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Unbundling AI — Benedict Evans

Oct 11, 2023 - news.bensbites.co
The article discusses the potential and challenges of Language Learning Models (LLMs) like ChatGPT. The author argues that while LLMs theoretically allow users to ask anything and get an answer to anything, they face issues of accuracy and the presentation of uncertainty. The author also highlights that LLMs are not databases and can only provide probable answers, not definitive ones.

The author further discusses the user interface of LLMs, comparing it to the evolution from command lines to GUIs, and suggests that LLMs might be a step forward and backward at the same time. The author concludes by suggesting that while LLMs are useful for certain tasks, their general-purpose nature and question-answer model might not be suitable for all tasks, and that specific UIs or tools might be needed to fully utilize their potential.

Key takeaways:

  • Large Language Models (LLMs) like ChatGPT have the potential to revolutionize how we interact with technology, as they can theoretically answer any question, turning a logic problem into a statistics problem.
  • However, the accuracy of these models is not binary, but probabilistic, which can lead to incorrect or misleading answers, posing a significant challenge in AI science.
  • The user interface of LLMs is another issue, as it currently operates on a question-and-answer basis, which can feel like a trial-and-error process rather than a creative one.
  • Despite these challenges, LLMs are a powerful tool that can be used for a variety of tasks, from writing code to brainstorming marketing ideas, but their full potential is yet to be realized.
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