaker that offers over 350 built-in algorithms, pre-trained models, and pre-built solution templates to help you get started with ML fast. Perform the training step to fine-tune the pre-trained model using transfer learning. Create the model. Register the model.

Scripts 96

Scripts APIs Engineering Enterprise 96

AWS Machine Learning

FEBRUARY 12, 2025

Many use cases involve using pre-trained large language models (LLMs) through approaches like Retrieval Augmented Generation (RAG). Fine-tuning is a supervised training process where labeled prompt and response pairs are used to further train a pre-trained model to improve its performance for a particular use case.

APIs 73

APIs Management Benchmark Scripts 73

AWS Machine Learning

SEPTEMBER 26, 2024

This text-to-video API generates high-quality, realistic videos quickly from text and images. Trained on the Amazon SageMaker HyperPod , Dream Machine excels in creating consistent characters, smooth motion, and dynamic camera movements. Luma AI’s recently launched Dream Machine represents a significant advancement in this field.

Scripts 106

Scripts APIs Metrics Management 106

AWS Machine Learning

APRIL 19, 2024

In this post, we focus on how we used Karpenter on Amazon Elastic Kubernetes Service (Amazon EKS) to scale AI training and inference, which are core elements of the Iambic discovery platform. We wanted to build a scalable system to support AI training and inference. The service is exposed behind a reverse-proxy using Traefik.

Metrics 113

Metrics APIs Scripts Construction 113

AWS Machine Learning

DECEMBER 22, 2023

Large language model (LLM) training has surged in popularity over the last year with the release of several popular models such as Llama 2, Falcon, and Mistral. Training performant models at this scale can be a challenge. These features improve the usability of the library, expand functionality, and accelerate training.

Scripts 111

Scripts APIs Engineering Finance 111

AWS Machine Learning

JULY 29, 2022

Pre-trained models and fully managed NLP services have democratised access and adoption of NLP. Amazon SageMaker is a fully managed service that provides developers and data scientists the ability to build, train, and deploy machine learning (ML) models quickly. Build your training script for the Hugging Face SageMaker estimator.

Scripts 89

Scripts APIs Big data Engineering 89

AWS Machine Learning

MARCH 15, 2023

The best practice for migration is to refactor these legacy codes using the Amazon SageMaker API or the SageMaker Python SDK. SageMaker runs the legacy script inside a processing container. Step Functions is a serverless workflow service that can control SageMaker APIs directly through the use of the Amazon States Language.

Scripts 130

Scripts APIs Engineering Construction 130

AWS Machine Learning

AUGUST 19, 2022

Today, a lot of customers are using TensorFlow to train deep learning models for their clickthrough rate in advertising and personalization recommendations in ecommerce. Model iteration is one of a data scientist’s daily jobs, but they face the problem of taking too long to train on large datasets. Automatic mixed precision training.

Best practices 78

Best practices APIs Scripts Advertising 78

Zingtree

MAY 3, 2018

If you’re a Zendesk user in a Contact Center environment, you’ll want to be using our Zendesk Agent Scripting app. This makes it easy to guide, train and onboard agents and is a huge productivity booster for everyone. This two-minute video shows you how Agents interact with the Agent Scripting App: Getting Started.

Scripts 67

Scripts APIs Feedback Contact Center 67

AWS Machine Learning

FEBRUARY 16, 2023

Modern model pre-training often calls for larger cluster deployment to reduce time and cost. At the server level, such training workloads demand faster compute and increased memory allocation. As models grow to hundreds of billions of parameters, they require a distributed training mechanism that spans multiple nodes (instances).

Scripts 90

Scripts Benchmark APIs Engineering 90

AWS Machine Learning

AUGUST 18, 2022

Amazon SageMaker is a fully-managed service for ML, and SageMaker model training is an optimized compute environment for high-performance training at scale. SageMaker model training offers a remote training experience with a seamless control plane to easily train and reproduce ML models at high performance and low cost.

Scripts 85

Scripts APIs Benchmark Engineering 85

AWS Machine Learning

SEPTEMBER 2, 2022

Distributed deep learning model training is becoming increasingly important as data sizes are growing in many industries. Many applications in computer vision and natural language processing now require training of deep learning models, which are growing exponentially in complexity and are often trained with hundreds of terabytes of data.

Scripts 84

Scripts Metrics Accountability APIs 84

Zingtree

MAY 24, 2018

If you’re a Zendesk user in a Contact Center environment, you’ll want to be using our Zendesk Agent Scripting app. This makes it easy to guide, train and onboard agents and is a huge productivity booster for everyone. Benefits of the Zendesk Agent Scripting App. Installing the Agent Scripting App into Zendesk.

Scripts 61

Scripts APIs Real estate Feedback 61

AWS Machine Learning

AUGUST 1, 2024

Amazon Bedrock 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, Mistral AI, Stability AI, and Amazon through a single API. The scripts for fine-tuning and evaluation are available on the GitHub repository.

APIs 111

APIs Scripts Real estate Accountability 111

AWS Machine Learning

AUGUST 2, 2024

Traditionally, earnings call scripts have followed similar templates, making it a repeatable task to generate them from scratch each time. On the other hand, generative artificial intelligence (AI) models can learn these templates and produce coherent scripts when fed with quarterly financial data.

Engineering 117

Engineering Scripts Metrics APIs 117

AWS Machine Learning

JUNE 9, 2022

SageMaker JumpStart provides one-click fine-tuning and deployment of a wide variety of pre-trained models across popular ML tasks, as well as a selection of end-to-end solutions that solve common business problems. In this post, we’re excited to announce that all trainable JumpStart models now support incremental training.

Scripts 71

Scripts APIs Enterprise Accountability 71

AWS Machine Learning

MAY 16, 2024

The main AWS services used are SageMaker, Amazon EMR , AWS CodeBuild , Amazon Simple Storage Service (Amazon S3), Amazon EventBridge , AWS Lambda , and Amazon API Gateway. The SageMaker pipeline predefined in CodeBuild runs, and sequentially runs steps such as preprocessing including provisioning, model training, and model registration.

Personalization 107

Personalization APIs Scripts Technical Support 107

AWS Machine Learning

AUGUST 3, 2023

As machine learning (ML) becomes increasingly prevalent in a wide range of industries, organizations are finding the need to train and serve large numbers of ML models to meet the diverse needs of their customers. Training and serving thousands of models requires a robust and scalable infrastructure, which is where Amazon SageMaker can help.

APIs 83

APIs Scripts SaaS Management 83

AWS Machine Learning

MARCH 6, 2023

Large language models (LLMs) are neural network-based language models with hundreds of millions ( BERT ) to over a trillion parameters ( MiCS ), and whose size makes single-GPU training impractical. The size of an LLM and its training data is a double-edged sword: it brings modeling quality, but entails infrastructure challenges.

Best practices 87

Best practices APIs Transportation Scripts 87

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 95

APIs Scripts Benchmark Metrics 95

AWS Machine Learning

OCTOBER 24, 2022

The plentiful and jointly trained parameters of DL models have a large representational capacity that brought improvements in numerous customer use cases, including image and speech analysis, natural language processing (NLP), time series processing, and more. The challenge with DL training.

Scripts 83

Scripts Enterprise Benchmark APIs 83

AWS Machine Learning

JANUARY 5, 2024

The AWS portfolio of ML services includes a robust set of services that you can use to accelerate the development, training, and deployment of machine learning applications. Collaboration – Data scientists each worked on their own local Jupyter notebooks to create and train ML models.

Management 123

Management APIs Engineering Government 123

AWS Machine Learning

OCTOBER 31, 2022

Training these gigantic models is challenging and requires complex distribution strategies. Data scientists and machine learning engineers are constantly looking for the best way to optimize their training compute, yet are struggling with the communication overhead that can increase along with the overall cluster size. on 256 GPUs.

Scripts 69

Scripts Benchmark APIs Engineering 69

AWS Machine Learning

OCTOBER 27, 2022

Certain machine learning (ML) workloads, such as training computer vision models or reinforcement learning, often involve combining the GPU- or accelerator-intensive task of neural network model training with the CPU-intensive task of data preprocessing, like image augmentation. This post is co-written with Chaim Rand from Mobileye.

Scripts 74

Scripts Benchmark Metrics Transportation 74

AWS Machine Learning

JANUARY 8, 2024

The first allows you to run a Python script from any server or instance including a Jupyter notebook; this is the quickest way to get started. In the following sections, we first describe the script solution, followed by the AWS CDK construct solution. The following diagram illustrates the sequence of events within the script.

Scripts 99

Scripts Construction APIs Healthcare 99

AWS Machine Learning

FEBRUARY 13, 2023

With the increasing use of artificial intelligence (AI) and machine learning (ML) for a vast majority of industries (ranging from healthcare to insurance, from manufacturing to marketing), the primary focus shifts to efficiency when building and training models at scale. The steps are as follows: Open AWS Cloud9 on the console.

Scripts 79

Scripts Best practices Transportation Construction 79

AWS Machine Learning

MARCH 23, 2023

Although this example shows how to perform this for inference operations, you can extend the solution to training and other ML steps. Endpoints are deployed with a couple clicks or lines of code using SageMaker, which simplifies the process for developers and ML experts to build and train ML and deep learning models in the cloud.

Scripts 107

Scripts APIs Government Analytics 107

AWS Machine Learning

SEPTEMBER 8, 2023

Amazon Rekognition makes it easy to add image analysis capability to your applications without any machine learning (ML) expertise and comes with various APIs to fulfil use cases such as object detection, content moderation, face detection and analysis, and text and celebrity recognition, which we use in this example.

APIs 109

APIs Scripts Entertainment Personalization 109

Zingtree

APRIL 14, 2015

We’re proud to announce that we’ve “officially” launched our Agent Scripting for call centers. Zingtree Interactive Decision Tree System Redefines Call Center Agent Scripting with New App. New agent scripting tools aid in training and corporate compliance for call center applications.

Scripts 48

Scripts Call Center APIs Analytics 48

AWS Machine Learning

JULY 29, 2022

The data scientists in this team use Amazon SageMaker to build and train a credit risk prediction model using the shared credit risk data product from the consumer banking LoB. Build and train ML models using a data mesh architecture on AWS. Part 1: Data mesh set up and data product registration. Data exploration.

Scripts 77

Scripts Analytics Accountability Engineering 77

AWS Machine Learning

SEPTEMBER 12, 2023

In this post, we demonstrate the technical benefits of using Hugging Face transformers deployed with Amazon SageMaker , such as training and experimentation at scale, and increased productivity and cost-efficiency. This merge event now triggers a SageMaker Pipelines job using production data for training purposes.

Management 109

Management APIs CRM Metrics 109

AWS Machine Learning

JUNE 29, 2022

However, training these gigantic networks from scratch requires a tremendous amount of data and compute. For smaller NLP datasets, a simple yet effective strategy is to use a pre-trained transformer, usually trained in an unsupervised fashion on very large datasets, and fine-tune it on the dataset of interest. training script.

Benchmark 83

Benchmark Metrics APIs Scripts 83

AWS Machine Learning

MARCH 19, 2024

Generative AI using large pre-trained foundation models (FMs) such as Claude can rapidly generate a variety of content from conversational text to computer code based on simple text prompts, known as zero-shot prompting. The user can use the Amazon Recognition DetectText API to extract text data from these images. setup.sh. (a

Construction 127

Construction Scripts APIs Enterprise 127