349 karma · joined October 13, 2020
For example, you can use Sparql to perform structured queries on Wikidata (a structured database version of Wikipedia) to get well beyond unstructured documents.
Here's every person in Wikibase that was born in NYC: https://query.wikidata.org/#%23Humans%20born%20in%20New%20Yo...
I felt the pang in my bones reading this. All of us peons are just wading through this brave new world trying to do what we know is right but ultimately having no choice but to give in to life's needs.
I also like the freedom of not having to ration a daily allowance of tokens.
Would it still be justified if we replaced "taxes" with "judgement in the afterlife"?
It’s still alive. Many sites still use it. Many people still subscribe to those sites. RSS reader apps are still being created to this day.
That said I really love food. I cook all 3 types often and go out to eat all 3 types (and even regional variants) quite frequently.
By "news should be free" I think you probably mean "taxpayer funded".
95% of the time the code doesn't even build but it gets all the jigsaw pieces in place and it's a million times easier to start deleting and moving pieces around than to start from scratch.
Ranking an index is hard. It's not just BM25 or cosine similarity. How do you prioritize certain domains over others? How do you rank homepages that typically have no real content in them for navigational queries?
Changing the behavior of 90% of the non-Chinese internet is unraveling 25 years and billions of dollars spent on ensuring Google is the default and sometimes only option.
Historically, it takes a significant technological counter position or anti-trust breakup for a behemoth like Google to lose its footing. Unfortunately for us, Google is currently competing well in the only true technological threat to their existence to appear in decades.
I got a $5000 quote to fix my AC 2 summers ago and no amount of Youtube was able to help me DIY a fix.
Maybe in the long term there will be more HVAC techs than auto mechanics. Somehow I don't think that's likely.
NLP is fast but requires a model that is trained on an ontology that works with your data. Once you do, it’s a matter of simply feeling the model your bazillion CSVs and PDFs.
LLMs are slow but way easier to start as ontologies can be generated on the fly. This is a double edged sword however as LLMs have a tendency to lose fidelity and consistency on edge naming.
I work in NLP, which is the most used in practice as it’s far more consistent and explainable in very large corpora. But the difficulty in starting a fresh ontology dead ends many projects.
One day I needed to get a hotfix out to prod STAT. I pinged my manager to accept the MR and explained all the testing I've done. He said I could just accept it myself if I wanted it up now.
Turns out I've had the permission to push to prod since day one. The only red tape I had to cross was my own confidence.
It was so fast I was able to build basic collision physics of letter tiles and have their positions sync to multiple clients at once. What a shame to be killed by Google.
I haven't had a need for real time databasing since, but this is inspiring me to build another collaborative app.
It idles as an automator calendar alarm and runs on schedule like a calendar event. When a price drop is detected, it displays a notification using osascript.
When my macbook is asleep, it waits to check the price on wake.
The only input required is the URL of the product page. You can include a target price if you like.
No need to sell your soul to price tracking apps!
Mac only. Because I only use a mac.