How much human oversight does an AI system actually need?
This question gets answered with philosophy a lot more often than it gets answered with an actual plan. Here is a more useful, and much less abstract, way to think about it.
This question gets answered with philosophy a lot more often than it gets answered with an actual plan. Here is a more useful, and much less abstract, way to think about it.
The AI demos that get the most applause in a boardroom are usually the ones that end up abandoned within a year. The systems that actually stick around are the boring ones nobody brags about.
For years, talking to an AI on the phone felt like talking to an AI on the phone. That has genuinely changed recently, and the reason has less to do with the models getting smarter and more to do with a few unglamorous engineering problems finally getting solved.
Every few months someone announces the hallucination problem is basically solved. It is not, and treating it as a bug to eliminate instead of a property to design around is why so many AI projects quietly stall.
Everyone calls their product an AI agent now, even the ones that are just a chatbot with a new label. Here is a plain explanation of what actually separates a real agent from a chatbot wearing an agent costume.
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