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gfrangakis

103 karma · joined March 28, 2014

CTO @ Mira
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gfrangakis··on OpenArch – PyTorch implementations of modern LLM architectures
Really cool. I know the sauce is in the layers and weights, but its kind of mind blowing how short / simple the implementations are
gfrangakis··on Light Pollution Map
What is this random spot with seemingly nothing around it in Russia?

https://www.lightpollutionmap.info/#zoom=5.85&lat=68.2729&lo...

gfrangakis··on Morrowind rebooted the original Xbox
That blew my mind as well. I remember it looking so good.

Xbox - 64mb

Xbox 360 - 512mb

Xbox One - 8 GB (later 12 GB)

Xbox Series X - 16 GB

This last one also surprises me, was expecting at least 32GB

gfrangakis··on One Year Alone in Forest of Sweden Building a Log Cabin
Managed to make it through without being attacked by a single greyling. Quite the accomplishment
gfrangakis··on The Bit Short: Inside Crypto’s Doomsday Machine
On the other hand, some people want Bitcoin to succeed so much - or rather want the price of Bitcoin to succeed because they speculate on it - that they'll engineer some fraudulent schemes in a relatively unregulated market to support their bank accounts.

I think it's likely a bit of both, but you can't deny there is something unsavory going on with Tether and these offshore exchanges

gfrangakis··on Show HN: Amplication – Instantly Generate Node.js Apps with GraphQL and REST API
I had seen this a while ago but should take a fresh look at it - it seems like there should be a community tool that generates data providers from an openapi spec. Thanks!
gfrangakis··on Show HN: Amplication – Instantly Generate Node.js Apps with GraphQL and REST API
I believe so - basically following the vanilla SQLAlchemy integration guide they have [0], and not trying to await query results as they do in the the async guide [1]

[0] https://fastapi.tiangolo.com/tutorial/sql-databases/ [1] https://fastapi.tiangolo.com/advanced/async-sql-databases/

gfrangakis··on Show HN: Amplication – Instantly Generate Node.js Apps with GraphQL and REST API
I'm curious - is there a tool handles solely the "frontend codebase generation" part of this? This looks great, but we already have a well-defined backend and REST API built using Python+FastAPI, with SQLAlchemy as an ORM and Postgres backing it. I am not a good UI/UX designer, but I understand and have built React applications, so really find myself looking for something that can take an OpenAPI.json spec and produce a hackable frontend codebase that follows best practices.
gfrangakis··on Museum of Bad Album Covers
If you had a chuckle at Immortal's Battles in the North album cover, please watch the video for The Call of the Wintermoon [0], which was on their first album, Diabolical Fullmoon Mysticism. I'm convinced they knew it was hilarious

[0] - https://www.youtube.com/watch?v=-VBdAY8eA9w

gfrangakis··on Hackers take over prominent Twitter accounts in simultaneous attack
Everyone say a prayer for Twitter engineers trying to fix this tonight
gfrangakis··on Full Autopilot in GTA Using TensorFlow
Seems like Forza would be easier to interface with too, example: this guy built a virtual cockpit[0] using VW parts -- the shifter, tach/speedometer all work

[0] - https://www.youtube.com/channel/UCSEqO_2kdxLtslBK9FLqtxA

gfrangakis··on How Stripe Designs Websites (2017)
The most impressive thing about Stripe's website is IMO their documentation. I've tried to replicate it using tools like widdershins and slate, but can't get it as beautiful or functional.
gfrangakis··on It takes now 53 weeks salary to earn same as 30 weeks in 1985
> 10/ When we say "inflation-adjusted wages look good," we are actually saying "if you could take your wage back to 1970 and spend it, you'd be better off than you were at the time with a 1970 wage." I mean, maybe that's interesting. But it doesn't describe lived experience.

Isn't more like saying, you can buy more units of 2020 "consumer goods" with a 2020 wage than you could buy 1970 consumer goods with a 1970 wage? His point is just the definition of inflation: $1,000 in nominal dollars more valuable in 1970 than in 2020.

gfrangakis··on Big Calculator: How Texas Instruments Monopolized Math Class
Why have no edtechs created a low cost version of the TI-83/84? One that mirrors the functionality of the TI calcs so that they can still be used with textbooks that are dependent on those. The article estimates the TI's cost $15-20 to make, but even that seems very high for what they are.

I imagine the harder part is getting approval from the organizations that administer standardized tests like College Board and the states themselves.

gfrangakis··on Stripe CLI
Is Stripe's "documentation stack" open-source? I've seen Slate and its derivatives, but honestly nothing really comes close to the full (amazing) dev experience their docs provide.
gfrangakis··on This Cat Does Not Exist
Dear god what have we done https://i.imgur.com/OanNO7W.jpg
gfrangakis··on Tile38 – Realtime geofencing and geospatial index, v1.11.0
S2 can also output interior coverings, which will return only the cells in a covering that are fully contained in a polygon. So if you encounter a point (or any cell) whose parent is in an interior covering, you don't have to do any additional checks to produce an exact result (whereas on the boundary, you may want to do a point-in-polygon test to be exact).
gfrangakis··on How We Built Uber Engineering’s Highest Query per Second Service (2016)
Library also available in Java[0] and to an extent in Golang[1], though the latter is incomplete.

S2 is fantastic for geofencing. Arbitrary regions can be covered by a set of S2 cells of varying level. A point (lat/lon) can be converted to a S2 cell of the smallest level (around a cm^2 of area on the sphere). Checking to see if one S2 cell is contained in another amounts to searching an integer range, since all children of a given S2 cell have IDs that fall within a fixed ranged. See also [2]

[0] https://github.com/google/s2-geometry-library-java

[1] https://github.com/golang/geo

[2] http://blog.christianperone.com/2015/08/googles-s2-geometry-...

gfrangakis··on How We Built Uber Engineering’s Highest Query per Second Service (2016)
A must-read followup that explores other data structures for geofencing:

https://medium.com/@buckhx/unwinding-uber-s-most-efficient-s...

gfrangakis··on New York Subway X-Ray Area Maps
It's the gray platform that intersects the middle of the 456 and the end of the NQRW