2 ms·

How do you propose you would train it to know what you want? Besides a versioned system prompt that you (or the AI) would have to continually adjust.

no_wizard 1y ago
I don't think this leaves out initial setup. Another source of information: habit observation. If I do something around the same time every day, over and over again, it would be nice if it simply helped me along unless I interrupt explicitly. It should fine tune itself to observations it makes about my behavior and patterns, as opposed to me interjecting constantly The constant need to query for information, rather than have useful information contextually pushed to me, fundamentally limits its utility once the novelty wears off. Without a sufficient complexity threshold (and this assumes accurate information and trust) its more work to query for things than it is to simply do them. From a consumer perspective, thats not great.
netsharc 1y ago
If you had a butler or PA who's with you all the time, they would know what genre of food you like based on your restaurant visits and your ravings about what you liked. The imaginary AI would have your location history for restaurant visits, your Instagram feed for pictures of foods/review of restaurants, your chat history to see what you've raved about. It would also have big data from other people who have seemingly similar tastes to you, to recommend you the next place to eat. Obviously since we're in lage-stage capitalism and everything is designed to extract profit out of you, we can't give commercial systems all our private data...
chipotle_coyote 1y ago
If it gathers enough data on you, it can theoretically figure that out. Siri "Suggestions" have been around for years, and if you go to the same place frequently on certain days/times (e.g., your workplace, a friend you visit every Saturday, places you often go to lunch) or use the same apps at similar days/times (e.g., pulling up Callsheet in the evening when you're watching TV shows or movies to do TMDB lookups), those suggestions will show up. All of those examples are real ones I've experienced. The quality is certainly variable, but it's decent. (Of course, it's "non-LLM" AI, which isn't particularly fashionable right now, but if we really want smarter AI agents we need to stop treating all problems as solvable with large language models.)

no_wizard 1y ago

I don't think this leaves out initial setup. Another source of information: habit observation. If I do something around the same time every day, over and over again, it would be nice if it simply helped me along unless I interrupt explicitly. It should fine tune itself to observations it makes about my behavior and patterns, as opposed to me interjecting constantly The constant need to query for information, rather than have useful information contextually pushed to me, fundamentally limits its utility once the novelty wears off. Without a sufficient complexity threshold (and this assumes accurate information and trust) its more work to query for things than it is to simply do them. From a consumer perspective, thats not great.

netsharc 1y ago

If you had a butler or PA who's with you all the time, they would know what genre of food you like based on your restaurant visits and your ravings about what you liked. The imaginary AI would have your location history for restaurant visits, your Instagram feed for pictures of foods/review of restaurants, your chat history to see what you've raved about. It would also have big data from other people who have seemingly similar tastes to you, to recommend you the next place to eat. Obviously since we're in lage-stage capitalism and everything is designed to extract profit out of you, we can't give commercial systems all our private data...

chipotle_coyote 1y ago

If it gathers enough data on you, it can theoretically figure that out. Siri "Suggestions" have been around for years, and if you go to the same place frequently on certain days/times (e.g., your workplace, a friend you visit every Saturday, places you often go to lunch) or use the same apps at similar days/times (e.g., pulling up Callsheet in the evening when you're watching TV shows or movies to do TMDB lookups), those suggestions will show up. All of those examples are real ones I've experienced. The quality is certainly variable, but it's decent. (Of course, it's "non-LLM" AI, which isn't particularly fashionable right now, but if we really want smarter AI agents we need to stop treating all problems as solvable with large language models.)