exodus
EnvisEdge
Our great sponsors
| exodus | EnvisEdge | |
|---|---|---|
| 3 | 2 | |
| 599 | 135 | |
| 3.0% | - | |
| 7.1 | 3.5 | |
| 12 days ago | 9 months ago | |
| Python | Python | |
| GNU Affero General Public License v3.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
exodus
-
Exodus for Android: Finds trackers embedded in all your apps
It's using an external database to check your apps: https://github.com/Exodus-Privacy/exodus
-
Privacy within chess platforms? What are your thoughts?
This is the tool: https://reports.exodus-privacy.eu.org/
-
Why do you do this �
After careful review, we feel Exodus has made an error in their indication that we have 1 tracker. Other people have reported a similar error within Exodus that you can read about here. We are reporting this to Exodus but we're also going to play with our code to see if we can prevent having them issue this false-positive.
EnvisEdge
-
A new way to build decentralised recommendation engines for the creator economy
Hear me out on what I think a truly decentralised content curation.
Twitter, FB (Meta), Youtube everyone harvests user data and train their recommendation engines which are then monetised by them (often unfairly).
In the future, the data stays on the users' devices and anyone can train their models by asking the user for the consent. THe data never leaves the device and ML models get trained on user device itself. The users get to choose from a host of recommendation choices and can ask for payment in return for using their data. So no one party can build a monopoly over the platform.
Check out a cool project I have been working on to solve this https://github.com/NimbleEdge/RecoEdge
-
Ask HN: What cutting-edge technology do you use?
Edge computing for machine learning. Instead of running ML models on the cloud, I train them on user's device, ask these devices to offload computation between each other and give me the best performance out there. I have my own local cloud formed by my laptop, smartphone and ipad.
I built out the library for these myself, checkout https://github.com/NimbleEdge/RecoEdge
What are some alternatives?
tracker-control-android - TrackerControl Android: monitor and control trackers and ads.
Converter - Typescript to Scala.js converter
1Hosts - World's most advanced DNS filter-/blocklists!
privacy - Library for training machine learning models with privacy for training data
browser - The browser that fights for your privacy.
rtl-sdr-blog - Modified Osmocom drivers with enhancements for RTL-SDR Blog V3 and V4 units.
presidio - Context aware, pluggable and customizable data protection and de-identification SDK for text and images
spotlight - Deep recommender models using PyTorch.
cape-dataframes - Privacy transformations on Spark and Pandas dataframes backed by a simple policy language.
Quill - Compile-time Language Integrated Queries for Scala
App Manager - A full-featured package manager and viewer for Android
vision_ui - This is a vision-based 3d model manipulation and control UI