Tag: ai/ml

Digital lending is a critical business enabler for banks and financial institutions. Customers apply for a loan online after completing the know your customer (KYC) process. A typical digital lending process involves various activities, such as user onboarding (including steps to verify the user through KYC), credit verification, risk verification, credit underwriting, and loan sanctioning. …

Read more “Build an Amazon Bedrock based digital lending solution on AWS”

Closing the gap between impressive model demos and real-world performance is crucial for successfully deploying generative AI for enterprise. Despite the incredible capabilities of generative AI for enterprise, this perceived gap may be a barrier for many developers and enterprises to “productionize” AI. This is where retrieval-augmented generation (RAG) becomes non-negotiable – it strengthens your …

Read more “Introducing Vertex AI RAG Engine: Scale your Vertex AI RAG pipeline with confidence”

In this post, I’ll show you how to use Amazon Bedrock—with its fully managed, on-demand API—with your Amazon SageMaker trained or fine-tuned model. Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies such as AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and …

Read more “Unlock cost-effective AI inference using Amazon Bedrock serverless capabilities with an Amazon SageMaker trained model”

The exponential growth of machine learning models brings with it ever-increasing datasets. This data deluge creates a significant bottleneck in the Machine Learning Operations (MLOps) lifecycle, as traditional data preprocessing methods struggle to scale. The preprocessing phase, which is critical for transforming raw data into a format suitable for model training, can become a major …

Read more “Distributed data preprocessing with GKE and Ray: Scaling for the enterprise”

Generative AI applications are gaining widespread adoption across various industries, including regulated industries such as financial services and healthcare. As these advanced systems accelerate in playing a critical role in decision-making processes and customer interactions, customers should work towards ensuring the reliability, fairness, and compliance of generative AI applications with industry regulations. To address this …

Read more “Align and monitor your Amazon Bedrock powered insurance assistance chatbot to responsible AI principles with AWS Audit Manager”

Foundation models such as Gemini have revolutionized how we work, but sometimes they need guidance to excel at specific business tasks. Perhaps their answers are too long, or their summaries miss the mark. That’s where supervised fine-tuning (SFT) comes in. When done right, it unlocks incredible precision to tailor Gemini for specialized tasks, domains, and …

Read more “Supervised Fine Tuning for Gemini: A best practices guide”

In this post, we walk you through the process to build an automated mechanism using Amazon SageMaker to process your log data, run training iterations over it to obtain the best-performing anomaly detection model, and register it with the Amazon SageMaker Model Registry for your customers to use it. Log-based anomaly detection involves identifying anomalous …

Read more “Efficiently build and tune custom log anomaly detection models with Amazon SageMaker”