If the postwar computer scientists who conceived of AI had chosen a different name such as ‘applied statistics’, we would be spared a lot of confusion
Network room at a Google data centre: Social media has been flooded with screenshots of Overview’s unhinged responses to innocuous search terms. Photograph: Google
But then I started using an app that employed machine learning to convert recorded speech into text. The thing was surprisingly accurate and efficient, and I was impressed by its ability to automate a process I found incredibly dull and time-consuming. It wasn’t perfect; it struggled with strong accents, and muffled words, and it often made completely stupid errors for no obvious reason – but then, so did I, and it took me a lot longer to make them.
Ken Early: Germany cannot solve the nation’s problems but they can bring a moment of happiness‘Our mental health is completely destroyed. We are living in constant sadness’ But the usefulness of this software hints at some of the ways in which the Large Language Model technology it’s based on has been wildly oversold. As a speech-to-text transcription tool, it does a modest and narrowly delineated thing extremely well. It generates a primary text based on recorded speech, and secondary texts – the bullet-point outline and the longer summary – based on an automated analysis of the primary text.
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