PrivOps

Getting clean, actionable data into the hands of leaders and all personnel at the right time is critical for mission success. By creating a library of standardized, interchangeable objects that can be used and reused to optimize data pipeline construction, the PrivOps metaDNA catalog makes it possible to accelerate the process of creating clean, actionable data from many data sources and safely s

03/25/2024

After some pretty extensive experimentation with generative AI over the last year (chatGPT-4, 3.5, 3.0), I have come to the conclusion that it's like dealing with an idiot savant - absolutely clueless in some ways, astonishing in others. One of those astonishing areas is bu****it, or more graciously described, imagination. I hate the term hallucination when applied to AI as it implies the AI has the ability to discern reality in the first place, which I don't think it does, at least not yet.

Using Generative AI with Clean Data to Survive in Shark Infested Waters: Lean Data (Part 3) — PrivOps - low-code, no-code integration and access management

11/21/2023

How do you deal with Data Privacy when thinking about using your enterprise data with AI? Unless access to clean compliant data at scale is part of your AI initiative, it will fail. Please enjoy this post to learn more.

Using Generative AI with Clean Data to Survive in Shark Infested Waters: Lean Data (Part 3) — PrivOps - low-code, no-code integration and access management In part 3 of this blog post series, we discuss how a data fabric can be used to implement techniques borrowed from lean manufacturing to optimize the time required to integrate training data for LLMs and maximize business results.