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New work in progress Vtuber model progress! Trying new mouth physics and face mapping plus adjusting my mouth shapes! VT: ironmouse🇵🇷😈💖 Art: Rosuuri🐰Offkai 103 Rig: Me

201,215 Aufrufe • vor 3 Monaten •via X (Twitter)

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Hello cult of Roy the Demon! tl;dr ca E3oEF6TZb5DssCqwyXRt31AUEnGqvcHeVcyGvLiqpump Over the past year I've been blessed to have my childhood character Roy the Demon go absolutely viral on social media with over 800m views. Unfortunately what came with that were many fake memecoins being made using my work and name. It honestly felt pretty weird and upsetting seeing other people profit off my art without me being involved in any capacity, not only for monetary reasons, but because my art is super important to me, and if I work on something I love to be 100% involved in all my creations. After thinking heavily on it, I decided the best move was to take ownership and control of my own work. I've been lucky to connect with some of the biggest people in the crypto space, a lot of them artists and brand builders who’ve successfully worked on their own IPs and products. Some even asked to get involved as advisors, which I'm now taking more seriously. I'm only bringing on people I trust and have similar goals in mind that I do. I’ll be launching my official token on At launch, I’ll be getting about 37.5% of the supply, here’s how that breaks down: 15% for me (artist ownership) 15% for community initiatives, in a multi-sig wallet that requires multiple people including myself to access 7.5% for potential advisors (locked for 3 months) To be clear: the content isn’t changing. That's always been the main focus of everything I've done, and it will stay that way. I'm still here to make you guys laugh every day, if anything, you’ll get even MORE content now. This token isn’t replacing that but rather giving the part of the community who has asked for an official fan token what they wanted, while shutting down randos trying to profit off my work. Huge thank you to all the teams and people who’ve sat down with me, answered my questions, and gave me guidance. I didn’t realize just how many talented artists and entrepreneurs were building in this space, and I’m excited to try something new. Appreciate you all, diem

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Colmap 4.0 was very recently released, so it inspired me to do some work to better understand it and its new capabilities with Rerun. I want to really understand how Colmap, and in particular, pycolmap, works outside of just calling it via the CLI. So my goal is to use the low-level pycolmap API to log every part of the pipeline. The explicit goal is to have an alternative to the SQLite database that I can utilize. Instead of SQLite, I want to try logging everything directly to rerun and use RRD. This means I can have deep inspectability and still save the features/matches/2D view geometry, but be able to view it directly in rerun. I think this is one of the superpowers that rerun provides; data and visualizations are deeply integrated. As I'm often working with sequential data (videos), I'm going to specifically focus on four things: 1. Monocular Video Simple: Calls high-level APIs such as pycolmap.extract_features, pycolmap.match_sequential, pycolmap.incremental_mapping. These are basically identical to the CLI options and provide a good baseline. 2. Monocular Video Streamed: Take the above high-level APIs and break them down to their iterator version, logging each component in a streamed manner. This way, I can stream the intermediate features to rerun while the extraction/matching/mapping is happening. 3. Rig with unknown calibration: <- WHAT THE VIDEO SHOWS This is probably the most interesting version and the first one I've been working on. It allows one to set a rig between known sensors, such as in VR/AR devices, leading to much better reconstructions with multiple cameras. This is the case where we don't know the calibration a priori, so we have to run a reconstruction twice: once as a normal Colmap reconstruction with no rig constraints, use this to generate the constraints, and then do it again with the newly found rig. 4. Rig with known calibration: This is the RoboCap example, where we have a pre-calibrated set of sensors, so we don't need to run the two reconstructions and also gain better matching between cameras, both spatially and temporally. Again, this leads to a much better reconstruction! Along with all this, GLOMAP has become a first-class global mapper, making it super easy to use directly within pycolmap! I'm excited to do more with this and compare it to things like pycuvslam, vipe, and other alternatives.

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introducing a new, very fun, LLM benchmark- the Game-of-Life Bench! the rules are simple: given an 8x8 grid following Conway's game of life rules, the goal is to create an initial pattern with at most 32 cells that can last the longest number of turns before dying/repeating. some results to highlight (with caveats detailed below): - gpt 5.1 lasts the longest with a 106 step run - claude models are really bad at this! they refuse to reason about this task and score < 25 points - deepseek r1 is the best open model with 102 steps. why? because i wanted to create a benchmark that has (i think) no practicality, but is still fun to look at, cheap, and still measures something interesting. i also am a big fan of the game of life. its absurdly simple rules leading to intractability is extremely cool to me. also, i saw a lot of work with LLMs trying to "predict" the next state in Conway's game of life, I think game-of-life bench is more fun because it's pretty open ended and only asks the LLM for the initial state. I also think this could be an RL env? but idk why you would ever train on this task haha i don't think this is a "serious" benchmark because it doesnt measure anything practical, but i still think it's a hard benchmark exactly because you can't predict what happens with your initial state many turns into the future; this is why i was initially expecting all LLMs to be bad at it, but turns out, some are clearly better than the others (the ordering may surprise you!) reminder: this is still a work-in-progress; (1) i am gpu-poor so could only do 10 runs for each model, even though total running cost is relatively low. maybe with some more credits i can run more seeds for each model. (2) i handpicked models which i think are at the frontier right now, plus some others that were on my mind. so, if you'd like to see a model on here, let me know. (3) i currently only do an 8x8 grid because i thought that by itself would be pretty hard for current LLMs, but of course we can increase grid sizes! (4) the coolest thing is, i dont think we can calculate the max possible number of states (yay undecidability!) you can go without repeating, so this is essentially a no-ceiling task, which is pretty cool! again, i did this mostly out of a desire to make LLMs do something fun. if this keeps me entertained for a few more days, i'd likely release a blog post on it. if it keeps me entertained for a week (and someone sponsors me), i'll put more work into it :P lastly, this is fully open sourced, so feel free to run this on your own!

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Kuromiya Lucien

15,552 Aufrufe • vor 7 Monaten

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Eleven years ago I founded my first startup. One of the first things I did was to get a desk at the startup coworking space at Google Campus in Old Street. Through that community, I met so many of the people who would shape my career and learned so much about what the startup ethos is truly about. As we have scaled Attio, we've partnered with Google Cloud to build on top of the mind blowing technologies they've created like Spanner, Colossus and Gemini to power a new generation of CRM for our customers. For all these reasons, Google is deeply woven into my startup journey and that makes today's announcement so special to me. I'm beyond excited to announce our $52 million Series B, led by Michael McBride and the GV, along with the continued support of our incredible partners from Redpoint , Point Nine , Balderton Capital and 01A. We're entering a software renaissance driven by AI and we're unbelievably excited about continuing the hard work of delivering the next generation of CRM. We're building a truly AI-native platform that can run code, integrate anywhere and bring unified context for the next generation of autonomous workflows. None of this would have been possible without the support of the more than 5,000 customers who have already chosen Attio as the backbone of their GTM stack. Your belief in our vision is what has made this possible and I can't wait to share more about some of the incredible functionality that's still to come. I'm incredibly grateful for the continued support of alex bard , Patrick Chase, Ricardo Sequerra Amram, Daniel Waterhouse and dick costolo whose belief in Attio from the earliest days has been so essential to our progress so far and to my co-founder Nicolas Sharp, for the many sleepless nights and challenging decisions that got us this far. We've got so much still to build, and we're always hiring, so if you are interested in being part of reinventing the core of the GTM stack, please take a look at For now though, it's back to building!

Alexander Christie

16,506 Aufrufe • vor 11 Monaten

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41,333 Aufrufe • vor 1 Jahr