Vertex AI Embeddings API + Matching Engine: Grounding LLMs made easy

Many people are now considering how to bring generative AI and large language models to production services and facing several challenges.
You may wonder, "How to integrate LLMs or AI chatbots with existing IT systems, databases, and business data?". "We have thousands of products. How can I let LLM memorize them all precisely?". Or "How to handle the hallucination issues in AI chatbots to build a reliable service?".
A quick solution is "grounding with embeddings and vector search." What is grounding? What are embedding and vector search? This video discusses these crucial concepts to build reliable generative AI services for enterprise use.
Resources:
Original blog post → goo.gle/43sCOyh
Stack Overflow semantic search demo → goo.gle/3OkeLgm
Stack Overflow semantic search demo sample code → goo.gle/3Omj5fm
Nomic AI visualization → goo.gle/3Y14Dwc
Google Machine Learning Crash Course: Embeddings → goo.gle/3NRfOTy
Vertex AI Model Garden → goo.gle/3pXIene
Vertex AI Embeddings API for Text → goo.gle/44TufNN
Vertex AI Matching Engine → goo.gle/44xeYCO
Gen App Builder Enterprise Search → goo.gle/4798UlN
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[@googlecloudtech]

Subscribe to Google Cloud Tech → goo.gle/GoogleCloudTech

[@ollieanntan4478]

You couldn't afford to pay an intern to read it?

[@kidusadugna5425]

lol

[@sounishnath513]

Is it created by AI itself. The voice is a little bit off . Kind of new tone

[@linjithnp]

I felt that too. Some sentences are not ending appropriately

[@JohnMcclaned]

@@linjithnp Yeah it's text to speech.

[@o1egm]

Ok, and what is grounding??

[@waqarsbc]

I dislike it as a video.