Vertex Merging Magic of AlloyDB AI Elevates AI Apps!
Google introduced AlloyDB AI at Next ‘23, a set of built-in features for creating generative AI applications You may call a Vertex AI model from the database using SQL
AlloyDB AI conducts vector queries 10x quicker than PostgreSQL using the IVFFlat index and analytical queries 100X faster
Google’s end-to-end AI platform, Vertex AI, lets you upload, label, train, and deploy ML models Model Garden on Vertex AI supports Google, third-party, and open-source AI models
Five ways to use SQL to use Vertex AI or custom models for similarity search, sentiment analysis, bot identification, healthcare forecasts, and risk prediction
First, extract data from a database or data warehouse, construct embeddings, then upsert the vector into a vector database
Vertex AI’s model textembedding-gecko now generates product text embeddings when you put rows into your database
The pretrained model lets you instantly assess audience response to live broadcasts, creating dynamic user experiences and giving producers real-time feedback to course correct
As a health-tech startup, you want to help primary care doctors understand their patients’ heart health Patient cardiac risk scores may be generated using updated vitals like BMI and blood pressure