The article discusses the author's positive perspective on AI as a tool for generating text and code, contrasting it with Glyph's negative experiences. The author emphasizes the utilitarian nature of AI outputs, particularly in coding, and notes that their understanding and skill in utilizing AI tools have led to significant improvements in results. While Glyph’s critique reflects a lack of positive experiences and highlights a need for data, the author maintains a cautious optimism about AI's potential efficacy in practical applications like coding.
My experiences of genAI are all extremely bad, but that is barely even anecdata. Their experiences are neutral-to-positive. Little scientific data exists. How to resolve this?
I see a lot of potential in AI. That hasn't always been my stance, and I intend to remain critical, but right now I'm quite positive about its usefulness.
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