Vector embeddings and ChatGPT are the key to database startup Pinecone unlocking a $100 million funding round.
Pinecone says it provides long-term memory for AI, meaning a vector database that stores numeric descriptors – vector embeddings – of the parameters describing an item such as an object, an activity, an image, video, audio file etc. The database can be searched for items that match a starting vector to detect likely recommendations to suggest to a purchaser, potentially fraudulent transactions, facial detection and so forth. Such databases are needed for large language models such as ChatGPT in the machine learning arena.
Edo Liberty, founder and CEO of Pinecone, said: “The new wave of AI-powered applications create, store, and search through a large number of vector embeddings, which are AI representations of data. We created Pinecone and the vector database category as a whole to let all AI developers easily work with a scalable and cost efficient database for this workload.”
Pinecone was set up in 2019 and its funding progress has accelerated, with a $10 million seed round in 2021, an A-round worth $28 million in 2022, and now a $100 million B-round. This was led by led by Andreessen Horowitz, with participation from ICONIQ Growth and previous investors Menlo Ventures and Wing Venture Capital.
The funding is in response to Pinecone’s progress in 2022; it claimed to have experienced an explosion in paying customers across all industries and customer sizes, mentioning Gong with its revenue intelligence offering, and Zapier, with is workflow automation tools.
There has been a sudden surge in ChatGPT-related activity in the storage area, with widespread adoption of the ML tool needing data storage facilities and being applied as a tool to query stored information.
- SingleStore sees it as a database querying possibility.
- Databricks sees it as a new way to query analytics datasets.
- Panmnesia wants to run recommendation models faster.
- SK hynix wants to supply HBM chips to servers running chatbots.
- Zilliz is developing a cloud vector database.
- Nuclia is developing language search models.
- Cohesity will provide data structures to OpenAI.
Peter Levine, General Partner at Andreessen Horowitz, said: “The rise of AI is driving a fundamental shift in the way companies approach data management. In a very short amount of time, Pinecone has become a standard and critical component of the modern AI stack.”
B&F expects all storage data management, datalake, data warehouse and AIOps suppliers to be exploring chatbot technology.
Bob Wiederhold, Pinecone president, encapsulated the fervor around the ChatGPT area: “With this funding, we will capitalize on our hypergrowth amidst the AI revolution transforming every line of business and even creating new ones, from AI search to AI chatbots to AI agents and beyond.”
Chatbot technology is experiencing hypergrowth, and has found a place on Gartner’s hype curve where it is rocketing up to the peak of hyper-inflated expectations. Then it will tumble down to the trough of disillusionment, assuming the status of forgotten technologies like phrenology and holographic storage. But the hope is that it will emerge and climb the slope of enlightenment. The race is on to provide the platform technologies that will be needed when the chatbot phenomenon passes that phase and becomes widely deployed in the plateau of productivity.