Community Picks·2yHow We Reduced a $1,000/month Imgix Bill to $1 using Google Cloud - Hardcover
Adam Fortuna shares how his team reduced their Imgix bill from $1,000/month to $1 using Google Cloud. By migrating to Google Cloud Run and utilizing Imaginary, a Go-based image processing server, they managed to downscale their costs significantly. The new setup involves using a CDN, load balancer, and custom caching configurations to achieve faster response times and lower expenses.
Community Picks·2yBuilding Production API Services with Encore, TypeScript, and Neon Serverless Postgres
Encore now supports Neon Postgres across all environments, including AWS and GCP. This integration streamlines the development, testing, and production deployment of scalable API services. Encore's TypeScript SDK allows developers to use familiar language for backend development, and Neon offers serverless Postgres for optimized performance without manual management. The post details a step-by-step guide to creating and deploying a URL shortener application using Encore and Neon.
Hugging Face·2yDeploy Meta Llama 3.1 405B on Google Cloud Vertex AI
Learn how to deploy Meta Llama 3.1 405B on Google Cloud's Vertex AI using Hugging Face Deep Learning Containers. The post covers setup requirements, Google Cloud configuration, model registration, deployment processes, online prediction, and resource cleanup to avoid unnecessary costs.
Google Cloud·2yTop Google Cloud AI courses for summer learning
Embrace the summer by enhancing your AI skills with Google Cloud's curated learning roadmap. Utilize free monthly credits through the Google Cloud Innovators program to access a range of training courses, from understanding generative AI and responsible AI practices to advanced AI engineering and machine learning with Vertex AI and BigQuery. Level up your skills, earn badges, and explore exclusive prizes along the way.
Community Picks·2yBuilding Generative AI Applications in Go (continued)- Gari Singh, Google
The post discusses building generative AI applications with Go, focusing on various frameworks and APIs provided by Google Cloud. Key highlights include the use of native Go APIs for AI models, the concept of prompt engineering, and orchestrating models using Lang Chain Go. It also covers retrieval augmented generation (RAG) and using vector embeddings for context, with practical demos involving tools like AMA and Gen Kit for better AI integration. The emphasis is on creating modular, extensible applications using these tools.
Community Picks·2yGemini AI MultiModal Model Course
This course teaches how to build an app using the Gemini multimodal AI model developed by Google. The app can analyze uploaded images and provide text-based responses to questions about those images. The course covers an introduction to Gemini, setting up the development environment, authentication, and building the app using Node.js and React. Google provided funding through a grant to make the course possible.