https://thecout.com/ Recent content on Tom Ganz Hugo -- gohugo.io en-us Sat, 04 Apr 2026 22:08:13 +0100 https://thecout.com/blog/mcptooling/ Sat, 04 Apr 2026 10:00:00 +0100 https://thecout.com/blog/mcptooling/ If you let an AI agent loose on an API with 15 tools, it will eventually figure out the right sequence. But it will also try things that don’t make sense, hit errors, retry, and waste tokens doing it. The question is: can we make the API itself tell the agent what to do next? The Problem Consider an order management system. An order goes through states: pending → confirmed → shipped → delivered. https://thecout.com/blog/investmentprimer/ Sat, 04 Jan 2025 12:04:16 -0500 https://thecout.com/blog/investmentprimer/ How do we decide when to buy or sell a stock option? I’m trying to dedicate a blog post to the stuff I learned reading a few interesting papers about ML for portfolio hedging and optimization. Technical vs Fundamental analysis There are two different philosophies shared among the trader community 1. One is the Fundamental analysis that focuses on evaluating the intrinsic value of an asset based on underlying economic and financial factors. https://thecout.com/blog/dpfinetuning/ Mon, 04 Nov 2024 12:04:16 -0500 https://thecout.com/blog/dpfinetuning/ I already explained DP ML in another post 1, so this blog post covers the question, how can we design a service that lets customers finetune Large Language Models in a privacy preserving way. With the rise of data privacy laws like GDPR, DSGVO and CCPA, companies face increased scrutiny on data handling practices. The demand for privacy-preserving AI models is growing, especially in highly regulated industries. Despite this demand, many businesses lack the in-house expertise to implement their own model fine-tuning. https://thecout.com/blog/canvas/ Fri, 04 Oct 2024 12:04:16 -0500 https://thecout.com/blog/canvas/ Disclaimer: This post is more of a write-up and note-taking for my own exploration of HTML5 canvas fingerprinting and privacy-preserving techniques. How accurate are HTML5 canvas fingerprints? According to AmIUnique, only about 0.73% of users share the same canvas fingerprint as I do, highlighting its uniqueness. Canvas fingerprinting is a technique widely used in ad tracking and user identification systems and has recently been explored in risk-based authentication research 1. While there is extensive research into detecting and mitigating canvas fingerprinting, few studies have examined just how privacy-invasive these techniques are in practice. https://thecout.com/blog/backdoor/ Fri, 19 Apr 2024 12:04:16 -0500 https://thecout.com/blog/backdoor/ The xz backdoor I think everyone heard from the very recent xz library backdoor. In short, malicious code has been silently introduced in the official repository of this compression library. It then uses rtld-audit to add an audit hook and listen to dynamic linking events. In particular, OpenSSH on some distributions use xz for compression purposes and, as a result, loads xz. Please refer to 1 for more information about the backdoor. https://thecout.com/blog/virscan/ Tue, 04 Oct 2022 12:04:16 -0500 https://thecout.com/blog/virscan/ Lately I came across an interesting paper where the authors use Reinforcement Learning (RL) to obfuscate malicious Portable Executable (PE) files to evade detection by antivirus (AV) scanners. The authors use actions as, for instance, random byte padding, packing the binary, adding benign strings to the .text section, modifying timestamps, adding function imports, etc… to obfuscate the binary file. After applying these actions, the modified PE file will be checked against an AV to see if the detection rate decreases. https://thecout.com/blog/dp/ Mon, 14 Sep 2020 12:04:16 -0500 https://thecout.com/blog/dp/ In this post, I want to briefly introduce Differential Privacy to you, which, in my honest opinion, needs to get more attention in the software developer community. During my Master thesis, I evaluated the use of Differential Privacy for Federated Learning (I might explain Federated Learning in another post). The Theory Differential Privacy, originally $\epsilon$-Differential Privacy (DP)1, is a way to secure the privacy of individuals in a statistical database. A statistical database is a database, where only aggregation functions like “sum”, “average”, “count”, et cetera… can be executed. https://thecout.com/blog/3dgan/ Fri, 04 Sep 2020 12:04:16 -0500 https://thecout.com/blog/3dgan/ Did you ever wonder what it would look like if we combine a chair and an airplane? Turns out it doesn’t look that good. Before we get to this Chairplane, lets first outline this post’s topic: I am going to demonstrate you some possibilities of an 3D Generative Adversarial Network. That is: A GAN not applied to images, but to 3D Voxel objects. But what is a GAN? A GAN consists of two deep neural networks that try to game each other.