# Amazon SageMaker AI

Published articles for Amazon SageMaker AI.

This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles.

## Build an AI-powered product tagging system with Amazon SageMaker serverless model customization

DevFeed: [Build an AI-powered product tagging system with Amazon SageMaker serverless model customization](<https://devfeed.tech/articles/build-an-ai-powered-product-tagging-system-with-amazon-sagemaker-serverless-model-customization-26940.md>)

Original publisher: [Read original article](<https://aws.amazon.com/blogs/machine-learning/build-an-ai-powered-product-tagging-system-with-amazon-sagemaker-serverless-model-customization/>)

Author: Linpo Guo

Published: 2026-09-15T16:11:36Z

Content type: tutorial

Language: en

Sources: [Artificial Intelligence](<https://devfeed.tech/sources/artificial-intelligence.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Amazon SageMaker AI](<https://devfeed.tech/topics/amazon-sagemaker-ai.md>), [Fine-tuning](<https://devfeed.tech/topics/fine-tuning.md>), [rlvr](<https://devfeed.tech/topics/rlvr.md>), [grpo](<https://devfeed.tech/topics/grpo.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [model-deployment](<https://devfeed.tech/topics/model-deployment.md>), [Reinforcement learning](<https://devfeed.tech/topics/reinforcement-learning.md>), [SDK](<https://devfeed.tech/topics/sdk.md>), [Serverless](<https://devfeed.tech/topics/serverless.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [amazon-sagemaker](<https://devfeed.tech/tags/amazon-sagemaker.md>), [amazon-sagemaker-ai](<https://devfeed.tech/tags/amazon-sagemaker-ai.md>), [aws](<https://devfeed.tech/tags/aws.md>), [compute](<https://devfeed.tech/tags/compute.md>), [cost](<https://devfeed.tech/tags/cost.md>), [customization](<https://devfeed.tech/tags/customization.md>), [expert-400](<https://devfeed.tech/tags/expert-400.md>), [fine-tuning](<https://devfeed.tech/tags/fine-tuning.md>), [inference](<https://devfeed.tech/tags/inference.md>), [jobs](<https://devfeed.tech/tags/jobs.md>), [reinforcement-learning](<https://devfeed.tech/tags/reinforcement-learning.md>), [rlvr](<https://devfeed.tech/tags/rlvr.md>), [sdk](<https://devfeed.tech/tags/sdk.md>), [technical-how-to](<https://devfeed.tech/tags/technical-how-to.md>)

### AI overview

This walkthrough shows how to build a product tagging system by customizing Qwen3-8B with supervised fine-tuning and reinforcement learning with verifiable rewards on Amazon SageMaker serverless model customization. It then deploys the optimized model for asynchronous inference to enrich retail catalogs.

### Source excerpt

Manually tagging thousands of catalog products is slow and inconsistent. This walkthrough shows how to customize Qwen3-8B with supervised fine-tuning (SFT) and reinforcement learning with verifiable rewards (RLVR) on Amazon SageMaker serverless model customization, then deploy it for asynchronous inference to build a cost-efficient product tagging system.

## Announcing instance preference lists for Amazon SageMaker AI training jobs

DevFeed: [Announcing instance preference lists for Amazon SageMaker AI training jobs](<https://devfeed.tech/articles/announcing-instance-preference-lists-for-amazon-sagemaker-ai-training-jobs-26939.md>)

Original publisher: [Read original article](<https://aws.amazon.com/blogs/machine-learning/announcing-instance-preference-lists-for-amazon-sagemaker-ai-training-jobs/>)

Author: Kanwaljit Khurmi

Published: 2026-09-15T16:01:47Z

Content type: release

Language: en

Sources: [Artificial Intelligence](<https://devfeed.tech/sources/artificial-intelligence.md>)

Topics: [Amazon SageMaker AI](<https://devfeed.tech/topics/amazon-sagemaker-ai.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [Model Development](<https://devfeed.tech/topics/model-development.md>), [data-processing](<https://devfeed.tech/topics/data-processing.md>)

Tags: [amazon-sagemaker-ai](<https://devfeed.tech/tags/amazon-sagemaker-ai.md>), [announcements](<https://devfeed.tech/tags/announcements.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [intermediate-200](<https://devfeed.tech/tags/intermediate-200.md>), [model-development](<https://devfeed.tech/tags/model-development.md>), [pipelines](<https://devfeed.tech/tags/pipelines.md>), [scheduled](<https://devfeed.tech/tags/scheduled.md>), [training](<https://devfeed.tech/tags/training.md>)

### AI overview

Amazon SageMaker AI introduces instance preference lists for training and processing jobs. Users can specify up to five instance types in priority order, and SageMaker AI launches the job on the first option with available capacity, reducing manual retries and capacity monitoring.

### Source excerpt

Amazon SageMaker AI now offers instance preference lists for training and processing jobs. Specify an ordered list of up to five instance types, and SageMaker AI automatically launches on the first type with available capacity, eliminating manual retry loops and capacity-watching scripts.

## Reduce LLM latency with prefix-aware routing on Amazon SageMaker Inference

DevFeed: [Reduce LLM latency with prefix-aware routing on Amazon SageMaker Inference](<https://devfeed.tech/articles/reduce-llm-latency-with-prefix-aware-routing-on-amazon-sagemaker-inference-4740.md>)

Original publisher: [Read original article](<https://aws.amazon.com/blogs/machine-learning/reduce-llm-latency-with-prefix-aware-routing-on-amazon-sagemaker-inference/>)

Author: Kareem Syed-Mohammed

Published: 2026-09-10T21:58:09Z

Content type: release

Language: en

Sources: [Artificial Intelligence](<https://devfeed.tech/sources/artificial-intelligence.md>)

Topics: [Large Language Model](<https://devfeed.tech/topics/llm.md>), [Low-Latency Inference](<https://devfeed.tech/topics/low-latency-inference.md>), [Caching](<https://devfeed.tech/topics/caching.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [Inference Performance](<https://devfeed.tech/topics/inference-performance.md>)

Tags: [advanced-300](<https://devfeed.tech/tags/advanced-300.md>), [amazon-sagemaker](<https://devfeed.tech/tags/amazon-sagemaker.md>), [amazon-sagemaker-ai](<https://devfeed.tech/tags/amazon-sagemaker-ai.md>), [announcements](<https://devfeed.tech/tags/announcements.md>), [benchmarks](<https://devfeed.tech/tags/benchmarks.md>), [caching](<https://devfeed.tech/tags/caching.md>), [inference](<https://devfeed.tech/tags/inference.md>), [latency](<https://devfeed.tech/tags/latency.md>), [llama](<https://devfeed.tech/tags/llama.md>), [llm](<https://devfeed.tech/tags/llm.md>), [routing](<https://devfeed.tech/tags/routing.md>), [tensorrt-llm](<https://devfeed.tech/tags/tensorrt-llm.md>), [vllm](<https://devfeed.tech/tags/vllm.md>)

### AI overview

Amazon SageMaker Inference introduces prefix-aware routing for LLM requests. By consistently sending requests with matching prompt prefixes to the same instance, it improves reuse of cached KV computations and can reduce time to first token.

### Source excerpt

Amazon SageMaker Inference now offers prefix-aware routing, a routing strategy that sends requests sharing the same prompt prefix to the same instance so the KV cache stays warm. In benchmarks on Llama 3.1 70B, it reduced P50 time-to-first-token by up to 77% and raised KV cache hit rates from about 25% to over 80%.

## Amazon SageMaker Feature Store introduces UpdateRecord for feature-level writes

DevFeed: [Amazon SageMaker Feature Store introduces UpdateRecord for feature-level writes](<https://devfeed.tech/articles/amazon-sagemaker-feature-store-introduces-updaterecord-for-feature-level-writes-4726.md>)

Original publisher: [Read original article](<https://aws.amazon.com/blogs/machine-learning/amazon-sagemaker-feature-store-introduces-updaterecord-for-feature-level-writes/>)

Author: Mona Mona

Published: 2026-09-08T18:29:15Z

Content type: release

Language: en

Sources: [Artificial Intelligence](<https://devfeed.tech/sources/artificial-intelligence.md>)

Topics: [AI, ML & Data Engineering](<https://devfeed.tech/topics/ai-ml-data-engineering.md>), [Training AI Models](<https://devfeed.tech/topics/training-ai-models.md>), [AWS IAM](<https://devfeed.tech/topics/aws-iam.md>)

Tags: [amazon-dynamodb](<https://devfeed.tech/tags/amazon-dynamodb.md>), [amazon-elasticache](<https://devfeed.tech/tags/amazon-elasticache.md>), [amazon-machine-learning](<https://devfeed.tech/tags/amazon-machine-learning.md>), [amazon-sagemaker](<https://devfeed.tech/tags/amazon-sagemaker.md>), [amazon-sagemaker-ai](<https://devfeed.tech/tags/amazon-sagemaker-ai.md>), [announcements](<https://devfeed.tech/tags/announcements.md>), [api](<https://devfeed.tech/tags/api.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [aws-identity-and-access-management-iam](<https://devfeed.tech/tags/aws-identity-and-access-management-iam.md>), [intermediate-200](<https://devfeed.tech/tags/intermediate-200.md>), [technical-how-to](<https://devfeed.tech/tags/technical-how-to.md>)

### AI overview

Amazon SageMaker Feature Store adds the UpdateRecord API for atomic feature-level updates without reading or rewriting an entire record.

### Source excerpt

Amazon SageMaker Feature Store now supports feature-level writes. With the new UpdateRecord API, you can update one or more feature values in a single call without reading or rewriting the entire record. It is available for both the Standard (Amazon DynamoDB) and In-Memory (Amazon ElastiCache) online store tiers.

## Govern models with MLflow and Amazon SageMaker AI Model Registry sync: Part 2

DevFeed: [Govern models with MLflow and Amazon SageMaker AI Model Registry sync: Part 2](<https://devfeed.tech/articles/govern-models-with-mlflow-and-amazon-sagemaker-ai-model-registry-sync-part-2-4732.md>)

Original publisher: [Read original article](<https://aws.amazon.com/blogs/machine-learning/govern-models-with-mlflow-and-amazon-sagemaker-ai-model-registry-sync-part-2/>)

Author: Melanie Li

Published: 2026-09-08T17:03:50Z

Content type: article

Language: en

Sources: [Artificial Intelligence](<https://devfeed.tech/sources/artificial-intelligence.md>)

Topics: [Amazon SageMaker AI](<https://devfeed.tech/topics/amazon-sagemaker-ai.md>), [AWS IAM](<https://devfeed.tech/topics/aws-iam.md>), [CI/CD](<https://devfeed.tech/topics/cicd.md>), [Command-line interface](<https://devfeed.tech/topics/cli.md>)

Tags: [amazon-sagemaker-ai](<https://devfeed.tech/tags/amazon-sagemaker-ai.md>), [announcements](<https://devfeed.tech/tags/announcements.md>), [aws](<https://devfeed.tech/tags/aws.md>), [aws-identity-and-access-management-iam](<https://devfeed.tech/tags/aws-identity-and-access-management-iam.md>), [ci-cd](<https://devfeed.tech/tags/ci-cd.md>), [intermediate-200](<https://devfeed.tech/tags/intermediate-200.md>), [model](<https://devfeed.tech/tags/model.md>), [sync](<https://devfeed.tech/tags/sync.md>)

### AI overview

This article describes cross-account model-governance patterns for managed MLflow and Amazon SageMaker AI Model Registry sync. It covers hub-and-spoke and hybrid topologies, IAM-based roles, and CI/CD deployment of approved models.

### Source excerpt

Governing models across accounts is the next step after automatic model registration. This post extends managed MLflow and Amazon SageMaker AI Model Registry sync to two cross-account governance topologies: a hub-and-spoke pattern that centralizes governance with AWS RAM, and a hybrid pattern that keeps development accounts isolated.

## AWS Weekly Roundup: Welcome DuckLabs to the team, Agentic Resource Discovery (ARD), and more (August 31, 2026)

DevFeed: [AWS Weekly Roundup: Welcome DuckLabs to the team, Agentic Resource Discovery (ARD), and more (August 31, 2026)](<https://devfeed.tech/articles/aws-weekly-roundup-welcome-ducklabs-to-the-team-agentic-resource-discovery-ard-and-more-august-31-2026-4618.md>)

Original publisher: [Read original article](<https://aws.amazon.com/blogs/aws/aws-weekly-roundup-welcome-ducklabs-to-the-team-agentic-resource-discovery-ard-and-more-august-31-2026/>)

Author: Daniel Abib

Published: 2026-08-31T14:45:25Z

Content type: news

Language: en

Sources: [AWS News Blog](<https://devfeed.tech/sources/aws-news-blog.md>)

Topics: [data](<https://devfeed.tech/topics/data.md>), [Amazon S3](<https://devfeed.tech/topics/amazon-s3.md>), [Amazon Redshift](<https://devfeed.tech/topics/amazon-redshift.md>), [Node.js](<https://devfeed.tech/topics/node-js.md>)

Tags: [acquisition](<https://devfeed.tech/tags/acquisition.md>), [amazon-ec2](<https://devfeed.tech/tags/amazon-ec2.md>), [amazon-elastic-container-service](<https://devfeed.tech/tags/amazon-elastic-container-service.md>), [amazon-gamelift](<https://devfeed.tech/tags/amazon-gamelift.md>), [amazon-redshift](<https://devfeed.tech/tags/amazon-redshift.md>), [amazon-s3](<https://devfeed.tech/tags/amazon-s3.md>), [amazon-sagemaker](<https://devfeed.tech/tags/amazon-sagemaker.md>), [amazon-sagemaker-ai](<https://devfeed.tech/tags/amazon-sagemaker-ai.md>), [analytics](<https://devfeed.tech/tags/analytics.md>), [announcements](<https://devfeed.tech/tags/announcements.md>), [aws](<https://devfeed.tech/tags/aws.md>), [aws-fargate](<https://devfeed.tech/tags/aws-fargate.md>), [aws-glue](<https://devfeed.tech/tags/aws-glue.md>), [aws-iot-core](<https://devfeed.tech/tags/aws-iot-core.md>), [aws-lambda](<https://devfeed.tech/tags/aws-lambda.md>), [database](<https://devfeed.tech/tags/database.md>), [duckdb](<https://devfeed.tech/tags/duckdb.md>), [json](<https://devfeed.tech/tags/json.md>), [news](<https://devfeed.tech/tags/news.md>), [node-js](<https://devfeed.tech/tags/node-js.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [parquet](<https://devfeed.tech/tags/parquet.md>), [python](<https://devfeed.tech/tags/python.md>), [sql](<https://devfeed.tech/tags/sql.md>), [week-in-review](<https://devfeed.tech/tags/week-in-review.md>)

### AI overview

AWS weekly roundup covering the planned acquisition of DuckLabs, the company behind DuckDB, alongside Amazon ECS recovery updates and AWS Lambda preview runtimes for Node.js 26 and Python 3.15.

### Source excerpt

The news that interested me the most last week was the DuckLabs acquisition. AWS has signed a definitive agreement to acquire DuckLabs, the Amsterdam-based company behind DuckDB, the popular open source analytical database that runs in-process and executes SQL directly against files like Parquet, CSV, and JSON. DuckDB stays open source under its independent foundation [...]

## AWS Weekly Roundup: Local Zone in Athens, Claude Opus 5 on AWS, Lambda durable execution for .NET, and more (July 27, 2026)

DevFeed: [AWS Weekly Roundup: Local Zone in Athens, Claude Opus 5 on AWS, Lambda durable execution for .NET, and more (July 27, 2026)](<https://devfeed.tech/articles/aws-weekly-roundup-local-zone-in-athens-claude-opus-5-on-aws-lambda-durable-execution-for-net-and-more-july-27-2026-4614.md>)

Original publisher: [Read original article](<https://aws.amazon.com/blogs/aws/aws-weekly-roundup-july-27-2026/>)

Author: Daniel Abib

Published: 2026-07-27T14:54:41Z

Content type: news

Language: en

Sources: [AWS News Blog](<https://devfeed.tech/sources/aws-news-blog.md>)

Topics: [Amazon Web Services](<https://devfeed.tech/topics/aws.md>), [AWS Local Zones](<https://devfeed.tech/topics/aws-local-zones.md>), [Latency](<https://devfeed.tech/topics/latency.md>), [Amazon Bedrock](<https://devfeed.tech/topics/amazon-bedrock.md>), [Amazon EC2](<https://devfeed.tech/topics/amazon-ec2.md>), [Amazon S3](<https://devfeed.tech/topics/amazon-s3.md>), [Claude](<https://devfeed.tech/topics/claude.md>), [cloud-infrastructure](<https://devfeed.tech/topics/cloud-infrastructure.md>), [Amazon Elastic Container Service](<https://devfeed.tech/topics/amazon-elastic-container-service.md>), [anthropic](<https://devfeed.tech/topics/anthropic.md>), [data-governance](<https://devfeed.tech/topics/data-governance.md>)

Tags: [amazon-bedrock](<https://devfeed.tech/tags/amazon-bedrock.md>), [amazon-bedrock-agentcore](<https://devfeed.tech/tags/amazon-bedrock-agentcore.md>), [amazon-connect](<https://devfeed.tech/tags/amazon-connect.md>), [amazon-ec2](<https://devfeed.tech/tags/amazon-ec2.md>), [amazon-s3](<https://devfeed.tech/tags/amazon-s3.md>), [amazon-sagemaker-ai](<https://devfeed.tech/tags/amazon-sagemaker-ai.md>), [announcements](<https://devfeed.tech/tags/announcements.md>), [anthropic](<https://devfeed.tech/tags/anthropic.md>), [aws](<https://devfeed.tech/tags/aws.md>), [aws-lambda](<https://devfeed.tech/tags/aws-lambda.md>), [aws-local-zones](<https://devfeed.tech/tags/aws-local-zones.md>), [claude](<https://devfeed.tech/tags/claude.md>), [data-governance](<https://devfeed.tech/tags/data-governance.md>), [latency](<https://devfeed.tech/tags/latency.md>), [news](<https://devfeed.tech/tags/news.md>), [week-in-review](<https://devfeed.tech/tags/week-in-review.md>)

### AI overview

An AWS weekly roundup covering a new Local Zone in Athens, Greece, and selected AWS launches and updates, including Claude Opus 5 on Amazon Bedrock. The article highlights local data processing, data residency, low latency, and infrastructure for regional workloads.

### Source excerpt

Last week I had the privilege of spending three days in São Paulo with technical builders from across Latin America, brought together for a regional tech event full of deep-dive sessions, hands-on workshops, and conversations with customers and partners. What struck me most wasn't any single session, it was the energy of a technical community [...]

## From Hugging Face to Amazon SageMaker Studio in one click

DevFeed: [From Hugging Face to Amazon SageMaker Studio in one click](<https://devfeed.tech/articles/from-hugging-face-to-amazon-sagemaker-studio-in-one-click-7090.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/amazon/one-click-to-sagemaker-studio>)

Author: Hazim Qudah; Naidile Murali; Jeff Boudier; Simon Pagezy; Enrique Hernández Calabrés

Published: 2026-07-07T21:15:33Z

Content type: release

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [Amazon SageMaker AI](<https://devfeed.tech/topics/amazon-sagemaker-ai.md>), [hugging face](<https://devfeed.tech/topics/hugging-face.md>), [Amazon Web Services](<https://devfeed.tech/topics/aws.md>), [AWS IAM](<https://devfeed.tech/topics/aws-iam.md>), [Deployment](<https://devfeed.tech/topics/deployment.md>), [Fine-tuning](<https://devfeed.tech/topics/fine-tuning.md>), [enterprise deployment](<https://devfeed.tech/topics/enterprise-deployment.md>), [Serverless](<https://devfeed.tech/topics/serverless.md>)

Tags: [amazon-sagemaker-ai](<https://devfeed.tech/tags/amazon-sagemaker-ai.md>), [aws](<https://devfeed.tech/tags/aws.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [data](<https://devfeed.tech/tags/data.md>), [deployment](<https://devfeed.tech/tags/deployment.md>), [fine-tuning](<https://devfeed.tech/tags/fine-tuning.md>), [hugging-face](<https://devfeed.tech/tags/hugging-face.md>), [iam](<https://devfeed.tech/tags/iam.md>), [serverless](<https://devfeed.tech/tags/serverless.md>)

### AI overview

Hugging Face and Amazon SageMaker AI now provide a one-click path from supported model pages to SageMaker Studio. The integration can create a configured Studio environment and preserve model context for customization, fine-tuning, training, experimentation, and endpoint deployment.

### Source excerpt

Previously, getting started on SageMaker Studio after discovering a model on Hugging Face required navigating multiple steps between opening Amazon SageMaker AI in the AWS Console, creating a domain, configuring IAM permissions, and sometimes requesting GPU quota. For developers who want to iterate quickly, this friction slows down the path from inspiration to experimentation. The integration creates a more direct path from discovery to enterprise deployment.

## AWS Weekly Roundup: Claude Sonnet 5 on AWS, Amazon WorkSpaces for AI agents, AWS service availability updates, and more (July 6, 2026)

DevFeed: [AWS Weekly Roundup: Claude Sonnet 5 on AWS, Amazon WorkSpaces for AI agents, AWS service availability updates, and more (July 6, 2026)](<https://devfeed.tech/articles/aws-weekly-roundup-claude-sonnet-5-on-aws-amazon-workspaces-for-ai-agents-aws-service-availability-updates-and-more-july-6-2026-4612.md>)

Original publisher: [Read original article](<https://aws.amazon.com/blogs/aws/aws-weekly-roundup-claude-sonnet-5-on-aws-amazon-workspaces-for-ai-agents-aws-service-availability-updates-and-more-july-6-2026/>)

Author: Daniel Abib

Published: 2026-07-06T15:46:43Z

Content type: news

Language: en

Sources: [AWS News Blog](<https://devfeed.tech/sources/aws-news-blog.md>)

Topics: [Amazon WorkSpaces](<https://devfeed.tech/topics/amazon-workspaces.md>), [Amazon EC2](<https://devfeed.tech/topics/amazon-ec2.md>), [AWS CloudFormation](<https://devfeed.tech/topics/aws-cloudformation.md>), [Amazon Elastic Kubernetes Service](<https://devfeed.tech/topics/amazon-elastic-kubernetes-service.md>), [Kubernetes](<https://devfeed.tech/topics/kubernetes.md>)

Tags: [ai-agents](<https://devfeed.tech/tags/ai-agents.md>), [amazon-bedrock](<https://devfeed.tech/tags/amazon-bedrock.md>), [amazon-cloudwatch](<https://devfeed.tech/tags/amazon-cloudwatch.md>), [amazon-ec2](<https://devfeed.tech/tags/amazon-ec2.md>), [amazon-eks](<https://devfeed.tech/tags/amazon-eks.md>), [amazon-elastic-kubernetes-service](<https://devfeed.tech/tags/amazon-elastic-kubernetes-service.md>), [amazon-opensearch-service](<https://devfeed.tech/tags/amazon-opensearch-service.md>), [amazon-sagemaker-ai](<https://devfeed.tech/tags/amazon-sagemaker-ai.md>), [amazon-workspaces](<https://devfeed.tech/tags/amazon-workspaces.md>), [aws](<https://devfeed.tech/tags/aws.md>), [aws-certificate-manager](<https://devfeed.tech/tags/aws-certificate-manager.md>), [aws-cloudformation](<https://devfeed.tech/tags/aws-cloudformation.md>), [claude](<https://devfeed.tech/tags/claude.md>), [kubernetes](<https://devfeed.tech/tags/kubernetes.md>), [news](<https://devfeed.tech/tags/news.md>), [tls](<https://devfeed.tech/tags/tls.md>), [week-in-review](<https://devfeed.tech/tags/week-in-review.md>)

### AI overview

AWS weekly roundup covering Amazon WorkSpaces for AI agents, Claude Sonnet 5 availability, service availability updates, and recent launches including EC2 instances, CloudFormation Express mode, EKS Kubernetes rollbacks, and ACM ACME support.

### Source excerpt

A couple of editions ago I wrote about what I find so energizing about working with startups. Last week I got a fresh dose of it: I spent a few days with the AWS Startups team, listening to stories of founders talking about the problems they're actually solving. One story that stayed with me came [...]

## How to deploy and fine-tune DeepSeek models on AWS

DevFeed: [How to deploy and fine-tune DeepSeek models on AWS](<https://devfeed.tech/articles/how-to-deploy-and-fine-tune-deepseek-models-on-aws-7161.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/deepseek-r1-aws>)

Author: Simon Pagezy; Jeff Boudier; David Corvoysier

Published: 2025-01-30T00:00:00Z

Content type: tutorial

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [deepseek](<https://devfeed.tech/topics/deepseek.md>), [inference-endpoints](<https://devfeed.tech/topics/inference-endpoints.md>), [Amazon Web Services](<https://devfeed.tech/topics/aws.md>), [hugging face](<https://devfeed.tech/topics/hugging-face.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [Amazon Bedrock](<https://devfeed.tech/topics/amazon-bedrock.md>), [Amazon SageMaker AI](<https://devfeed.tech/topics/amazon-sagemaker-ai.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [autoscaling](<https://devfeed.tech/topics/autoscaling.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>)

Tags: [amazon-bedrock](<https://devfeed.tech/tags/amazon-bedrock.md>), [amazon-sagemaker](<https://devfeed.tech/tags/amazon-sagemaker.md>), [amazon-sagemaker-ai](<https://devfeed.tech/tags/amazon-sagemaker-ai.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [autoscaling](<https://devfeed.tech/tags/autoscaling.md>), [aws](<https://devfeed.tech/tags/aws.md>), [deepseek](<https://devfeed.tech/tags/deepseek.md>), [deployment](<https://devfeed.tech/tags/deployment.md>), [generative-ai](<https://devfeed.tech/tags/generative-ai.md>), [how-to](<https://devfeed.tech/tags/how-to.md>), [inference](<https://devfeed.tech/tags/inference.md>), [inference-endpoints](<https://devfeed.tech/tags/inference-endpoints.md>), [llms](<https://devfeed.tech/tags/llms.md>), [models](<https://devfeed.tech/tags/models.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [partnerships](<https://devfeed.tech/tags/partnerships.md>)

### AI overview

This tutorial explains how to deploy and fine-tune DeepSeek-R1 and its distilled models on AWS using Hugging Face Inference Endpoints. It covers production deployment with dedicated compute, autoscaling, scale-to-zero, security, optimized hardware, and deployment options through Amazon Bedrock and Amazon SageMaker AI.

### Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.