Managing LLM application performance through code standards, April 1, 2025
Catching Claude Cheating, March 23, 2025
Scanning AI application code for vulnerabilities and performance issues, March 17, 2025
Evals are not all you need, March 3, 2025
An AI Cyber Incident in Plain Sight, Nov 24, 2024
LLM System Data Exfiltration is not an LLM Issue, Aug 25, 2024
AI cybersecurity lessons from genAI, June 21, 2024
You won't train a better Gen AI model from your desk, April 13, 2024
Hyperbole in LLM testing, April 7, 2024
Data bias is giving way to training bias, Feb 24, 2024
AI Trends for 2024, Dec 30, 2023
Large Language Model Inference in Fortran, Dec 27, 2023
AI Model Weight Providers Should Not Police Uses, No Matter How Awful They Are, Aug 30, 2023
Prompting, realized, and unrealized bias in generatvie AI, Aug 20, 2023
Why host your own llm? Aug 13, 2023
llama2.ipynb (not really writing, it's from scratch language model inference, with commentary, to try and show what the AI hype is really about). July 30, 2023 Also on github
Technical considerations for applying copyright and copyleft to AI, July 25, 2023
Licenses used for AI model weights, July 21, 2023
Foundational AI models do not violate copyright, July 18, 2023
Copyright for AI Model Weights, July 10, 2023
Motivations and strategy for open sourcing AI model weights, July 7, 2023
Software licenses masquerading as open source, June 1, 2023
Using Gnuplot for ascii charts inside notebooks, May 17, 2023
Into the great wide open AI, May 10, 2023
Content and controversy in generative AI models, April 21, 2023
Random numbers in bash, March 2023
Tempering expectations for generative AI, March 31, 2023
The need for open AI models, Feb 21, 2023
Moving from AI use-cases to products, January 24, 2023
Manufacturing is leading the way in accountable AI, November 22, 2022
Kereva Scanner: Scan LLM apps for security and performance vulnerabilities
Available for consulting, speaking engagements, coffee/beer, etc. See resume for contact info.