However, rapid progress in AI revealed a different niche where Fleet fits much more naturally.I don't understand what this rapid progress is people keep talking about.
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However, rapid progress in AI revealed a different niche where Fleet fits much more naturally.
I don't understand what this rapid progress is people keep talking about. They added a bunch of tokens to the training to invoke external applications whose response is pasted into the context and call it "agentic". Wow, big deal. -
However, rapid progress in AI revealed a different niche where Fleet fits much more naturally.
I don't understand what this rapid progress is people keep talking about. They added a bunch of tokens to the training to invoke external applications whose response is pasted into the context and call it "agentic". Wow, big deal.@volpeon no but it's different and better and will finally let execs replace the pesky workers with robots!!!
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However, rapid progress in AI revealed a different niche where Fleet fits much more naturally.
I don't understand what this rapid progress is people keep talking about. They added a bunch of tokens to the training to invoke external applications whose response is pasted into the context and call it "agentic". Wow, big deal.What has changed since the Transformer paper which is the foundation for current LLMs? Some technological improvements to lower resource usage and improve response quality, which while nice doesn't really lead to practical changes for users. You still use it in the exact same way. The rest are adjustments to the training process which brought us "chain of though" and "agentic AI". That's fucking it. If anything, I'd expect more to happen with all the money getting pumped into it.
