Y
HN Search
Hacker News Search
new
|
comments
|
top
|
jobs
Xyra
searching PlanetScale…
1.
▲
2.
▲
3.
▲
4.
▲
5.
▲
6.
▲
7 ms
·
1.
▲
by
Xyra
7d ago
good idea, I emailed them. And no search engine, only Scry or direct web fetch of an URL in a Scry result or from the agent's memory.
2.
▲
by
Xyra
7d ago
thank you!
3.
▲
by
Xyra
8d ago
let me know if it was faster and more compositionally expressive than you expected
4.
▲
by
Xyra
8d ago
thanks, I try
5.
▲
by
Xyra
8d ago
Good point, fixed
6.
▲
by
Xyra
8d ago
Hi, yes. New users right now get free credit. When the server isn't burdened, queries are currently ~free (under $.01 per second, when most are well under a second). We're just trying to learn here how to use this thing productive
7.
▲
by
Xyra
8d ago
that's a good idea. it's very doable
8.
▲
Show HN: Scry, programmable internet search w/ congestion pricing
(scry.io)
3 points
by
Xyra
9d ago
|
0 comments
9.
▲
by
Xyra
1mo ago
thanks. I'm still sorting out pricing. I don't have experience with B2B and am interested in empowering out-of-distribution people, so will likely maintain some free tier + congestion-based auction pricing for non-commercial use.
10.
▲
by
Xyra
1mo ago
I've been working on grep.it.com. can currently grep over 200 TB of the internet
11.
▲
by
Xyra
1mo ago
hi, i've been working on this, grep.it.com. (i found your comment with it)
12.
▲
by
Xyra
3mo ago
making the internet sql queryable, crawling, cleaning, indexing, embedding many sources into source-aware schemas, solving contention problem with free-floating pricing. Currently crawling over 1M records/sec. software is still in alph
13.
▲
by
Xyra
9mo ago
Hetzner, Postgres, Rust, SvelteKit
14.
▲
by
Xyra
9mo ago
What did you think?
15.
▲
by
Xyra
9mo ago
emailed you, and it's https://venmo.com/u/XyraSinclair .
16.
▲
by
Xyra
9mo ago
We can iterate fast with understanding useful paradigms of vector manipulation. Yesterday I added `debias_vector(axis, topic)` and l2_normalization guidance.
17.
▲
by
Xyra
9mo ago
Thank you! I got the idea December 3, and initially released it December 19.
18.
▲
by
Xyra
9mo ago
I'm raising at least $175k and doing a serious startup.
19.
▲
by
Xyra
9mo ago
Thanks, that's very interesting.
20.
▲
by
Xyra
9mo ago
~300 token chunks right now. Have other exciting embedding strategies in the works.
21.
▲
by
Xyra
9mo ago
The scale is there. I'm scraping, cleaning, token efficientizing dozens of sources every single hour. The lack of monies for embedding everything was a temporary problem.
22.
▲
by
Xyra
9mo ago
in the direction of "empowering the public with new capabilities they didn't have before", Scry offers, with the copy and paste of a prompt and talking with an agent: 1) Full readonly-SQL + vector manipulation in a live publi
23.
▲
by
Xyra
9mo ago
Thank you! I'll be getting millions more quality, embedded documents, it'll be here just getting more useful.
24.
▲
by
Xyra
9mo ago
Thank you!
25.
▲
by
Xyra
9mo ago
You submit a SQL query to periodically run, we run it and store the results. As we ingest more documents (dozens of sources are being ingested every day), we run it again. If there's different outputs, you get an email.
26.
▲
by
Xyra
9mo ago
Maybe more actually, server costs and API credits for my agent-coordination research are expensive.
27.
▲
by
Xyra
9mo ago
Exactly, people want precision and control sometimes. Also it's very hard to beat SQL query planners when you have lots of material views and indexes. Like this is a lot more powerful for most use cases for exploring these documents th
28.
▲
by
Xyra
9mo ago
Thank you, I've started ingestion operations of pubmed.
29.
▲
by
Xyra
9mo ago
What is hyperbole? We are collectively experiencing a software intelligence explosion (people are shipping good software at prolific rates now due to Opus 4.5 and GPT-5.2-Codex-xhigh). With Scry, you can run arbitrary SELECT SQL statements
30.
▲
by
Xyra
9mo ago
I've since improved it, and also discovered a new method of vector composition I have added as a first-class primitive: debias_vector(axis, topic) removes the projection of axis onto topic: axis − topic * (dot(axis, topic) / dot(t
More ›