FatBrain AI (LZG International, Inc) Files for Several Patents Covering its Artificial Intelligence Suite of Products

FatBrain AI, the leader in powerful and easy-to-use AI solutions for the enterprise stars of tomorrow, files for several patent families.

FatBrain offers a comprehensive suite of Artificial Intelligence (AI) solutions that work by plugging into existing software-as-a-service (SaaS) products like Quickbooks, Shopify, Salesforce, Slack and Hubspot, as well as hundreds of other applications.

The patents filed cover technologies for Peer Intelligence, Hierarchical AI and Private Data Models. The Peer Intelligence patent family claims dynamic scoring for an entity or asset, quantiled by peer behavior within the context of trade (SIC/NAICS/HS), geo, time-series, other data-guided insight. The Hierarchical AI patent family claims generative systems with emergent controls connecting at least micro-, meso- and macro- entities or assets with the dynamic score at each level. The Private Data Model patent family claims augmented, personalized decision-making for multiple peers using small, private data.

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“With our generative AI technologies, FatBrain clients, and especially SMEs harness more effective and efficient insights.”

“Many and smart beat large and heavy. Our generative AI technologies align permissioned data of many into simplified data-driven insights for the best personalized outcomes,” said Peter B. Ritz, co-founder and CEO of FatBrain AI, a reference to U.S. Naval College Prof. John Arquilla’s book on modern warfare “Bitskrieg: The New Challenge of Cyberwarfare.” Polity Books (2021). “With these powerful, private, generative AI technologies, FatBrain clients, and especially SMEs harness more effective and efficient insights impacting everyday business decisions vs. any siloed F500s or government agencies.”

“FatBrain technologies claimed in the patents leverage discoveries from Cognitive Neuroscience to produce effective generative models that learn from small private data. This is in contrast with the traditional AI models —including large language model or LLMs like those in ChatGPT— which need massive amounts of data and learn orders of magnitude slower than humans,” added Dr. Rajarshi Das, PhD, Chief Scientific Officer and emeritus research fellow at the Santa Fe Institute and IBM Research. “Our work builds on the decades of work in control theory with reinforcement learning and multi-agent cooperation now advanced for example, by the latest generative model research championed by the Google’s DeepMind Gemini project.”

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