kazunori279

3 ms·

1. 1.▲
   by kazunori279 2y ago

   Improving RAG search relevance with new "task type" embeddings developed by the Google DeepMind team. Task type embeddings can effectively bridge the semantic gap between questions and answers, leading to more effective retrieval
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   Using "task type" embeddings for improving RAG search quality(cloud.google.com)

   2 points by kazunori279 2y ago|0 comments
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   What is Multimodal Search: “LLMs with vision” change businesses(cloud.google.com)

   1 points by kazunori279 3y ago|1 comments
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   by kazunori279 3y ago

   What if large language models (LLMs) had "vision", the ability to understand the meaning of images? Just like we have seen the innovation with LLMs with chatbots and text data, the ability would make another huge impact on busines
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   Vertex AI Embeddings for Text: Grounding LLMs Made Easy(cloud.google.com)

   2 points by kazunori279 3y ago|1 comments
6. 6.▲
   by kazunori279 3y ago

   Many people are now starting to think about how to bring Gen AI and large language models (LLMs) to production services. You may be wondering "How to integrate LLMs or AI chatbots with existing IT systems, databases and business data?&
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   Explore the Galaxy of Images with Cloud Vision API(cloud.google.com)

   2 points by kazunori279 10y ago|0 comments
8. 8.▲
   by kazunori279 11y ago

   This is so old! (from the author :)