🤝 The hidden data in every photo you share
Dear curious mind,
With this newsletter issue, I'm announcing a significant change in direction. Moving forward, this newsletter will focus primarily on privacy-friendly open models that you can self-host, rather than the cloud-based solutions from major players like OpenAI, Anthropic, Google, and xAI. While I'll continue to monitor developments from these companies, covering everything has become unsustainable, as mentioned in previous issues. My primary interest lies in using AI models with my personal data and private files, which are information I prefer not to share with third parties. I believe that in a future where AI assistants will know countless details about our lives, running models ourselves offers greater control and privacy than giving all our data to large corporations. Although we haven't yet reached this ideal state of personal AI, now is the perfect time to prepare.
In summary, future newsletters will emphasize open-source developments and models you can run locally on your own devices, helping you prepare for a future where you can maintain privacy while benefiting from AI that truly understands your needs.
In this issue:
💡 Shared Insight
Visual Privacy in an AI World: How Immich Self-Hosting Protects What Google Photos Exposes
📰 AI Update
QAT: The Training Technique That Makes AI Models 4x Smaller Without Sacrificing Quality
🌟 Media Recommendation
My Favourite Sources for Big AI News
💡 Shared Insight
Visual Privacy in an AI World: How Immich Self-Hosting Protects What Google Photos Exposes
As you might know, I'm a strong advocate for personal knowledge management (PKM). One of my habits is saving interesting articles to my "Read it Later" app rather than consuming them immediately. This creates a pool of content that sometimes gets rediscovered by chance rather than being treated as a to-do list.
This exact scenario happened recently with an eye-opening article from Heise (in German) about how much information is encoded in the images we share online. Ex Google employee Vishnu Mohandas created the web service They See Your Photos which uses Google's Vision API to demonstrate what companies can extract from a single uploaded image - from your social status to brand preferences and other valuable marketing data.
While writing this article, I discovered a recent trend about AI's location-finding abilities. A TechCrunch report highlighted a concerning feature where users leverage ChatGPT's latest models (o3 and o4-mini) to perform "reverse location searches" from photos. These advanced models can analyse uploaded images to identify locations with remarkable accuracy. Users are instructing the AI to identify cities, landmarks, restaurants, and bars from subtle visual clues in photos. The privacy implications are significant.
These revelations made me think deeper: if this much information can be derived from one image, what insights could be extracted from someone having access to all of my photos?
Like many others, I've been sharing my entire photo library with Google through their Photos service. Reading these articles and reflecting on my Google Photos usage sparked a pivotal change in my approach. I remembered that years ago, a friend had recommended Immich to me - an open-source alternative to Google Photos. I had tried other services in the past (LibrePhotos, PhotoPrism), but none did truly convice me.
This time, I decided to give Immich a proper chance, and I'm thoroughly impressed. The face recognition is remarkably accurate, and installation was straightforward using a Docker container on my modest home server that already runs multiple other services.
I liked Immich so much that I've already stopped uploading new photos to Google Photos. I initiated a data takeout, downloaded 90 gigabytes of photo and video data, and added it all to Immich. Despite this substantial library, the service remains responsive and fast on my setup.
A Reddit post captured my experience perfectly:
I finally decided to install it though Docker (documentation is great and simple for beginners) and I am completely blown away. It is not just a good Google Photos replacement, in some aspects, it goes beyond. The interface is extremely familiar to anyone who has used Google Photos. Face recognition is eerily accurate and the mobile app is exceptionally good.
The privacy benefits cannot be overstated. Self-hosting through Immich puts you entirely in control of your own photo and video data. No one has access to the data you upload to your Immich server. In today's world, where privacy concerns are increasingly relevant, using Immich returns control of your visual memories to you.
It's worth noting that self-hosting does require some technical knowledge. Immich isn't for everyone, as it comes with the learning curve of setting up and maintaining your own server. However, with enough research into open-source software and hosting - and AI assistants can help troubleshoot any setup issues you encounter - anyone can take advantage of what Immich has to offer.
My photos are now automatically backed up whenever I'm connected to my home Wi-Fi and my phone is charging. It's a liberating feeling knowing my visual memories are securely stored on my own server rather than in a corporate cloud.
📰 AI Update
QAT: The Training Technique That Makes AI Models 4x Smaller Without Sacrificing Quality [Google for Developers blog]
Google's Quantization-Aware Training (QAT) improves upon existing quantization techniques for Gemma 3 models. While quantization has long been used to reduce memory requirements of AI models, Google's approach enhances results by incorporating quantization information during the training rather than only after completion. This method simulates low-precision operations during training, preparing the model for better compression and reducing performance degradation. You can test the official QAT models and other quantizations already in Ollama and LM Studio.
🌟 Media Recommendation
My Favourite Sources for Big AI News
As announced in the introduction of this issue, I'll be shifting the focus of this newsletter to open models that you can operate without sharing your personal information to cloud-based services. I believe these privacy-friendly alternatives are crucial for the future of personal assistants, which need to know everything about me to be as helpful as possible. To give you alternatives to stay up-to-date with big AI news, I share my favourite AI news sources that have stood the test of time over the past two years.
Bens Bites
What started as one of the first daily AI newsletters has evolved into a comprehensive weekly overview covering all major AI developments. Bens Bites excels at summarizing important news while also highlighting interesting and viral articles from across the AI landscape, making it an efficient weekly read. Furthermore, he is a valuable source if you are into building apps with AI as a non-technical person.
ThursdAI
This weekly podcast began as audio-only but has expanded to include video, broadcasting live on YouTube every Thursday. The hosts not only cover major AI news, but frequently invite the developers behind open-source models and tools for in-depth discussions. They also offer a written newsletter summary of the weekly conversation.
Every
Though this is a paid newsletter, they offer many free issues. Rather than just reporting news, Every produces longer, thoughtfully researched articles that explore individual topics in detail. Their writing offers more in-depth analysis and fresh perspectives that go beyond surface-level reporting.
One Useful Thing
Business professor Ethan Mollick shares weekly essays with his insights on AI developments. He often receives early access to new models and tools, allowing him to prepare detailed articles for release days. His completely free content offers longer, thoughtful reads that provide valuable context and analysis.
All of these news sources have larger audiences than mine, and I receive no benefits or compensation for recommending them. They've simply proven their value to me over time, and I believe you might find them equally worthwhile as you navigate the rapidly evolving AI landscape.
Disclaimer: This newsletter is written with the aid of AI. I use AI as an assistant to generate and optimize the text. However, the amount of AI used varies depending on the topic and the content. I always curate and edit the text myself to ensure quality and accuracy. The opinions and views expressed in this newsletter are my own and do not necessarily reflect those of the sources or the AI models.
Great thoughtful post thanks. When you say home server? Does this have an offsite backup? And self hosting, there is opportunity to do this in the cloud. Do you have any recommendations on where to start? Appreciate that there will be cost with this.