Bringing AI to Your Data
summary
Google Cloud demonstrates concrete paths to production: TPU v5 hardware claims 4x performance, Vertex AI combines Vertex AI Search and Vertex AI Conversation for chat and search over company PDFs and web pages, and a Devo Team accelerator promises to put ML in production in less than two weeks versus a typical five‑week timeline. Model Garden hosts over 100 models, model tuning works with as few as 100 samples, and Duet/Document/Contact Center AI appear in preview with grounding, safety filters and provenance links.
AI-written summary · about
chapters (10)
- 0:00Introduction
- 3:24Vertex AI lifecycle
- 8:24Generative AI infrastructure
- 12:43Vertex AI Search & Conversation
- 17:04Generative AI use cases
- 21:01AI models & customization
- 25:02Grounding for accuracy
- 26:27Duet AI interactions
- 28:55Free resources & learning
- 30:22Google Cloud leads in AI
related talks
31mGoogle's AI Map
30mAI in the Cloud
45mFrom Buzz to Benefits: Google AI in Action
11mapproach to generative AI
51mCloud AI: How to Get Started Injecting AI Into Your Applications
44mBuilding smarter solutions with no expertise in machine learning
32mMachine Learning with Google Cloud Platform
12mKeynote: What's New in AI
