AWS AI’s Post

One more reason why one should use SageMaker Training - debugging made easier by providing shell access to model training environment - you can now easily diagnose a stuck training job, use command line tools to monitor the underlying compute resources, debug the training script, and then, quickly fix and execute it. #aws #machinelearning #modeltraining #generativeAI https://lnkd.in/gYdv_VHp

I have a question for folks who use Step Functions with CDK. Do you ever look at ASL? Or use the console to design a workflow before coding it in CDK? If you do, how do you map one DSL to the other? Feels like you have to learn both... 🤔 #aws #stepfunctions

Foundation model benchmarking tool. Run any model on Amazon SageMaker and benchmark for performance across instance type and serving stack options. PyPi library and CloudFormation template also available. #GenAI #LLMOps #AWS #SageMaker #Benchmark

Learning K8S and How many Components are in Worker node and Worker Node. If Missing then Please Comment. #AWS #K8S

In just THREE days, Andy Tante has: 1️⃣ Hosted a static website with Amazon S3 2️⃣ Visualised a dataset with Amazon QuickSight 3️⃣ Created a chatbot with Amazon Lex Want beginner friendly #AWS projects with FREE step by step guides and documentation templates? Just comment or DM "I'm in!" to get access ⚡ #awscloudpractitioner #cloudcomputing

a simple and easy to understand diagram of the AWS Sagemaker Groundtruth #ObjectDetectionModel#ML#AWSSageMaker

Fine-tune and deploy Llama 2 models cost-effectively in Amazon SageMaker JumpStart with AWS Inferentia and AWS Trainium

A reminder of how important screen sharing can be when working through a problem! We’ve been blocked on deploying docker images via Sagemaker for a while because of AWS permissions issues. Went back and forth with AWS support via email but no luck. 1 hour of screen sharing with an AWS engineer and we’re back in business! Finding that Sagemaker is great for prototyping/exploration but when you start building your own infrastructure with it it becomes tricky quickly! #aws #sagemaker #mlops

Five ways Amazon Q simplifies AWS CloudFormation development In this post, we will show you five ways Amazon Q Developer can help you work with CloudFormation for template code generation, querying CloudFormation resource requirements, explaining existing template code, understanding deployment options and issues, and querying CloudFormation documentation. For more such useful information, Do follow Whizlabs #AWS #AWScloud #AmazonQ #CloudFormation #CloudComputing #CloudComputingServices #whizlabs #AWScloudformation

Get hands-on experience scaling foundation model training using #AmazonSageMaker HyperPod & #AWSTrainium. 🤖 https://go.aws/45Juf4O At this workshop, you'll gain insights into setting up the software stack, optimizing resources, ensuring fault tolerance, & leveraging high-performance Trainium instances as #AWS solutions architects guide you through the labs.