https://en.wikipedia.org/wiki/Doomsday_argument
Statistically, we're most likely to be born when the world population is at its peak.
Readit Newsgregw134 commented on Deaths are projected to exceed births in 2031 cbo.gov/publication/61390... · Posted by u/johntfella
gregw134 commented on GLP-1s are breaking life insurance glp1digest.com/p/how-glp-... · Posted by u/alexslobodnik
They aren't even that awful in maintenance -- just expensive. The unpleasant part is when you're increasing the dose. After a while at the same dose, it's more or less unnoticeable IMO.
Unnoticable meaning doesn't have any effect at all, or just no bad side effects?
gregw134 commented on I decided to pay off a school’s lunch debt huffpost.com/entry/utah-s... · Posted by u/dredmorbius
Source? I don't see any mention of that here: https://help.kagi.com/kagi/search-details/search-sources.htm...
Search "chili recipes" on bing. Now search kagi or any other alternative search engine. They all show the exact same recipes because they're using the bing API.
I've always been somewhat opposed to this, because there's already like 10 different search alternatives, and now AI is taking over, which will further weaken their grip.
Google is on top because they do the best job; I use Yandex primarily, but I switch back to google all the time for coding related questions. In terms of advertising, there's billions of views on Facebook/Instagram/X to get, in addition to all the other sites. I get they're a big player, but I worry we're just beating Google because they're down, not because it's good for the consumer.
There's really only one alternative, Bing. Virtually all the other western search engines are using the Bing api, and just slightly modify the results.
I was the first employee at a company which uses RAG (Halcyon), and I’ve been working through issues with various vector store providers for almost two years now. We’ve gone from tens of thousands to billions of embeddings in that timeframe - so I feel qualified to at least offer my opinion on the problem.
I agree that starting with pgvector is wise. It’s the thing you already have (postgres), and it works pretty well out of the box. But there are definitely gotchas that don’t usually get mentioned. Although the pgvector filtering story is better than it was a year ago, high-cardinality filters still feel like a bit of an afterthought (low-cardinality filters can be solved with partial indices even at scale). You should also be aware that the workload for ANN is pretty different from normal web-app stuff, so you probably want your embeddings in a separate, differently-optimized database. And if you do lots of updates or deletes, you’ll need to make sure autovacuum is properly tuned or else index performance will suffer. Finally, building HNSW indices in Postgres is still extremely slow (even with parallel index builds), so it is difficult to experiment with index hyperparameters at scale.
Dedicated vector stores often solve some of these problems but create others. Index builds are often much faster, and you’re working at a higher level (for better or worse) so there’s less time spent on tuning indices or database configurations. But (as mentioned in other comments) keeping your data in sync is a huge issue. Even if updates and deletes aren’t a big part of your workload, figuring out what metadata to index alongside your vectors can be challenging. Adding new pieces of metadata may involve rebuilding the entire index, so you need a robust way to move terabytes of data reasonably quickly. The other challenge I’ve found is that filtering is often the “special sauce” that vector store providers bring to the table, so it’s pretty difficult to reason about the performance and recall of various types of filters.
What would you recommend for billions of embeddings?
gregw134 commented on Jeep owners fed up with in-car pop-up ads kbb.com/car-news/jeep-own... · Posted by u/spudlyo
> Last year, Ford filed a patent for an in-car advertising system that would use the car’s speakers and display screen to serve ads to drivers and passengers
I've owned Ford stock for 10 years, I think I'll finally sell it today
gregw134 commented on When imperfect systems are good: Bluesky's lossy timelines jazco.dev/2025/02/19/impe... · Posted by u/cyndunlop
As a systems enthusiast I enjoy articles like this. It is really easy to get into the mindset of "this must be perfect".
In the Blekko search engine back end we built an index that was 'eventually consistent' which allowed updates to the index to be propagated to the user facing index more quickly, at the expense that two users doing the exact same query would get slightly different results. If they kept doing those same queries they would eventually get the exact same results.
Systems like this bring in a lot of control systems theory because they have the potential to oscillate if there is positive feedback (and in search engines that positive feedback comes from the ranker which is looking at which link you clicked and giving it a higher weight) and it is important that they not go crazy. Some of the most interesting, and most subtle, algorithm work was done keeping that system "critically damped" so that it would converge quickly.
Reading this description of how user's timelines are sharded and the same sorts of feedback loops (in this case 'likes' or 'reposts') sounds like a pretty interesting problem space to explore.
Would you be willing to share more about how you guys did click ranking at Blekko? It's an interesting problem.
Australia's land tax system makes it effectively impossible for large corporations to own large chunks of residential property, but our real estate is amongst the world's most expensive and landlords are still awful - it's just that the landlords are hundreds of thousands of dentists and, yes, software engineers rather than corporate entities.
If you want housing to be cheaper and renters to be better treated, increase supply. Everything else is window-dressing.