ContentCategory.TUTORIAL

Gemini Drops is our regular monthly update on how to get the most out of the Gemini app.

A practical, code-driven guide to scaling deep learning across machines — from NCCL process groups to gradient synchronization The post Building a Production-Grade Multi-Node Training Pipeline with PyTorch DDP appeared first on Towards Data Science .

Simulate a quantum computer with Qiskit The post A Beginner’s Guide to Quantum Computing with Python appeared first on Towards Data Science .

Learn how to move a PostgreSQL data directory to a new location on Ubuntu 20.04 using rsync.

Google has released Gemini 3.1 Flash Live in preview for developers through the Gemini Live API in Google AI Studio. This model targets low-latency, more natural, and more reliable real-time voice interactions, serving as Google’s ‘highest-quality audi…

In this tutorial, we work directly with Qwen3.5 models distilled with Claude-style reasoning and set up a Colab pipeline that lets us switch between a 27B GGUF variant and a lightweight 2B 4-bit version with a single flag. We start by validating GPU av…

In this post, we walk you through how to implement a fully automated, context-aware AI solution using a serverless architecture on AWS. This solution helps organizations looking to deploy responsible AI systems, align with compliance requirements for v…

Last year, AWS announced an integration between Amazon SageMaker Unified Studio and Amazon S3 general purpose buckets. This integration makes it straightforward for teams to use unstructured data stored in Amazon Simple Storage Service (Amazon S3) for …

In my latest posts, we’ve talked a lot about prompt caching as well as caching in general, and how it can improve your AI app in terms of cost and latency. However, even for a fully optimized AI app, sometimes the responses are just going to take some …

Learn how to deploy Postgres to a Kubernetes cluster with StatefulSets, persistent storage, and Helm. Follow this step-by-step guide and get started.