The Great Disconnect: Why Talking to Machines Still Feels Like Talking to Machines
Author(s): MKWriteshere
Originally published on Towards AI.
From Clippy to ChatGPT: The Thirty-Year Quest to Solve AI’s Hardest Problem
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In 1995, Gartner published its first “Hype Cycle” report — a visual representation of how technologies evolve from innovation to widespread adoption. Right at the top of this inaugural curve, at the “Peak of Inflated Expectations,” sat “Intelligent Agents.” Three decades later, we’re still riding this rollercoaster of anticipation and disappointment with AI assistants.
Imagine the journey as a dramatic mountain trek: enthusiastic climbers rush up the slopes of hype, tumble down into the “Trough of Disillusionment,” then gradually ascend the “Slope of Enlightenment” toward the “Plateau of Productivity.” This is precisely the path AI assistants have followed multiple times.
Few developments have experienced as many ups and downs as artificial intelligence assistants. From the much-maligned Clippy to the sophisticated ChatGPT, we’ve witnessed these digital helpers ride waves of hype only to crash against the shores of reality.
Yet with each cycle, they’ve grown more capable, inching ever closer to the science fiction dream of a truly intelligent digital companion.
Let’s unpack this fascinating evolution and understand why contextual reasoning remains the final frontier for AI.
Cast your mind back to 1997. Microsoft Office users were suddenly introduced to an animated… Read the full blog for free on Medium.
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