It was officially a 4-day workweek, but felt like a regular week. Lots going on, and plenty of things to do. But I greatly prefer that to the alternative! Have a great weekend, y’all.
[blog] Serving Stable Diffusion with RayServe on GKE Autopilot. How would you make this text-to-image model available to other apps in your environment? William gives us a step by step for getting it going on Kubernetes.
[blog] Coaching Feedback. I’m familiar with the SHARE model for giving feedback, but don’t always remember to use it. This is a good reminder to break it out more often.
[blog] Google named a leader in the Forrester Wave: AI/ML Platforms, Q3 2024. You like us, you really like us. It’s cool to see Google as the only hyperscale cloud in the leader section.
[blog] Getting 🍨 Ice Cream 🍦 Recommendations at Scale with Gemini, Embeddings, and Vector Search. Alok really likes ice cream. He’s also great at AI/ML and helps us understand the role of embeddings in creating a recommendation engine.
[article] Cycle Time. Most of you are trying to shrink the time it takes to go from idea to working software in production. But what activity starts the “cycle time” clock? And when is the software considered “shipped”?
[blog] Securing Generative AI: Defending Against Prompt Injection. I thought this was good advice for a problem most of us hadn’t even thought much about yet.
[guide] Enterprise application with Oracle Database on Compute Engine. There’s more going on than just AI stuff. Here’s a good new guide on hosting a highly available app that depends on Oracle databases. All on VMs.
[blog] Gemma explained: PaliGemma architecture. This is an open vision-language model that produces a text response from image or text input.
[article] InfoQ AI, ML and Data Engineering Trends Report – September 2024. What’s “late majority” versus “early adopters” in this fast moving space? Here’s one lens on it.
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