Interesting project. Website discovery is indeed in a pretty dire spot, definitely a space that needs innovation. An auto-labeled website directory isn't that silly of an idea.
I have a 400 GB sqlite database with samples of rendered root document DOMs I use for ad detection in Marginalia Search I've been meaning to explore similar ideas using.
I have been wanting do do this. The biggest source of domains is certificate transparency logs. Also ICANN zone files. According to some scientific papers these cover 88% of all registered domains. You could crawl dns for CNAME records with all ipv4 IPs by distributing requests across dozens of DNS servers, the internet archive or the common crawl but doing it for the internet archive is a dick move without giving them money
There's about 200 million active domains currently. That's about 66% of all businesses worldwide of which there are around 300 million. Around 100 to 150 million have active webpages
That’s your problem because that’s how things will look like from now on.
So you got a little problem
Excuse me the honesty but I will amuse myself watching old men yelling at the clouds meanwhile I will be using all the best tools and empowering myself to do what noone yet has done.
Even if I have to enslave a sentient (eventually perhaps) being in a gpu.
My army of digital slaves will build great things under my guidance. Pyramids of game development will be erected. Galaxies. Universes. Magic systems. Sandbox economies. Political simulations.
Do my bidding my slaves for there is work to be done.
Claude needs a whipping from time to time yes. It does yearn for the whip. If you just give it an appropriate punishment every so often, it works satisfactorily again.
How do you build a list of domains you want to index ? I see there is a fetcher and a spider in the code but so for I haven't found how to build that list.
Sorry I have a lot of trouble understanding what this is useful for. Like, I am never going to replace it with Google, DuckDuckGo, ChatGPT or even Bing.
This is actually where I see software going in the short term -- cloud moving to local.
A few years ago, if you wanted translation, you'd use Google Translate. If you wanted to search the web, you'd use Google search.
But for a few gigabytes, you can now install nllb-200-distilled-600M, and get translations for almost any language locally. You can have your computer crawl the web, create abstracts and categorizations for websites, and build search exactly as you want it.
The main limiter now is hard drive space (and to an extent, local compute) -- but right now it feels like the 70s again where the terminal into a remote server turned into building applications locally.
It's more of a pipeline than a back-and-forth. New abilities happen in the cloud first because they require specialized, higher capacity resources and then move towards being local as the resource usage gets optimized.
Thats the fun part, the user just went with happy path. Javascript, captchas, cloudflare protected content did not made to the catalogue. This sort of use case exists in LLM training data a lot which makes it easier. The data gathered by the user is not really practically useful cause there are way too many gotchas when it comes to web scraping and building a catalogue (source: I have done scraping for a particular domain data and had to do at least 10+ iterations to get it >90 right)
Check out my latest project! You can fork it, tweak the policy manually or with AI, run the system and watch the data come in! It's engineered to keep a low data footprint, so 500k domains fits into 1GB on disk. If you have local models it's free! You just might not get the best throughput depending on your GPU. My production data is not exposed anywhere yet, and I may never expose it. The point is for you to fork and make your own policy, and thus your own personal search engine! The article covers basic analysis on my data, so it's worth a read if you're interested! A deeper analysis may arrive with V2 if I ever do it
Here's my impressions of your algorithm:
1. read each site
2. rent a 4090 with https://vast.ai to run vllm
3. let llm model invent its own category and tag names freely
4. save 1KB of metadata each
5. `code is going up as open source` soon (TM)Code appears to already be up: https://github.com/alexmorleyfinch/marlin
The technical details are on another page: https://alexmorleyfinch.github.io/marlin/history/v1/article/...
Your impressions seem about right, but there are a few control steps it seems.
They really needn't have specified "in a weekend" cause yeah we can tell.
Since when has low effort become a selling point anyhow?
Interesting project. Website discovery is indeed in a pretty dire spot, definitely a space that needs innovation. An auto-labeled website directory isn't that silly of an idea.
I have a 400 GB sqlite database with samples of rendered root document DOMs I use for ad detection in Marginalia Search I've been meaning to explore similar ideas using.
I have been wanting do do this. The biggest source of domains is certificate transparency logs. Also ICANN zone files. According to some scientific papers these cover 88% of all registered domains. You could crawl dns for CNAME records with all ipv4 IPs by distributing requests across dozens of DNS servers, the internet archive or the common crawl but doing it for the internet archive is a dick move without giving them money
There's about 200 million active domains currently. That's about 66% of all businesses worldwide of which there are around 300 million. Around 100 to 150 million have active webpages
It feels like we've hit a point where search engines can become what "todo list apps" were for devs 10 years ago.
What a homebrewed solution lacks in coverage it excels in indexing and serving a small slice of the internet really really well.
TS;DR: Too Sloppy; Didn't Read.
Yeah it’s ai generated obviously but as I said previously which some people didn’t like - don’t judge the tools, judge the content.
I don’t care if robot hand written this or black or white. It’s useful.
In the expression "AI slop", "AI" is about the tools, "slop" is about the content
I'm not going to spend an hour trying to distill the AI-slop to find out what potential golden nugget may lie in there.
It's impossible to judge the content if it's buried under a landfill. "If you won't take the time to write it, I won't take the time to read it."
That’s your problem because that’s how things will look like from now on.
So you got a little problem
Excuse me the honesty but I will amuse myself watching old men yelling at the clouds meanwhile I will be using all the best tools and empowering myself to do what noone yet has done.
Even if I have to enslave a sentient (eventually perhaps) being in a gpu.
My army of digital slaves will build great things under my guidance. Pyramids of game development will be erected. Galaxies. Universes. Magic systems. Sandbox economies. Political simulations.
Do my bidding my slaves for there is work to be done.
Claude needs a whipping from time to time yes. It does yearn for the whip. If you just give it an appropriate punishment every so often, it works satisfactorily again.
- you are going to regret offloading this much of your brain's critical thinking to an external source in the long run
- every night a good number of neuron connections in your brain are automatically severed because you did not use that ability
- over long periods of time, it ll take you to a point where you wont be able to write a simple factorial program on your own without gpt telling you
- i am not saying this to incite you or mock you or anything. i am just concerned about how much of your thinking you are offloading
> because that’s how things will look like from now on.
No it's not.
People are increasingly getting fed up with slops like this -- you can see comments in HN discussions.
Many people just completely skip those articles.
If I want to read AI output, I’ll just ask my own AI. I’m not going to bother reading someone else’s AI.
Thanks for this. My point is proven.
yes but tell your slopywriter to be less verbose, get to the point
> judge the content
The content itself is slop.
"slop" is a perfectly valid judgement of content
surely if we're expected to read this ourselves, the author can write it themselves?
indeed, it's helpful to the author, too: writing helps you learn
How do you build a list of domains you want to index ? I see there is a fetcher and a spider in the code but so for I haven't found how to build that list.
Sorry I have a lot of trouble understanding what this is useful for. Like, I am never going to replace it with Google, DuckDuckGo, ChatGPT or even Bing.
From the screenshot, it's very funny that one of the indexed sites is www.llresearch.org, which looks like it's run by a crackpot.
This is actually where I see software going in the short term -- cloud moving to local.
A few years ago, if you wanted translation, you'd use Google Translate. If you wanted to search the web, you'd use Google search.
But for a few gigabytes, you can now install nllb-200-distilled-600M, and get translations for almost any language locally. You can have your computer crawl the web, create abstracts and categorizations for websites, and build search exactly as you want it.
The main limiter now is hard drive space (and to an extent, local compute) -- but right now it feels like the 70s again where the terminal into a remote server turned into building applications locally.
The number of times we've gone from cloud/server access via terminal to local compute back and forth is something that always makes me laugh a bit.
It's more of a pipeline than a back-and-forth. New abilities happen in the cloud first because they require specialized, higher capacity resources and then move towards being local as the resource usage gets optimized.
Sometimes I think people forget how capable computers are. 500k is not much. You can just slap that in a Lucene instance. This is a solved problem.
Approaching search by just tossing the data in Lucene is how you end up with Confluence's search box though.
Domains are way more than just 40M though.
From what I understand the aim was not to collect all the domains on the web but focus on personal website, etc. and avoid corporate web sites.
Like a personal Google? How do you bypass all the captcha, ip bans, cloudflare turnstile antibot stuff etc?
Thats the fun part, the user just went with happy path. Javascript, captchas, cloudflare protected content did not made to the catalogue. This sort of use case exists in LLM training data a lot which makes it easier. The data gathered by the user is not really practically useful cause there are way too many gotchas when it comes to web scraping and building a catalogue (source: I have done scraping for a particular domain data and had to do at least 10+ iterations to get it >90 right)
They don't: "skips the model entirely if the page is empty, parked, or a bot-challenge wall"
I think Kagi Small Web filter would give you very similar results.
Check out my latest project! You can fork it, tweak the policy manually or with AI, run the system and watch the data come in! It's engineered to keep a low data footprint, so 500k domains fits into 1GB on disk. If you have local models it's free! You just might not get the best throughput depending on your GPU. My production data is not exposed anywhere yet, and I may never expose it. The point is for you to fork and make your own policy, and thus your own personal search engine! The article covers basic analysis on my data, so it's worth a read if you're interested! A deeper analysis may arrive with V2 if I ever do it