Document Modeling Testing 
O'Reilly on Data
JANUARY 21, 2025
Your companys AI assistant confidently tells a customer its processed their urgent withdrawal requestexcept it hasnt, because it misinterpreted the API documentation. This fueled a belief that simply making models bigger would solve deeper issues like accuracy, understanding, and reasoning. Development velocity grinds to a halt.
O'Reilly on Data
JANUARY 9, 2024
We still rely on humans to test and fix the errors. With the current models, every time you generate code, you’re likely to get something different. How do you understand what the program is doing if it’s a different program each time you generate and test it? Bard even gives you several alternatives to choose from.)
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O'Reilly on Data
MARCH 25, 2025
Weve seen this across dozens of companies, and the teams that break out of this trap all adopt some version of Evaluation-Driven Development (EDD), where testing, monitoring, and evaluation drive every decision from the start. What breaks your app in production isnt always what you tested for in dev! The way out?
O'Reilly on Data
DECEMBER 12, 2019
Not least is the broadening realization that ML models can fail. And that’s why model debugging, the art and science of understanding and fixing problems in ML models, is so critical to the future of ML. Because all ML models make mistakes, everyone who cares about ML should also care about model debugging. [1]
O'Reilly on Data
JUNE 18, 2024
While RAG is conceptually simple—look up relevant documents and construct a prompt that tells the model to build its response from them—in practice, it’s more complex. Including all those results in a RAG query would be impossible with most language models, and impractical with the few that allow large context windows.
CIO Business Intelligence
MARCH 19, 2025
Meanwhile, in December, OpenAIs new O3 model, an agentic model not yet available to the public, scored 72% on the same test. Were developing our own AI models customized to improve code understanding on rare platforms, he adds. That adds up to millions of documents a month that need to be processed.
AWS Big Data
NOVEMBER 27, 2024
dbt helps manage data transformation by enabling teams to deploy analytics code following software engineering best practices such as modularity, continuous integration and continuous deployment (CI/CD), and embedded documentation. Create dbt models in dbt Cloud. Deploy dbt models to Amazon Redshift. Choose Test Connection.
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