Highlights:

  • Zilliz Cloud is utilized to drive AI models for product recommendation engines, semantic text search, targeted advertising, risk management, and fraud protection.
  • Zilliz Cloud can offer the foundation for a ChatGPT/VectorDB/Prompts-as-Code technological stack that, according to the business, enables LLMs to vastly scale out their expertise by gaining access to multiple other data sources.

Zilliz Inc., a startup specializing in vector databases, has announced that its newly upgraded Zilliz Cloud solution is what artificial intelligence practitioners need to prevent hallucinations.

Large language models, such as ChatGPT, have captivated the public’s curiosity because of their amazing ability to generate human-like replies to virtually any query. Nevertheless, Zilliz observes that these models are far from ideal, with one of their significant flaws being that they frequently generate answers in the absence of accurate data. The AI industry refers to this phenomenon as “hallucination,” It may be highly dangerous in some scenarios, such as when AI is employed to answer customer service concerns.

Zilliz thinks it can avoid these hallucinations. It quotes OpenAI LP, the developer of ChatGPT, noting that these falsified replies may be reduced by providing LLMs with external sources of domain-specific data, which Zilliz Cloud can assist in.

Zilliz Cloud is a vector database supporting AI applications built on the open-source Milvus project. These models often translate unstructured data such as texts, videos, and user actions into vectors, which are complicated numerical sequences. So, it is frequently necessary to determine which vectors are closest to or most comparable to others.

A specialized vector database is crucial while sorting and ranking a lot of vectors. Conventional databases are intended to store tables and documents, making them inefficient for machine learning. Zilliz Cloud is unique because it can dynamically alter and index millions of vectors to respond to the usual queries posed to AI models.

Zilliz Cloud drives AI models for product recommendation engines, targeted advertising, semantic text search, risk management, and fraud protection. Nonetheless, its vector-native architecture makes it perfect for LLMs as well.

By utilizing OpenAI plugins to connect to ChatGPT, Zilliz Cloud can offer the foundation for a ChatGPT/VectorDB/Prompts-as-Code technological stack that, according to the business, enables LLMs to vastly scale out their expertise by gaining access to multiple other data sources. With greater understanding, hallucinations should become far less frequent.

Charles Xie, Chief Executive, said that if AI is supposed to fulfill its potential, it needs to become more trustworthy. He further said, “Hallucinations or wrong answers erode that trust. With the billion-vector performance of Zilliz, we can help address that by expanding context and data retrieval.”