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Meet “Claude”: Anthropic’s rival to ChatGPT

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Re: Meet “Claude”: Anthropic’s rival to ChatGPT

#4
I just read that their chatbot will update word-by-word Slack channels, justifying the need for edits and an emoji to acknowledge the interaction is over. Why do they ensure that the appearance happens "word-by-word"? Is that a trick to reduce the response time or is that a design feature (that feels very much like a flaw to me)?

Re: Meet “Claude”: Anthropic’s rival to ChatGPT

#6

I just read that their chatbot will update word-by-word Slack channels, justifying the need for edits and an emoji to acknowledge the interaction is over. Why do they ensure that the appearance happens "word-by-word"? Is that a trick to reduce the response time or is that a design feature (that feels very much like a flaw to me)?

The response takes a long time to generate. The user could just sit there and stare at a blank response, or start reading in realtime as the response is generated.

Re: Meet “Claude”: Anthropic’s rival to ChatGPT

#7

I just read that their chatbot will update word-by-word Slack channels, justifying the need for edits and an emoji to acknowledge the interaction is over. Why do they ensure that the appearance happens "word-by-word"? Is that a trick to reduce the response time or is that a design feature (that feels very much like a flaw to me)?

The response takes a long time to generate. The user could just sit there and stare at a blank response, or start reading in realtime as the response is generated.

I find it surprising that you can display any of it before the whole thing is done, since I would expect information dependencies between the start and the finish of a sentence or paragraphs. I have yet to really look into how these models work, they are black boxes to me.

Re: Meet “Claude”: Anthropic’s rival to ChatGPT

#9

I just read that their chatbot will update word-by-word Slack channels, justifying the need for edits and an emoji to acknowledge the interaction is over. Why do they ensure that the appearance happens "word-by-word"? Is that a trick to reduce the response time or is that a design feature (that feels very much like a flaw to me)?

The response takes a long time to generate. The user could just sit there and stare at a blank response, or start reading in realtime as the response is generated.

I did not expect that, when iterating with smaller models like nanoGPT, even tough the output is one token at a time it did not felt like it would take half a second between each of them, but I guess that's what happen with billions parameters models.
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