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LLM impact seen in specialized tool creation, not direct problem-solving

作者 PulseAugur 编辑部 · [2 个来源] ·

The primary impact of large language models (LLMs) is expected to stem from their ability to assist humans in creating specialized tools, rather than directly solving problems. This perspective shifts the focus from what LLMs can do independently to the potential of human-LLM collaborative systems. The discussion emphasizes the creation of tailored solutions through this partnership. AI

影响 Focuses on the future application and impact of LLMs, offering a perspective on their role in tool creation and human-AI collaboration.

排序理由 The cluster consists of opinion pieces discussing the potential impact of LLMs.

在 Mastodon — sigmoid.social 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

报道来源 [2]

  1. Mastodon — sigmoid.social TIER_1 English(EN) · [email protected] ·

    Yes. I suspect the biggest impacts of LLMs won't come from a workflow "problem -> #LLM produces solution," but from "problem -> LLM helps create specialised too

    Yes. I suspect the biggest impacts of LLMs won't come from a workflow "problem -> #LLM produces solution," but from "problem -> LLM helps create specialised tools -> solution." Asking what LLMs can or can't do is IMHO far less interesting than asking what human-LLM systems might …

  2. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    Yes. I suspect the biggest impacts of LLMs won't come from a workflow "problem -> #LLM produces solution," but from "problem -> LLM helps create specialised too

    Yes. I suspect the biggest impacts of LLMs won't come from a workflow "problem -> #LLM produces solution," but from "problem -> LLM helps create specialised tools -> solution." Asking what LLMs can or can't do is IMHO far less interesting than asking what human-LLM systems might …

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