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> I want to be clear that I'm not against these tools generally. I use them myself
No essay is made worse by being stripped of filler. If the reader has got this far, this sentence is entirely redundant, I think.
Being forced to use them to continue to have an income is causing me a cognitive dissonance and a level of stress that is surely going to kill me though. I strongly resent the fact that I've been backed into this corner where my choice is to swallow my principles or throw away a career I've worked half my life on
Anti AI: It’s inevitable and I hate it
Oh no. They’re converging. But I guess that just proves the point doesn’t it.
I spent an hour debugging my networking setup and I just turned on voice mode and used ChatGPT to help me figure out why everything was working except my networking equipment wasn't changing IP addresses when I set it. As it answered my questions, it gave thoughtful answers and explained everything along the way to the point where I started to guess that I needed to upgrade my control plane, and lo and behold, that was the answer. If I had to peruse through links just for the false idea that I would be getting a cognitive benefit, I might have spent 4x the amount of time or given up.
I'm very happy that we are living in an where we can get reliable answers immediately and move on to what we want to do.
An extreme example, but what happens if Bob Nottechnical follows GPT instructions which happen to include `sudo rm -rf /`? How would Bob know to stop trusting the instructions when every time he's followed things before it worked as expected?
So for now I'm doing both. A bit search and a bit AI.
There was a point, perhaps about five years ago, where using Google had become a genuinely frustrating hurdle I needed to overcome to do the actual work. Now the frustration is completely gone.
It was not, and at least because it was obviously wrong I clicked through to a page with the real UV index.
But had it said "The UV index is 1.7" I might have believed it, but it'd still have been wrong, potentially dangerously so.
Now to be clear, live data is precisely the sort of thing I expect it to get wrong, and I never intended to trigger let alone read an "AI summary", but it's still worrying for those less inclined to dismiss it.
Can't trust anything anymore these days.
Proving that search hasn't stopped making us think at all. Just like we've had to do with humans since the dawn of time, we continue to have to think hard about how our intent will be interpreted.
Ironically, Googles AI overview often links to references that state the polar opposite of what the AI overview claims.
Half the time it just describes some unrelated shit. Maybe it’s interesting but totally sidetracks your search.
IMO it’s like Google 15 years ago where it was causing more panic and disinformation but people knew it back then - we laughed at Google’s persistent and incorrect diagnoses.
Now though, with boomers and young Gen Y and older Gen Z - maybe the dumbest yet most confident people alive it’s causing a lot of harm. Everyone thinks they know everything and because they inherit from their parents and are basically rich society rewards them for being retarded
What's worse, when reading the Google outputs, I have learned to ignore almost any website besides a select few, one of which is Reddit. Which is very weird thinking about it, but it worked in the past.
If I had tried to find an authoritative source I might have spent a minute on it. Would it have killed me? No. Would I do that for something more life-threatening? Of course. But flash results are... fine, for 90% of what I search for.
Obviously not a silver bullet - for example, not much help if you're looking for modern tooling-related stuff - but I've found it really useful as a way of reading up on fundamentals.
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Fundamental learning path does not change. Whatever searche result force feeds you it's ok. So long as you have a critical thinking mindset.
People simply read titles, and oh that's what happened.
If you apply the first order thinking, you can spot most of mistakes in docs and results. But then you gotta move onto the second order thinking to see if the conclusion you came up with will be good for the future.
Say, you searched for how to build a house yourself.
You see an AI result that recommends contractors.
But if you break it down why AI recommended the contractor, you can see harness (assumptions) such ass security (the builder/searcher should not be harmed), convinience (how fast do you need) without regards to your personal needs. - that's why comapnies want so much of your info, so they can try to guess better output based on your needs.
Now you breakdown using the 1st principle, you find out that you don't want those assumed AI answer, and you ask more direct question and guide it.
But then after applying the 2nd order principle, you might buy into the AI's recommendation that you don't want to spend too much time building one yourself for the safety (you are a pro athelet, who should not do heavy labor for the sake of the next game match).
Anyways, consider multiple thinking models and views.
Searches propagate between nodes, nodes specialize on specific sections of the index, which can be random + user preference (maximizing redundance and availability for the things people actually care about).
Soulseek already gets like halfway there and it's not even trying to be. How hard could it be?
There were essentially two main ways of doing P2P search: flooding and Distributed Hash Tables (DHT). Flooding is exactly how it sounds: you flood a query across the whole network. The most popular applications like Limewire, Kazaa etc were flooding based, and as you can imagine, didn’t scale well. I recall some stories of havoc on networks due to the amount of traffic they generated. However they were simple and allowed somewhat complex queries, because each node basically ran a brute force search on its local index.
On the other hand, DHTs organize nodes in a distributed index structure such that queries can be routed in a deterministic manner, typically in O(logN) hops. DHTs were basically the granddaddies of distributed NoSQL DBs like DynamoDB and Cassandra.
So you can already see the limitations of DHTs: they need keys to be indexed, typically keywords. You had to pick a small handful of keywords for it to be manageable. This inherently limits the complexity and scale of the queries.
Both had an existential problem with spam. There were essentially no defenses against bad actors poisoning the network with spam and malware. It was a huge unsolved problem until Bitcoin popularized proof of work (which had been suggested in various forms before, but Bitcoin was the first practical, robust application.)
And neither could approach the sophistication of Google, which could extract very high quality signals from their centralized troves of data to refine and rank results.
Personally though I think the time is ripe for a renaissance. Spam and bad actors are still existential problems, but with vectors / embeddings the discovery aspect could be addressed. It occurs to me that the most popular large scale vector search mechanism is HNSW networks, which seem pretty amenable to P2P networks…
https://yacy.net/
[0] https://yacy.net/index.html
Or, in a more simple sense it’s entirely Google’s fault
I bet a large number of them run Google ads.
As such, it is not in Google's best interests to cut them out of search, regardless of how low quality they are.
It is well known that Google and SEO have a wink wink / nudge nudge relationship where Google "hides" its search algorythm, and somehow the websites with the most ads get closer to the top every year.
Is there a lot of additional secret sauce that made google work well in its prime?
The AI thing is poor as well, because it makes things up and changes context all the time.
Now when I am looking for information on this or that I'm obliged to append reddit, Wikipedia or YouTube in my search to hope to have something with real content (and I hate watching videos to be kept informed and I feel there is more and more LLM generated content there also).
I even have a subscription to chatgpt now that I use more and more as a replacement for a Google search, or at least as a supplement.
I don't like it very much because in the best case I have only a handful of sources that it selected instead of being able to look by myself at all the possible sources, but it is still better than spending hours finding something that is not SEO-slop.
I'm convinced it will never improve because it helps google and the others push their AI stuff, and they desperately need it to justify the billions poured in it, but also because it gave them a much deeper control on what is provided to the users.