5,043 karma · joined December 9, 2009
http://nyaruka.com/
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I think you are setting far too high a bar with "majority of information worker tasks". My wild ass guess is that with some thoughtful design and focus as it stands today GPT-4 could do 25% of tasks (or make workers 25% more efficient). The economic impacts of that are vast and I'm not particularly optimistic about who will benefit most from them. That's what the fuss is about IMO, not that we have some kind of AGI on our hands, which is far too high a bar.
This is a very convenient position to take for white men in power. Now we insist it must be a perfectly level playing field, never mind the centuries of racism.
Having some compassion for people losing their jobs isn't uncalled for. Especially when the same is going to start happening with programmers soon.
EVs aren't the best road trip vehicle but that's ok, I don't road trip every day. They absolutely are the best 99% daily vehicle though if you have home charging.
Nothing is the best at everything, the EV compromise is pretty darn acceptable though. (that said, PHEVs with 80 miles of range would be even better)
One possible conclusion might be that the only thing keeping GPT algos from going full AGI is a loop and small context windows.
The thing to remember is that GPT has no state apart from the context, so it can't "remember" anything apart from what's in the text. That doesn't mean it shouldn't be able to stay consistent in a guessing game but it does mean it can't keep secrets.
Some of that can be solved with layers above GPT where say it it told it can save "state" that isn't passed on to the human but fed back in to generate the next response. But the size of that context is very limited. (a few thousand words)
There seem to be a fair number of experiments playing with giving GPT this kind of long term memory, having it establish goals then calling it over and over as it accomplishes subgoals to try to work around those limitations.
As someone not skilled in this art, is there anything preventing us from opening that context window many orders of magnitude? What happens then? And what happens if it is then "thinking in text" faster than we can read them? (with an intent towards paper clips)
This is a genuine question, I'm not trolling.
I have been skeptical about all this, but decided to play with using ChatGPT for coding a task I had. It wasn't perfect, either in workflow or in final results but what was clear was that not adopting it will very quickly make you lag behind your peers.
I think the additive bonus is especially high for senior devs who are fast, in that those will be faster in grokking the generated code and better at guiding it to the right solution.
I guarantee you that in five years anybody who cares at all about their productivity will be using it constantly in their workflow, probably much sooner.