Security

How Google AI’s New Method Reduces LLM Training Data by 10,000x Google Research has unveiled a groundbreaking method for fine-tuning large language models (LLMs) that reduces required training data by up to 10,000 times. This innovative approach utilizes active learning to focus expert labeling on the most informative examples, especially “boundary cases” where model uncertainty is highest. In experiments with Gemini Nano models, this technique matched or surpassed the quality of models trained on 100,000 random labels with as few as 250 to 450 targeted examples. This development promises to make AI model development significantly leaner, more agile, and more cost-effective. ...

Overview In this post, I am going to describe how to maintain access to Amazon AWS EKS - Kubernetes cluster with only attaching an IAM Role as an instance profile, without configuring access keys on the EC2 instance. The benefit of course is not storing any Amazon IAM credentials on the EC2 instance, having your infrastructure more secure. Use Case: Jenkins CI/CD Pipeline In my use case, I wanted to have my Jenkins CI server have access to EKS cluster for adding continuous delivery using Jenkins declarative pipeline to my continuous integration process. By doing that, I achieved a full CI/CD process for all the microservices that Jenkins handled. ...