Meet Edo Liberty, founder of Pinecone, a managed database for large-scale vector searching. As far as his career goes, he hasn’t fallen short of brilliant, and he has done an outstanding job with his academic achievements as well.

Until April 2019, was a Director of Research at AWS and Head of Amazon AI Labs. The Lab built cutting-edge machine learning algorithms, systems, and services for AWS customers. 

As a machine learning specialist, he developed horizontal platforms and improved applications, such as online advertising, search, security, media recommendation, and email abuse prevention. He holds a B.Sc. in Physics and Computer Science from Tel Aviv University, as well as a Ph.D. in Computer Science from Yale University. He then became a Postdoctoral Fellow at Yale’s Program in Applied Mathematics. He has more than 75 academic papers and patents published in the areas of machine learning, systems, and optimization.

Pinecone, his company, has developed a vector database that serves as a crucial infrastructure component for AI-powered applications, acting as their long-term memory. Their managed service enables engineers to build fast and scalable applications that use embeddings from AI models, thereby facilitating quicker production. Recently, Pinecone secured $100M in Series B funding, valuing the company at $750M. The funding round was led by Andreessen Horowitz, with participation from ICONIQ Growth, as well as previous investors Menlo Ventures and Wing Venture Capital. Pinecone operates in San Francisco, New York, and Tel Aviv.

So, when in 2019 Edo Liberty established Pinecone, he did it with the aim of leveraging the power of AI models and vector search to enhance applications such as spam detectors and recommendation systems. In his role as a research director at AWS and Yahoo!, Edo had witnessed the potential of combining these technologies on a large scale. However, he was surprised to discover that there was no readily available packaged solution for those without the same engineering and data-science resources at their disposal. This realization led to the creation of Pinecone and the vector database.

Pinecone was designed to provide the essential storage and retrieval infrastructure required for developing and operating cutting-edge AI applications. The guiding principle behind its creation was to make the solution accessible to engineering teams of all sizes and levels of AI expertise. This led to the development of a fully managed service that is renowned for its ease of use and accessibility.

Their team of engineers and scientists are dedicated to developing cutting-edge search and database technology that will drive AI/ML applications for the foreseeable future. Their goal is to provide users with capabilities that were previously only available to a select few tech giants.

The Pinecone vector database is an essential element of the AI technology stack, which assists companies in addressing one of the most significant obstacles in deploying GenAI solutions: hallucinations. It enables them to store, search, and retrieve the most pertinent and current information from their data, and send that context to Large Language Models (LLMs) with each query. This process is known as Retrieval Augmented Generation (RAG), and Pinecone facilitates the delivery of relevant, precise, and prompt responses from search or GenAI applications to end-users..

Furthermore, Pinecone has recently announced its integration with Amazon Bedrock. This fully managed service from Amazon Web Services (AWS) is designed to facilitate the development of Generative AI (GenAI) applications. As a result of this integration, customers can now significantly reduce hallucinations and accelerate the go-to-market of Generative AI (GenAI) applications such as chatbots, assistants, and agents.

Amazon Bedrock is a serverless platform that empowers users to choose and tailor suitable models to meet their requirements. The platform seamlessly integrates and deploys these models using renowned AWS services, including Amazon SageMaker.

The integration of Pinecone with Amazon Bedrock provides developers with a seamless and efficient means of constructing factual GenAI applications that incorporate Pinecone’s user-friendly interface, high-performance capabilities, cost-effectiveness, and scalability with their preferred LLM. Pinecone’s excellent security features and its accessibility on the AWS Marketplace enable enterprise developers to expedite the deployment of these GenAI solutions to the market.

According to the Founder & CEO of Pinecone, a significant number of AWS customers have already embraced the platform. The integration of Pinecone with AWS now provides an opportunity for more developers to create and deploy dependable and scalable GenAI applications without delay. The integration will be made available to all Amazon Bedrock and Pinecone users by the conclusion of the 4th quarter. For further details on the integration, read their most recent blog post.

We can’t wait to see what else this company has in store for the future!

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