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Pinecone leads 'explosion' in vector databases for generative AI - VentureBeat
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Pinecone leads 'explosion' in vector databases for generative AI - VentureBeat
July 14, 2023 9:12 AM Bob Wiederhold, Pinecone COO, right, speaks with investor Tim Tully, at VB Transform on Wednesday Image Credit: Michael O'Donnell Head over to our on-demand library to view sessions from VB Transform 2023. Register Here Vector databases, a relatively new type of database that can store and query unstructured data such as images, text and video, are gaining popularity among developers and enterprises who want to build generative AI applications such as chatbots, recommendation systems and content creation. One of the leading providers of vector database technology is Pinecone, a startup founded in 2019 that has raised $138 million and is valued at $750 million. The company said Thursday it has “way more than 100,000 free users and more than 4,000 paying customers,” reflecting an explosion of adoption by developers from small companies as well as enterprises that Pinecone said are experimenting like crazy with new applications. By contrast, the company said that in December it had fewer than in the low thousands of free users, and fewer than 300 paying customers. Pinecone held a user conference on Thursday in San Francisco, where it showcased some of its success stories and announced a partnership with Microsoft Azure to speed up generative AI applications for Azure customers. Event VB Transform 2023 On-Demand Did you miss a session from VB Transform 2023? Register to access the on-demand library for all of our featured sessions. Register Now Follow all our VentureBeat Transform 2023 coverage Bob Wiederhold, the president and COO of Pinecone, said in his keynote talk at VB Transform that generative AI is a new platform that has eclipsed the internet platform and that vector databases are a key part of the solution to enable it. He said the generative AI platform is going to be even bigger than the internet, and “is going to have the same and probably even bigger impacts on the world.” Vector databases: a distinct type of database for the generative AI era Wiederhold explained that vector databases allow developers to access domain-specific information that is not available on the internet or in traditional databases, and to update it in real time. This way, they can provide better context and accuracy for generative AI models such as ChatGPT or GPT-4, which are often trained on outdated or incomplete data scraped from the web. Vector databases allow you to do semantic search, which is a way to convert any kind of data into vectors that allow you to do “nearest neighbor” search. You can use this information to enrich the context window of the prompts. This way, “you will have far fewer hallucinations, and you will allow these fantastic chatbot technologies to answer your questions correctly, more often,” Wiederhold said. Wiederhold’s remarks came after he spoke Wednesday at VB Transform, where he explained to enterprise executives how generative AI is changing the nature of the database, and why at least 30 vector database competitors have popped up to serve the market. See his interview below. Bob Wiederhold, COO of Pinecone, right, speaks with investor Tim Tully of Menlo Ventures at VB Transform on Wednesday Wiederhold said that large language models (LLMs) and vector databases are the two key technologies for generative AI. Whenever new data types and access patterns appear, assuming the market is large enough, a new subset of the database market forms, he said. That happened with relational databases and no-SQL databases, and that’s happening with vector databases, he said. Vectors are a very different way to represent data, and nearest neighbor search is a very different way to access data, he said. He explained that vector databases have a more efficient way of partitioning data based on this new paradigm, and so are filling a void that other databases, such as relational and no-SQL databases, are unable to fill. He added that Pinecone has built its technology from scratch, without compromising on performance, scalability or cost. He said that only by building from scratch can you have the lowest latency, the highest ingestion speeds and the lowest cost of implementing use cases. He also said that the winner database providers are going to be the ones that have built the best managed services for the cloud...
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