I agree that several of OP’s examples weren’t the best, and that AGI did not arrive in 2022. However, one of the big lessons we’ve learned from the last few years of LLM advancement is that there is a rapidly growing variety of tasks that, as it turned out, modern ML can nail just by scaling up and observing extremely large datasets of behavior by sentient minds. It is not clear how much low-hanging fruit remains, only that it keeps coming.
Furthermore, when using products like Stablediffusion, DALLE, and especially ChatGPT, it’s important to note that these are products packaged to minimize processing power per use for a public that will rarely notice the difference. In certain cases, the provider might even be dumbing down the AI to reduce the frequency that it disturbs average users. They can count as confirming evidence of danger but aren’t reliable for disconfirming evidence of danger, there’s plenty of other sources for that.
I agree that several of OP’s examples weren’t the best, and that AGI did not arrive in 2022. However, one of the big lessons we’ve learned from the last few years of LLM advancement is that there is a rapidly growing variety of tasks that, as it turned out, modern ML can nail just by scaling up and observing extremely large datasets of behavior by sentient minds. It is not clear how much low-hanging fruit remains, only that it keeps coming.
Furthermore, when using products like Stablediffusion, DALLE, and especially ChatGPT, it’s important to note that these are products packaged to minimize processing power per use for a public that will rarely notice the difference. In certain cases, the provider might even be dumbing down the AI to reduce the frequency that it disturbs average users. They can count as confirming evidence of danger but aren’t reliable for disconfirming evidence of danger, there’s plenty of other sources for that.