I have spent the past several years building AI into products where a wrong answer has a price attached: an AI-powered payroll compliance platform for the Australian market, where an error lands in someone's bank account, and a college admissions product, where a poor match can shape a student's next four years. The question that decided the architecture was the same in both. How far should the language model be allowed to go before something deterministic takes over? One in five U.S. payrolls…
This article has been indexed from Unite.AI