AWS Machine Learning Blog

APRIL 19, 2024

We used AWS services including Amazon Bedrock , Amazon SageMaker , and Amazon OpenSearch Serverless in this solution. In this series, we use the slide deck Train and deploy Stable Diffusion using AWS Trainium & AWS Inferentia from the AWS Summit in Toronto, June 2023 to demonstrate the solution.

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

The following figure illustrates the idea of a large cluster of GPUs being used for learning, followed by a smaller number for inference. Examples of other PBAs now available include AWS Inferentia and AWS Trainium , Google TPU, and Graphcore IPU. Suppliers of data center GPUs include NVIDIA, AMD, Intel, and others.

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AWS Machine Learning Blog

FEBRUARY 24, 2023

AWS recently released Amazon SageMaker geospatial capabilities to provide you with satellite imagery and geospatial state-of-the-art machine learning (ML) models, reducing barriers for these types of use cases. To train this model, we need a labeled ground truth subset of the Low Altitude Disaster Imagery (LADI) dataset.

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AWS Machine Learning Blog

MAY 15, 2023

We outline how we built an automated demand forecasting pipeline using Forecast and orchestrated by AWS Step Functions to predict daily demand for SKUs. Conclusion In this post, we walked through an automated demand forecasting pipeline we built using Amazon Forecast and AWS Step Functions.

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AWS Machine Learning Blog

SEPTEMBER 19, 2023

Prerequisites To follow this tutorial, you need the following: An AWS account. AWS Identity and Access Management (IAM) permissions. 2019| Used| 32675 |40990.00| NA| 1686627154| | 5| Acura TLX A-Spec| 2023| New| NA|50195.00|50195| Prior to joining AWS, Ninad worked as a software developer for 12+ years.

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ODSC - Open Data Science

FEBRUARY 17, 2023

TensorFlow is desired for its flexibility for ML and neural networks, PyTorch for its ease of use and innate design for NLP, and scikit-learn for classification and clustering. BERT is still very popular over the past few years and even though the last update from Google was in late 2019 it is still widely deployed.

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AWS Machine Learning Blog

APRIL 19, 2023

Then we needed to Dockerize the application, write a deployment YAML file, deploy the gRPC server to our Kubernetes cluster, and make sure it’s reliable and auto scalable. The DJL was created at Amazon and open-sourced in 2019. The DJL continues to grow in its ability to support different hardware, models, and engines.

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AWS Machine Learning Blog

FEBRUARY 10, 2023

As an example, in the following figure, we separate Cover 3 Zone (green cluster on the left) and Cover 1 Man (blue cluster in the middle). We design an algorithm that automatically identifies the ambiguity between these two classes as the overlapping region of the clusters. The Illustrated Transformer.” Selvaraju, Ramprasaath R.,

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phData

NOVEMBER 8, 2024

Partitioning and clustering features inherent to OTFs allow data to be stored in a manner that enhances query performance. 2019 - Delta Lake Databricks released Delta Lake as an open-source project. This is invaluable in big data environments, where unnecessary scans can significantly drain resources.

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AWS Machine Learning Blog

APRIL 29, 2024

For AWS and Outerbounds customers, the goal is to build a differentiated machine learning and artificial intelligence (ML/AI) system and reliably improve it over time. First, the AWS Trainium accelerator provides a high-performance, cost-effective, and readily available solution for training and fine-tuning large models.

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AWS Machine Learning Blog

APRIL 11, 2023

It’s a fully managed on-demand service, integrated with SageMaker and other AWS services, and therefore creates and manages resources for you. The basic_infra.yaml file provides example AWS CloudFormation code to provision the necessary prerequisite infrastructure. Maren has been with AWS since November 2019.

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AWS Machine Learning Blog

NOVEMBER 30, 2023

The number of companies launching generative AI applications on AWS is substantial and building quickly, including adidas, Booking.com, Bridgewater Associates, Clariant, Cox Automotive, GoDaddy, and LexisNexis Legal & Professional, to name just a few. Innovative startups like Perplexity AI are going all in on AWS for generative AI.

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Flipboard

APRIL 13, 2023

At AWS, we have played a key role in democratizing ML and making it accessible to anyone who wants to use it, including more than 100,000 customers of all sizes and industries. AWS has the broadest and deepest portfolio of AI and ML services at all three layers of the stack. Today’s FMs, such as the large language models (LLMs) GPT3.5

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Mlearning.ai

APRIL 16, 2023

AWS Bedrock is a new service that empowers companies to harness the power of machine learning models called Foundation Models (FMs) to create Generative AI applications. AWS Bedrock’s serverless experience makes it easy to customize foundation models (FMs) with proprietary data.

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AWS Machine Learning Blog

OCTOBER 11, 2024

Amazon Bedrock Knowledge Bases provides industry-leading embeddings models to enable use cases such as semantic search, RAG, classification, and clustering, to name a few, and provides multilingual support as well. You can set up the notebook in any AWS Region where Amazon Bedrock Knowledge Bases is available.

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Data Science Dojo

DECEMBER 31, 2023

Following earlier collaborations in 2019 and 2021, this agreement focused on boosting AI supercomputing capabilities and research. Google Cloud was cemented as Anthropic’s preferred provider for computational resources, and they committed to building large-scale TPU and GPU clusters for Anthropic. Read more here 3.

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