ep_jhu

(2025)

See also related: https://news.ycombinator.com/item?id=45467500

This HN thread called it hours before this Reuters report

https://news.ycombinator.com/item?id=47602019

My wife and I quit our tech jobs and moved from the US to a European country last year to learn/grow/explore. The plan is to renew the visa and continue our exploration.

For 2026, other than more traveling, I have just started a course at the local tech university on solar power, and asset management/O&M of solar installations. The hope is to gain basic domain knowledge for potentially transitioning my career into this field in a year or two, taking advantage of my SWE, data analytics, and PM experience.

I'm also planning to take my host country's driving exam. That means I first need to learn how to drive a car with manual transmission, after 30+ years driving in the US.

Nice! I like that it moves things to the recycling bin rather than straight up deleting them. Also, the filtering is great. I wish Apple included that in the OSX (Storage > Messages) or iOS (Storage > Review Large Attachments) UIs. It seems like a must-have.

Everyone here is thinking about privacy and surveillance and here I am wondering if this is what lets us speed up nano cameras to relativistic speeds with lasers to image other solar systems up close.

My COVID project was DCSkyCam[1], which is on a Pi4 with the HQ camera to do sunrises/sunsets, and uses TFLite and other packages for object detection and identification of helicopters that fly by. I also have a Pi 3B running pihole[2] and running custom scrape jobs to alert me of certain website updates, which I’d like to transition to using selenium but the 3B is too slow for chromedriver - might upgrade to a Pi 5 if I can.

[1] https://dcskycam.net [2] https://pi-hole.net/

One issue I always run into when implementing these approaches is the embedding model's context window being too small to represent what I need.

For example, on this project, looking at the generation of training data [1], it seems like what's actually being generated are embeddings on a string concatenated from each review, title, description, etc. [2]. With the max_seq_length set to 200, wouldn't lengthy book reviews result in the book description text never being encoded? Wouldn't this result in queries not matching against potentially similar descriptions if the reviews are topically dissimilar (e.g., discussing author's style, book's flow, etc. instead of plot).

[1] https://github.com/veekaybee/viberary/blob/main/src/model/ge... [2] https://github.com/veekaybee/viberary/blob/main/src/model/ge...

In 1966 NASA launched two rockets to LEO as part of the Gemini 12 mission - under 2 hours apart (Gemini, Athena docking target.)

As for SpaceX, just a few months ago the Psyche asteroid mission and a Starlink launch also happened the same day.

There’s already been hacks with 100k user account data leaked: https://www.bleepingcomputer.com/news/security/over-100-000-...

OpenAI says it was an issue with the user devices not their service, though.

For my DCSkyCam project, htop shows 1.8 load average on my Pi 4B. It's always busy, with resources left to handle spikes based on what the camera detects (or post to mastodon/website). I'd say it's right-sized. Best part - not throttled, even without a case, fans, or even heatsinks. That probably wouldn't be the case with a Pi 5.

The account I use for my @dcskycam Twitter bot has been locked a few times for posting sunset videos flagged as inappropriate and the account itself was “permanently suspended for repeated violations” only to be un-suspended almost immediately.

This is just a hobby project for me but if it was revenue generating I’d be looking for other platforms rather than starting new projects on such an unstable platform!

Not to hijack the OP, but yes, my Twitter bot actually tweets spots to his bot. My DCSkyCam data this helps train his models, but another objective for me was to learn image ML techniques, so I’m using all my own data/models.

This is great! I've done something similar, but to detect helicopters and tweet them to a local copter spotting group: https://twitter.com/dcskycam/with_replies

I also use the Pi+HQ Cam, but with their wide-angle lens, and I do all the object detection (and heli type classification for a handful of types) on-device using TFLite.

How do you not run up a Rekognition bill?! One of my project goals was to have the total cost be as low as possible, so while I do use AWS for the website hosting (S3+R53+CF) it's $0.60/mo - everything else is on-device. With Rekognition, processing a file every 2 seconds, it would add up!

I'm running a Twitter bot that tweets out sunrise/sunset timelapses, and also does on-device object detection and classification to tweet out helicopters that fly by the field of view.

https://twitter.com/dcskycam/with_replies

It's a Pi 4B with the HQ Cam (6mm lens). The ML models are trained on my MBP, converted to tflite, and run on the pi itself.

The main use case is the timelapses, but after seeing that that most of the helicopters that flew by weren't transmitting ADSB, I figured I could help out the @helicoptersofdc crowdsourcing project (run by someone else) by contributing heli spots in an automated manner that might otherwise go unreported.

I also have a 3B+ running pihole on the LAN.

The “long tail” you mention reminds me of the “dead internet” conspiracy theory.

https://www.theatlantic.com/technology/archive/2021/08/dead-...

I wonder if anyone can quantify and keep trends through time of an estimated percentage of auto-generated/bot content, at least for major domains.

Check out Shoutcast Server. They have a basic offering up to 12k listeners. Should require minimal client work.