Idiocracy prompts sarcasm - Game/Sound Design/AI Tools - https://xitter.cf/t.co/SkTZECUY3u - Ex EA,PWE/Runic/Cryptic,5PG - These are like, my opinions, man.

Sol System, Multirealmic
Joined February 2009
This may turn out to be more legendary than one may hope! Curious to see how he will group and strategize in Ashes II m.twitch.tv/wintergaming/hom…
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Excited for another look at Ashes of the Singularity II? Tune into @StarcraftWinter on Twitch where he’ll be playing with one of the games developers live at 10 PM EST Today on October 27th, 2026 twitch.tv/wintergaming
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no way... Liquid AI just released 6 open models that run locally on any device, even on your phone that means you can have your own AI for every task, fully free, with no token limits, right on your laptop or phone text, vision, voice, video, decisions, each one a specialist you can train on your own data in their tests LFM3-1.7B outran every model in its class, even ones 5x its size in theory, a model like this can do your specific job better than the newest Opus or Astra
🤝 Paid partnership
Introducing 𝙻𝙵𝙼𝟹: our new generation of Liquid Foundation Models. With a new tri-hybrid architecture and new multimodal encoders, the LFM3 family is the ideal model suite for specialized intelligence. > 6 model instances, across text, audio, vision, and omni modalities, generative and decision models. > 𝙻𝙵𝙼𝟹-𝟷.𝟽𝙱: text, 256k context window. > 𝙻𝙵𝙼𝟹-𝚅𝙻-𝟸𝙱: vision-language model with video-input support for spatial understanding > 𝙻𝙵𝙼𝟹-𝙰𝚞𝚍𝚒𝚘-𝟸𝙱: tool calls, voice chat, reasoning in 18 languages. > 𝙻𝙵𝙼𝟹-𝙾𝚖𝚗𝚒-𝟸𝙱: an omni model combines vision, audio, and language. > 𝚍𝟷-𝟸𝙱 and 𝚍𝟷-𝙾𝚖𝚗𝚒-𝟸𝙱: decision models with typed outputs and calibrated probabilities in a single pass. Omni adds audio input. > fine-tune on 1 GPU. > a new tri-hybrid architecture > architecture optimized for 14 processor classes across GPUs, CPUs, and NPUs. > 𝙻𝙵𝙼𝟹-𝚅𝙻-𝟸𝙱 is a beast. It performs competitively with Gemma 4 12B (6x larger), and Gemini 3.5 Flash Lite, and GPT-5.6 Luna, with 1.9B parameters. > 𝙻𝙵𝙼𝟹-𝟷.𝟽𝙱 is #1 on the Pareto frontier of device intelligence 𝚙𝚒𝚙𝚎𝚝𝚝𝚎.𝚕𝚒𝚚𝚞𝚒𝚍.𝚊𝚒 Every modality for specialized intelligence. Pick the one that fits your use case, customize it, and run it on-device. 1/ 🧵
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RIP to everyone who spent years learning 3D in Blender 💀 Hi3D just released an open-source model that turns any object from a photo into a full 3D model. It's trained on 2 million 3D assets, and in their technical report 90% of its models pass 3D-print slicing. Just generate the base from a photo, refine the details with Opus 5.5 and you're done. The barrier to 3D just disappeared, you can find more details in the article below:
🤝 Paid partnership
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People are building some seriously cool things with EmbeddingGemma 2 that it’s becoming hard to keep up with! The community is taking its multimodal capabilities and running with them, building everything from in-browser WebGPU photo search to native Apple Silicon acceleration. So, here’s a round up of some amazing projects 🧵👇:
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The October sale is live in the Americas Nintendo Switch eShop!🍂 Save up to 50% on multiple Pinball FX packs and almost every Pinball FX Midnight table! 🟣Pinball FX: nintendo.com/us/store/produc… 🔴Pinball FX Midnight: nintendo.com/us/store/produc…
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Someone turned the AI CEO drama into a Spanish soap opera!
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あの「ビームライフル」の音を、オシレーターとノイズジェネレーター、フィルターで再現するシンセを作りました。 音程や音色、時間変化まで自由にいじれるので、自分だけのビームライフル音が作れます。
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Today is the day you have been waiting for! Gwar's Team Antarctica Scumdogs #DLC is LIVE #PlayStation®5 (GWAR: Antarctica Scumdogs) store.playstation.com/en-us/… #XBOX Series X|S (GWAR: Antarctica Scumdogs) xbox.com/en-us/games/store/g… #Steam (Mutant Football League 2: GWAR: Antarctica Scumdogs) store.steampowered.com/app/5… #videogames #mfl #football #nfl
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I use this constantly. I run Sins of a Solar Empire simulations on my work machine from home. xitter.cf/AiClairvoyance/status/…
Do you have agents working on multiple machines? Clairvoyance makes it easy to message them regardless of location. No special setup.
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Replying to @AiClairvoyance
Nothing quite like building Mac apps, on your mac, from your PC.
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Opening shots. Both sides still have everything. Give it a minute. Wishlist Ashes 2 Now: store.steampowered.com/app/3…
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Introducing 𝙻𝙵𝙼𝟹: our new generation of Liquid Foundation Models. With a new tri-hybrid architecture and new multimodal encoders, the LFM3 family is the ideal model suite for specialized intelligence. > 6 model instances, across text, audio, vision, and omni modalities, generative and decision models. > 𝙻𝙵𝙼𝟹-𝟷.𝟽𝙱: text, 256k context window. > 𝙻𝙵𝙼𝟹-𝚅𝙻-𝟸𝙱: vision-language model with video-input support for spatial understanding > 𝙻𝙵𝙼𝟹-𝙰𝚞𝚍𝚒𝚘-𝟸𝙱: tool calls, voice chat, reasoning in 18 languages. > 𝙻𝙵𝙼𝟹-𝙾𝚖𝚗𝚒-𝟸𝙱: an omni model combines vision, audio, and language. > 𝚍𝟷-𝟸𝙱 and 𝚍𝟷-𝙾𝚖𝚗𝚒-𝟸𝙱: decision models with typed outputs and calibrated probabilities in a single pass. Omni adds audio input. > fine-tune on 1 GPU. > a new tri-hybrid architecture > architecture optimized for 14 processor classes across GPUs, CPUs, and NPUs. > 𝙻𝙵𝙼𝟹-𝚅𝙻-𝟸𝙱 is a beast. It performs competitively with Gemma 4 12B (6x larger), and Gemini 3.5 Flash Lite, and GPT-5.6 Luna, with 1.9B parameters. > 𝙻𝙵𝙼𝟹-𝟷.𝟽𝙱 is #1 on the Pareto frontier of device intelligence 𝚙𝚒𝚙𝚎𝚝𝚝𝚎.𝚕𝚒𝚚𝚞𝚒𝚍.𝚊𝚒 Every modality for specialized intelligence. Pick the one that fits your use case, customize it, and run it on-device. 1/ 🧵
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LFM3 from @liquidai is on Ollama! Small models built to run anywhere and fine-tune on a single GPU: - Text, vision, audio, omni, and decision models - Text model fits in about 1 GB at 4-bit - 256K context window Available to run locally.
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This interview with GabeN is quite interesting: “Perhaps unsurprisingly, Newell believes that LLM tools are the next great technological leap, and are going to prove so transformative that this is where people should focus their learning.“ pcgamer.com/software/ai/gabe…
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We'll see, because outside of librarian like uses, for Local AI Models, you have to use a different model to actually read, parse, adapt, utilize and put to work the data that is read from Granite models parsing it. Hard to do with just using the current Granite models. I can't go from PDF to computer use of the learned principles with one local model. Which is fine because @AiClairvoyance helps me run multiple local models to do the work anyway.
RAG is officially cooked. IBM built a retriever that hallucinates 65x less than fine-tuned RAG systems. Right now, every company is using Retrieval-Augmented Generation (RAG) to stop their AI from hallucinating. The idea is to give the AI a private database to read so it doesn't make things up. But there is a massive structural flaw. Standard RAG blindly grabs documents based on vector similarity and forces the AI to read them. If the retriever pulls irrelevant garbage, the AI doesn't stop. It just hallucinates with citations. IBM just dropped a paper that changes the math entirely. They built a new retrieval architecture that hallucinates 65x less than state-of-the-art fine-tuned RAG systems. 65x is the difference between a fun prototype and a production-grade enterprise system. Instead of blindly dumping context into the model and hoping for the best, their system actively filters and validates the retrieved data before the generation step even begins. It cuts out the noise. It forces absolute precision. For businesses, this is the holy grail. Zero hallucinations means zero liability. It means autonomous agents can finally be trusted with sensitive company data without a human babysitting every output.
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We asked everyone to join us in building open-sourced apps. Seemed fair to go first. A few of us built OPENjutsu as a side project. It’s fully open source, so it’s as much yours as it is ours. Run it on Comfy, run it locally, or plug in a paid model if you want higher quality. Your #OpenSourceHiggsfield submissions are due October 30.
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The full video is now live on @YouTube! A big thank you to @larsmoravy, @EricETesla, and the rest of the Tesla team for taking the time to walk us through the Cybercab and share the engineering, design, and technology behind it.
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A new open-source project claims to shrink vector database storage by 97% It reportedly compresses 60 million text chunks from 201 GB to just 6 GB, with no accuracy loss in its tests, running locally without a GPU or cloud infrastructure Your laptop could handle workloads that once required expensive servers Repo: github.com/StarTrail-org/LEA…
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I can't speak for this last Next Fest but I am really glad that we had Ashes of the Singularity II in the February Next Fest. It gave us so much useful feedback and allowed us to really polish and refine the game. I think we'll end up selling a lot more copies in the long term even though we pushed its release date out.
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