AI newsThe story, in brief
Are better models better?
Your AI model is 'better.' But better at what? The gap between model improvements and real-world answers is wider than you think.
The KeyNews take
Why it matters
As AI models improve incrementally each week, leaders are confusing capability gains with business value. This piece challenges the assumption that better model performance translates to better outcomes, especially for factual/deterministic questions—a critical blind spot for enterprises betting on AI ROI.
The key facts
3 to knowWeekly model improvements are not translating to better answers on deterministic questions
Models struggle with 'right answers' vs. 'better answers' distinction
Implications for enterprise AI deployment and expectation-setting
Go to the source
Benedict Evansben-evans.com
Publisher excerpt: Every week there’s a better AI model that gives better answers. But a lot of questions don’t have better answers, only ‘right’ answers, and these models can’t do that. So what does ‘better’ mean, how do we manage these things, and should we change what we expect from computers?
