Research shows Google collects 20x more data from Android than Apple collects from iOS. Block this non-consensual telemetry using pihole blocklists.

Overview

pihole-antitelemetry

Research shows Google collects 20x more data from Android than Apple collects from iOS. Block both using these pihole lists.

Project Goals and FAQ

The purpose and goals of this blocklist are outliined in the FAQ

The lists

For a list of domains that should not break anything, use telemetry-domains.txt.

If you want to also block domains that are not well-tested, add telemetry-domains_beta.txt to the list.

Domains that are known to break user-facing services or apps are moved to telemetry-domains_borked.txt for use at your own risk.

These lists are maintained with help from the community. Any efforts to help sort domains into the correct blocklists will help others better block non-consensual telemetry.

Existing lists

Owner
Adrian Edwards
Adrian Edwards
Training deep models using anime, illustration images.

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[AI6101] Introduction to AI & AI Ethics is a core course of MSAI, SCSE, NTU, Singapore

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An implementation of the paper "A Neural Algorithm of Artistic Style"

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UWA System Health Lab 0 Jun 04, 2021
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ADGAN - The Implementation of paper Controllable Person Image Synthesis with Attribute-Decomposed GAN

ADGAN - The Implementation of paper Controllable Person Image Synthesis with Attribute-Decomposed GAN CVPR 2020 (Oral); Pose and Appearance Attributes Transfer;

Men Yifang 400 Dec 29, 2022
source code for 'Finding Valid Adjustments under Non-ignorability with Minimal DAG Knowledge' by A. Shah, K. Shanmugam, K. Ahuja

Source code for "Finding Valid Adjustments under Non-ignorability with Minimal DAG Knowledge" Reference: Abhin Shah, Karthikeyan Shanmugam, Kartik Ahu

Abhin Shah 1 Jun 03, 2022
Free-duolingo-plus - Duolingo account creator that uses your invite code to get you free duolingo plus

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This is the code for Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning

This is the code for Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning It includes /bert, which is the original BERT repos

Mitchell Gordon 11 Nov 15, 2022
Implementing Graph Convolutional Networks and Information Retrieval Mechanisms using pure Python and NumPy

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Noah Getz 3 Jun 22, 2022
Implementation and replication of ProGen, Language Modeling for Protein Generation, in Jax

ProGen - (wip) Implementation and replication of ProGen, Language Modeling for Protein Generation, in Pytorch and Jax (the weights will be made easily

Phil Wang 71 Dec 01, 2022
Code for paper entitled "Improving Novelty Detection using the Reconstructions of Nearest Neighbours"

NLN: Nearest-Latent-Neighbours A repository containing the implementation of the paper entitled Improving Novelty Detection using the Reconstructions

Michael (Misha) Mesarcik 4 Dec 14, 2022
Code accompanying "Adaptive Methods for Aggregated Domain Generalization"

Adaptive Methods for Aggregated Domain Generalization (AdaClust) Official Pytorch Implementation of Adaptive Methods for Aggregated Domain Generalizat

Xavier Thomas 15 Sep 20, 2022
SafePicking: Learning Safe Object Extraction via Object-Level Mapping, ICRA 2022

SafePicking Learning Safe Object Extraction via Object-Level Mapping Kentaro Wad

Kentaro Wada 49 Oct 24, 2022
The code for two papers: Feedback Transformer and Expire-Span.

transformer-sequential This repo contains the code for two papers: Feedback Transformer Expire-Span The training code is structured for long sequentia

Facebook Research 125 Dec 25, 2022
PyAF is an Open Source Python library for Automatic Time Series Forecasting built on top of popular pydata modules.

PyAF (Python Automatic Forecasting) PyAF is an Open Source Python library for Automatic Forecasting built on top of popular data science python module

CARME Antoine 405 Jan 02, 2023
YOLOv2 in PyTorch

YOLOv2 in PyTorch NOTE: This project is no longer maintained and may not compatible with the newest pytorch (after 0.4.0). This is a PyTorch implement

Long Chen 1.5k Jan 02, 2023
(ICCV 2021 Oral) Re-distributing Biased Pseudo Labels for Semi-supervised Semantic Segmentation: A Baseline Investigation.

DARS Code release for the paper "Re-distributing Biased Pseudo Labels for Semi-supervised Semantic Segmentation: A Baseline Investigation", ICCV 2021

CVMI Lab 58 Jan 01, 2023