AI Repo: google-research/timesfm

Skyler: Hey everyone, and welcome back to Git News A I! I'm your host Skyler, and I'm absolutely pumped to dive into today's trending A I repositories with you. Before we jump in, I want to give a quick shout out to our sponsor LimitLess A I - they're doing some incredible work in the A I space, so definitely check them out. Today we're covering some seriously cool repos, from Google's new time series foundation model to some leaked system prompts that'll blow your mind, plus some amazing tools for free Claude access and computer vision workflows. Skyler: Let's kick things off with something really exciting from Google Research - TimesFM, which stands for Time Series Foundation Model. This is Google's take on creating a pretrained foundation model specifically for time series forecasting, and honestly, it's about time we had something like this. With over thirteen thousand stars already, this repo is getting massive attention from the M L community. What makes TimesFM special is that it's designed to handle time series data the same way that large language models handle text - it's pretrained on a huge variety of time series data and can then be fine-tuned or used zero-shot for your specific forecasting tasks. If you're working on anything involving predictions over time - whether that's stock prices, energy consumption, user behavior, or really any sequential data - this could be a game changer. The fact that it comes from Google Research means it's built on solid theoretical foundations, and the Python implementation makes it accessible for most developers. This is definitely one to bookmark if you're doing any kind of predictive analytics work. Skyler: Now, here's something that's going to make you go "whoa" - we've got a repo called system prompts leaks that's absolutely exploding with over thirty-six thousand stars. This repository is basically a treasure trove of extracted system prompts from all the major A I models - we're talking ChatGPT, Claude, Gemini, Grok, Perplexity, you name it. These are the behind-the-scenes instructions that tell these models how to behave, and seeing them is like getting a peek behind the curtain of how these systems actually work. What's fascinating is how different companies approach system prompting - some are incredibly detailed and specific, while others are surprisingly simple. If you're building A I applications or just curious about how these models are guided to behave the way they do, this repo is absolutely fascinating. It's being updated regularly too, so you can see how these prompts evolve over time. Fair warning though - once you start reading through these, you'll probably lose a few hours just exploring how different the approaches are across different models. Skyler: Speaking of Claude, let's talk about free-claude-code, because this one's a real gem for developers who want to use Claude's coding capabilities without breaking the bank. This Python-based tool gives you free access to Claude Code right in your terminal, as a VS Code extension, or even through Discord. With almost fifteen hundred stars and growing, it's clear that developers are loving this approach. What I really appreciate about this project is how it democratizes access to one of the best coding A I assistants out there. Whether you're a student learning to code, working on open source projects, or just want to experiment with Claude's coding capabilities before committing to a paid plan, this tool has your back. The recent updates show they're actively maintaining it and fixing installation issues, which is always a good sign. If you've been curious about Claude's coding abilities but haven't wanted to pay for access, definitely check this one out. Skyler: Next up is GLM-OCR from the zai organization, and this one's hitting all the right notes - accurate, fast, and comprehensive optical character recognition. With over five thousand stars, this Python-based O C R solution is making waves in the computer vision community. What sets GLM-OCR apart is its focus on that trifecta of accuracy, speed, and comprehensiveness. Most O C R solutions force you to pick two out of three, but GLM-OCR is trying to nail all three. The recent activity shows they're actively working on pipeline reconstruction and stream parsing improvements, which suggests they're really focused on making this production-ready. If you're working on document processing, data extraction from images, or any kind of text recognition tasks, this could be exactly what you need. The fact that it's comprehensive means it's probably handling multiple languages and various document types, which is crucial for real-world applications. Skyler: Finally, let's talk about Supervision from Roboflow, and wow - thirty-seven thousand stars tells you everything you need to know about how valuable this project is to the computer vision community. Their tagline says it all: "We write your reusable computer vision tools," and they're absolutely delivering on that promise. Supervision is essentially a toolkit that handles all those tedious but essential tasks you need for computer vision projects - annotation processing, dataset management, visualization, evaluation metrics, you name it. What I love about this project is that it's solving the "plumbing" problems that every computer vision developer faces, so you can focus on the interesting stuff instead of reinventing the wheel. The recent updates show they're fixing memory usage issues and improving annotation handling, which are exactly the kinds of optimizations that matter when you're working with large datasets. If you're doing any computer vision work, whether it's object detection, image segmentation, or any other visual A I task, Supervision should definitely be in your toolkit. Skyler: That's a wrap on today's trending repositories! Thanks again to our sponsor LimitLess A I for making this show possible - seriously, go check out what they're building. Don't forget to subscribe to Git News A I if you haven't already, and as always, you can find all the links to today's repositories in the show notes. Until next time, keep coding and keep exploring the amazing world of A I!