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We love stories of dramatic breakthroughs and neat endings: The lone inventor cracks the technical challenge, saves the day, the end. These are the recurring tropes surrounding new technologies.
Unfortunately, these tropes can be misleading when we’re actually in the middle of a technology revolution. It’s the prototypes that get too much attention rather than the complex, incremental refinement that truly delivers a breakthrough solution. Take penicillin. Discovered in 1928, the medicine didn’t actually save lives until it was mass-produced 15 years later.
History is funny that way. We love our stories and myths about breakthrough moments, but oftentimes, reality is different. What really happens — those often long periods of refinement — make for far less exciting stories.
This is where we’re currently at in the artificial intelligence (AI) and machine learning (ML) space. Right now, we’re seeing the excitement of innovation. There have been amazing prototypes and demos of new AI language models, like GPT-3 and DALL-E 2.
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Regardless of the splash they made, these kinds of large language models haven’t revolutionized industries yet — including ones like customer support, where the impact of AI is especially promising, never mind general business cases.
AI for customer experience: Why haven’t bots had more impact?
The news about new prototypes and tech demos often focuses on the model’s “best case” performance: What does it look like on the golden path, when everything works perfectly? This is often the first evidence that disruptive technology is arriving. But, counter-intuitively, for many problems, we …