OpenAI has released ChatGPT as a research preview. Its conversational interface lets non-specialists draft, summarise, brainstorm and work with code, turning large language models from a specialist topic into a general-purpose business tool.
The underlying capability is not new to anyone who has been paying attention. What is new is that you no longer need to be paying attention. That is usually the moment a technology starts to matter commercially, and it is a different moment from the one the research community would pick.
The business thought
The near-term advantage is not replacing everyone. It is compressing routine knowledge work: the drafting, summarising and rearranging that occupies a great deal of the working day without being the point of anyone’s job.
The durable opportunity lies in combining models with proprietary workflow, data, distribution and human review, rather than merely wrapping a public chatbot. A wrapper is a feature and it will be competed away. What is defensible is whatever the model cannot get to on its own.
The practical watch
Treat output quality, privacy, copyright, security and auditability as product requirements rather than afterthoughts. Each is capable of stopping a deployment on its own, and none of them get easier by being deferred.
Test a narrow workflow against time, quality and error-rate baselines before rolling anything across a company. The error rate is the one people skip, and it is the one that decides whether the time saved is real.
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Source: OpenAI, Introducing ChatGPT.