I hope my ai agent can learn what I like and give me suitable recommendations based on that.
Part if why ai is so overvalued is companies don’t value my time. Slop won’t fix that. I’m hooeful that ai agents allow us to filter out the junk we don’t want. No more waiting on hold. No made searching online for deals and product reviews. Just agents parsing data that we want.
For entertainment, there was a shift when we moved from broadcast to digital as we could binge and not miss episodes. The rise of reality TV muddied the waters of quality and was the equivalent of ai slop. However those that preferred, avoided it.
Of course that won’t be automatic. We’re going to need open models, open training data and a great FOSS ecosystem around personal agents. We also need to make sure that the means of compute don’t fall out of people’s hands.
I hope my ai agent can learn what I like and give me suitable recommendations based on that.
lol, no. It will learn what you like, sell that information to advertisers and governments, and then give you recommendations based on what the AI’s billionaire owners want you to watch.
Yes, with openai, or Google. That’s why I hope we can move more to FOSS agents. Currently, big tech uses our data against us to try and manipulate us.
With big data processing being more available, things like price checking and review checking can be automated. The problem is its always cat and mouse. Browser extensions started by finding you discount codes and automatically entering them. Then they started to mine your data and swap referral codes to theirs as they enshittified.
LLM’s are here to stay nut they are not groundbreaking in the way businesses hope, replacing workers. They are useful in replacing tasks. They are just not consistently good at those tasks. They shift the cognitive effort in many cases. Well, we should use them to shift the effort back onto corporations.
That’s what i told my friend when they mentioned that their clanker recommended the most expensive stuff when asked. Sure, the top result from google will be given the priority, but when parameters can sneakily be adjusted to favour people who paid them, then we will never know what being recommended is an ad or not.
Either way, you could have your own LLM agent and run it locally. That way your recommendations wouldn’t be steered towards greatest quarterly revenue. Instead, it would be something that actually serves your purposes.
Or even better, don’t be lazy and curate your own interests.
My high school motto was “Faber Quisque Fortunae” (each man creates their own destiny).
That means that You need to take responsibility for your own actions and decisions. You don’t outsource living.
Curating your own interests involves some aapect of information seeking. Llms can be used for that. It’s not a case that anyone should trust ai to make a decision. It’s that ai can help surface information to allow them to make a decision. The problem is too many people are letting the ai make a decision for them, or using it instead of other information that is better.
Either way, you could have your own LLM agent and run it locally
Ignoring everything else, that wouldn’t work. Your local llm instance, to recommend you new movies, would have to scour the internet to summarize information about them.
Boom, thats the vector of it getting steered towards greatest quarterly revenue.
Yeah that’s true. Search results, movie reviews and blogs definitely can be used to steer it in any direction. You just need to keep the LLM on a very short leash and keep a close eye on its diet. Takes some effort to do this properly.
If the goal is to say “hi, my local LLM, recommend me a new movie that I like, because god forbid I’ll take a risk and grow”, then you having to curate the data feed going into LLM to describe new movies is in practice this:
you’ll have to find sources of data (websites, threads, communicties)
verify each and everyone for poisoning BEFORE adding to your deterministic vectorization (see what Netflix did for recommendation algorithm recently) and applying custom LLM-like in architecture model.
Tl;dr;
Either you can use LLM and will be steered towards greatest quarterly revenue
OR you have to put the same effort as if reading all reviews from multiple sources by yourself
And in both cases you still end up with the same outcome “maybe you’ll like it” :P
Unless there are community based information sources. Adblock works mainly by blacklisting. Foss agents could use a combination of blacklisting and whitelisting in the same way. Yes, it takes effort, but spread over a community, it’s minimal. In the days before internet, it meant buying a magazine or newspaper. There has always been a certain amount of effort to find reviews, other than word of mouth, which will continue.
I hope my ai agent can learn what I like and give me suitable recommendations based on that.
Part if why ai is so overvalued is companies don’t value my time. Slop won’t fix that. I’m hooeful that ai agents allow us to filter out the junk we don’t want. No more waiting on hold. No made searching online for deals and product reviews. Just agents parsing data that we want.
For entertainment, there was a shift when we moved from broadcast to digital as we could binge and not miss episodes. The rise of reality TV muddied the waters of quality and was the equivalent of ai slop. However those that preferred, avoided it.
Of course that won’t be automatic. We’re going to need open models, open training data and a great FOSS ecosystem around personal agents. We also need to make sure that the means of compute don’t fall out of people’s hands.
lol, no. It will learn what you like, sell that information to advertisers and governments, and then give you recommendations based on what the AI’s billionaire owners want you to watch.
Yes, with openai, or Google. That’s why I hope we can move more to FOSS agents. Currently, big tech uses our data against us to try and manipulate us.
With big data processing being more available, things like price checking and review checking can be automated. The problem is its always cat and mouse. Browser extensions started by finding you discount codes and automatically entering them. Then they started to mine your data and swap referral codes to theirs as they enshittified.
LLM’s are here to stay nut they are not groundbreaking in the way businesses hope, replacing workers. They are useful in replacing tasks. They are just not consistently good at those tasks. They shift the cognitive effort in many cases. Well, we should use them to shift the effort back onto corporations.
That’s what i told my friend when they mentioned that their clanker recommended the most expensive stuff when asked. Sure, the top result from google will be given the priority, but when parameters can sneakily be adjusted to favour people who paid them, then we will never know what being recommended is an ad or not.
Oh boy, did that rub everyone the wrong way.
Either way, you could have your own LLM agent and run it locally. That way your recommendations wouldn’t be steered towards greatest quarterly revenue. Instead, it would be something that actually serves your purposes.
Or even better, don’t be lazy and curate your own interests.
My high school motto was “Faber Quisque Fortunae” (each man creates their own destiny). That means that You need to take responsibility for your own actions and decisions. You don’t outsource living.
Curating your own interests involves some aapect of information seeking. Llms can be used for that. It’s not a case that anyone should trust ai to make a decision. It’s that ai can help surface information to allow them to make a decision. The problem is too many people are letting the ai make a decision for them, or using it instead of other information that is better.
Most of the raw information has been deliberately obfuscated in with malicious ads.
If we were able to dismantle the toxic malicious web advertising apparatus, we wouldn’t need them. At all!
Absolutely. That’s the preferred way. Be active and put in the effort.
Ignoring everything else, that wouldn’t work. Your local llm instance, to recommend you new movies, would have to scour the internet to summarize information about them.
Boom, thats the vector of it getting steered towards greatest quarterly revenue.
Yeah that’s true. Search results, movie reviews and blogs definitely can be used to steer it in any direction. You just need to keep the LLM on a very short leash and keep a close eye on its diet. Takes some effort to do this properly.
That defeats the purpose then.
If the goal is to say “hi, my local LLM, recommend me a new movie that I like, because god forbid I’ll take a risk and grow”, then you having to curate the data feed going into LLM to describe new movies is in practice this:
Tl;dr;
Either you can use LLM and will be steered towards greatest quarterly revenue OR you have to put the same effort as if reading all reviews from multiple sources by yourself
And in both cases you still end up with the same outcome “maybe you’ll like it” :P
Unless there are community based information sources. Adblock works mainly by blacklisting. Foss agents could use a combination of blacklisting and whitelisting in the same way. Yes, it takes effort, but spread over a community, it’s minimal. In the days before internet, it meant buying a magazine or newspaper. There has always been a certain amount of effort to find reviews, other than word of mouth, which will continue.