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Divinity video game from Larian - may use AI trained on own assets and to help development
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<blockquote data-quote="Umbran" data-source="post: 9836810" data-attributes="member: 177"><p>How about a couple of more basic arguments:</p><p></p><p>1) Efficiency, in and of itself, is not of value. Only with a plan to usefully use the savings does it become valuable. If you don't plan what to use it for, you will waste it anyway.</p><p></p><p>2) Generative AI, in general, has not been shown to raise overall efficiency. The folks who produce genAI <em>say</em> it will increase efficiency, and will show you things like time-to-task-completion metrics to support that assertion. But they studiously avoid showing you what happens in the rest of the workflows the AI work is associated with.</p><p></p><p>Commonly, the generative AI content goes into the workflow, and then in one way or another requires editing and revision that wipes away the savings in that task-completion time. This is often most obvious in AI generated code, or technical writing - the coding task is completed quickly, but the code is fragile, or difficult to maintain, and breaks later, increasing cost in fixing regression defects than it originally saved.</p><p></p><p>This leads to how only about 5% of enterprise-level generative AI projects end up delivering the expected value to the company that uses it.</p></blockquote><p></p>
[QUOTE="Umbran, post: 9836810, member: 177"] How about a couple of more basic arguments: 1) Efficiency, in and of itself, is not of value. Only with a plan to usefully use the savings does it become valuable. If you don't plan what to use it for, you will waste it anyway. 2) Generative AI, in general, has not been shown to raise overall efficiency. The folks who produce genAI [I]say[/I] it will increase efficiency, and will show you things like time-to-task-completion metrics to support that assertion. But they studiously avoid showing you what happens in the rest of the workflows the AI work is associated with. Commonly, the generative AI content goes into the workflow, and then in one way or another requires editing and revision that wipes away the savings in that task-completion time. This is often most obvious in AI generated code, or technical writing - the coding task is completed quickly, but the code is fragile, or difficult to maintain, and breaks later, increasing cost in fixing regression defects than it originally saved. This leads to how only about 5% of enterprise-level generative AI projects end up delivering the expected value to the company that uses it. [/QUOTE]
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Divinity video game from Larian - may use AI trained on own assets and to help development
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