What makes one AI model better than another? Like any software: the programming. But unlike regular software where the logic has a start and end, AI models are programmed from many angles, all centering around a gigantic maze of numbers and how they mathematically tie together. Essentially, the world's information is converted into the largest mathematical matrix ever conceived, and the matrix is trained, adjusted and tested with countless trials and errors in massive datacenters.
This topic is so fever pitched today that "AI scientists" (a.k.a. AI programmers) who have worked on successful chatbot deployments are offered rock-star compensation packages from competing companies.
Direct From the Horse's Mouth
When chatbots Gemini, Claude, Grok and ChatGPT were asked "what is the secret sauce in AI programming," they all provided similar details; however, ChatGPT had the most comprehensive summary: "the secret sauce in AI programming is more like a stew of thousands of small engineering decisions, most of them unpublished, that together create a competitive edge." See
AI glossary.
The Programming Decisions
The neural network is the architecture of the model, and all decisions affect it. The model is trained with data, the quantity and quality of which are major decisions, as well the algorithms chosen that are constantly making adjustments. Models are tuned and fine-tuned over countless iterations. This is nothing like regular application programming. AI model development is most assuredly a "stew of engineering decisions." See
AI model,
AI training vs. inference,
AI programming,
neural network and
AI transformer.