AWS Machine Learning Blog

DECEMBER 4, 2024

SageMaker AI makes sure that sensitive data stays completely within each customer’s SageMaker environment and will never be shared with a third party. It also empowers data scientists and ML engineers to do more with their models by collaborating seamlessly with their colleagues in data and analytics teams.

ML 133

ML Generative AI Data Scientist ML Engineer 133

AWS Machine Learning Blog

JULY 25, 2024

By accelerating the speed of issue detection and remediation, it increases the reliability of your ML training and reduces the wasted time and cost due to hardware failure. This solution is applicable if you’re using managed nodes or self-managed node groups (which use Amazon EC2 Auto Scaling groups ) on Amazon EKS. and public.ecr.aws.

Auto-complete 112

Auto-complete Software Development ML ML Engineer 112

The MLOps Blog

JANUARY 23, 2023

Just so you know where I am coming from: I have a heavy software development background (15+ years in software). Came to ML from software. Founded two successful software services companies. Founded neptune.ai , a modular MLOps component for ML metadata store , aka “experiment tracker + model registry”.

DevOps 59

DevOps Metadata Software Engineer Data Scientist 59

The MLOps Blog

JULY 18, 2023

But ideally, we strive for complete independence of the models in our system so that we can update them without then having to go update every other model in the pipeline – that’s a danger that you can run into. But it’s absolutely critical for most people in our space that you do some type of auto-scaling.

Conversational AI 52

Conversational AI Natural Language Processing Machine Learning AI 52

AWS Machine Learning Blog

NOVEMBER 14, 2024

It also helps achieve data, project, and team isolation while supporting software development lifecycle best practices. Furthermore, sharing model resources directly across multiple accounts helps improve ML model approval, deployment, and auditing. It can take up to 20 minutes for the setup to complete.

ML 104

ML Auto-complete Machine Learning Auto-classification 104

AWS Machine Learning Blog

DECEMBER 2, 2024

Challenges in deploying LLMs for inference As LLMs and their respective hosting containers continue to grow in size and complexity, AI and ML engineers face increasing challenges in deploying and scaling these models efficiently for inference. Marc Karp is an ML Architect with the Amazon SageMaker Service team.

Large Language Models 109

Large Language Models Auto-complete Machine Learning LLM 109

AWS Machine Learning Blog

JULY 23, 2024

is an auto-regressive language model that uses an optimized transformer architecture. 405B-Instruct You can use Llama models for text completion for any piece of text. Christopher Whitten is a software developer on the JumpStart team. The Llama 3.1 At its core, Llama 3.1 24xlarge, ml.p5.48xlarge Meta-Llama-3.1-8B-Instruct

Machine Learning 124

Machine Learning Computer Vision Python ML 124