Business News Report
June 13, 2023

AI Computer Infrastructure Startup Led by Former Google Brain, Palantir, and X Engineers Raises $8.5M in Seed Funding

In Brief

Normal Computing has raised $8.5 million in seed funding to build computer infrastructure enabling AI for enterprise and government applications.

Celesta Capital and First Spark Ventures led the round.

Normal Computing’s Probabilistic AI aims to solve the reliability issues and “hallucinations” of large language models for enterprises.

Normal Computing, the startup building full-stack probabilistic AI computer infrastructure, has raised $8.5 million in a seed round led by Celesta Capital and First Spark Ventures, with participation from Micron Ventures.

AI computer infrastructure startup led by former Google Brain, Palantir, and X engineers Raises $8.5M in seed funding

The newly raised funds will be used to further develop Normal Computing’s infrastructure, and support the research and development of Normal Computing’s application development platform and Probabilistic AI technology.

Normal Computing is a New York-based deep tech startup founded by former Google Brain, Alphabet, X, and Palantir engineers, teamed with leaders and engineers from Meta Probability, HuggingFace, Los Alamos National Laboratory, and Aesara Probability.

The team’s extensive experience in Alphabet’s largest-scale and AI workflows led to the development of Normal Computing’s Probabilistic AI technology. According to Faris Sbahi, the CEO and co-founder at Normal Computing, the existing challenges in the reliability of generative AI models, such as unpredictable factual errors and “hallucinations,” present significant obstacles in advancing core enterprise workflows.

Normal Computing says that its Probabilistic AI may solve these challenges as the technology is designed to deploy these large AI systems reliably, detecting and fixing failures like hallucinations and predictably adapting and learning in real-time to private data and changing conditions.

The company says that integrating large models like LLMs and Diffusion Models into composed workflows with their Probabilistic AI technology – in addition to specialized models, enterprise-specific plugins, and domain-specific processes – can be applied to real-world use cases. 

This technology helps automate complex underwriting processes, which deal with policies that have specific guidelines across multiple locations. It also enables autonomous workflows for creating and verifying specialized code that meets important requirements and follows unique patterns in custom and confidential codebases.

“AI has the potential to improve essentially everything we value, but we’ve seen a trend of doubling down on certain architectures and approaches because they work with today’s held conventional tools and infrastructure, not because they are as trustworthy or understandable as we can achieve,” said Faris Sbahi.

He suggested that the solution is to redesign AI systems from the ground up, as opposed to relying on surface-level approaches like prompt engineering and retrieval-based methods, which are insufficient, particularly when it comes to addressing challenges faced by enterprises.

Normal Computing is currently initiating pilot programs with Fortune 500 companies in various industries, with a focus on key sectors such as semiconductor manufacturing, supply chain management, banking, and government agencies.

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About The Author

Cindy is a journalist at Metaverse Post, covering topics related to web3, NFT, metaverse and AI, with a focus on interviews with Web3 industry players. She has spoken to over 30 C-level execs and counting, bringing their valuable insights to readers. Originally from Singapore, Cindy is now based in Tbilisi, Georgia. She holds a Bachelor's degree in Communications & Media Studies from the University of South Australia and has a decade of experience in journalism and writing. Get in touch with her via [email protected] with press pitches, announcements and interview opportunities.

More articles
Cindy Tan
Cindy Tan

Cindy is a journalist at Metaverse Post, covering topics related to web3, NFT, metaverse and AI, with a focus on interviews with Web3 industry players. She has spoken to over 30 C-level execs and counting, bringing their valuable insights to readers. Originally from Singapore, Cindy is now based in Tbilisi, Georgia. She holds a Bachelor's degree in Communications & Media Studies from the University of South Australia and has a decade of experience in journalism and writing. Get in touch with her via [email protected] with press pitches, announcements and interview opportunities.

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