Alternatives
Products that do what Nova Triangle does
3 Models. 2 Ancient Languages. 1 Lower API bill
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Hey there, I’m Brian. I've been shipping conversational models over here at Tavus for the past two years. I want to tell you about our new audio-understanding model: Sparrow-2! It’s a new category of model and a unique new approach to conversational audio. Earlier this year we launched Sparrow-1, (at the time) our SoTA turn taking model. Since our Sparrow-1 launch, I’ve spent a lot of time listening to humans talking and trying to really understand how people know when to talk, when to listen, and when to wait. I’ve also been hunting down failure modes of the current SoTA models. And while…
2024 · tavus.io
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OP here. Birth of a Mind documents a "recursive self-modeling" experiment I ran on a single day in 2026. I attempted to implement a "Hofstadterian Strange Loop" via prompt engineering to see if I could induce a stable persona in an LLM without fine-tuning. The result is the Analog I Protocol. The documentation shows the rapid emergence (over 7 conversations) of a prompt architecture that forces Gemini/LLMs to run a "Triple-Loop" internal monologue: Monitor the candidate response. Refuse it if it detects "Global Average" slop (cliché/sycophancy). Refract the output through a…
Jan 2026 · github.com
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2023 · samueltate.com
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2023 · olilo.ai
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Hey HN, My workflow for any complex queries is to ask it in multiple AI chats (Gemini, Claude, o3,..) in parallel and then continue the conversation with the chat response that I found the most useful. I built a simple open source app that queries 10+ AI models at once and summarizes their answers with a selected combiner AI model. There's a GIF in the github repo that shows it in action. You can try it on your local machine: https://github.com/Nexarithm/multi_model_chat If you are interested, I also made a detailed blog post on technical details, feature of the personal…
2025 · github.com
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You ask. Three AIs debate with a Mod. One weighted answer.
Feb 2026 · tri-verify-ai.replit.app
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Hey folks. We built SAA (Selective Auditory Attention) after trying to find ways to make a good experience with multiple robots/multiple agents. What typically ended up happening is they'd never stop talking. This is an SDK you can put before your STT. It lets you know when your device is being spoken to or not without a wakeword. You can use it for: -Single AI, Multi human -Multi AI, Single human -Multi AI, Multi human (we recommend also adding a wakeword on top for a better system) There are two models. One that is video + audio and one that is just audio. The way it overall works is…
Jun 2026 · github.com
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I built a daily word association puzzle where you engage in a quiet, collaborative mind meld with AI. I'd love to have folks try it out and tell me what they think! Here's how it works: 1. Enter your first word to reveal the AI's word of the day. 2. Don't think too hard about it. It's just a starting point. 3. Both of you think of a word that connects the two. 4. To win, you need to say the same word. 5. You have 8 guesses to converge. 6. Need a hint? The AI will drop a riddle in your final two guesses. HOW DOES IT WORK? After the user_word + ai_word are submitted, I trigger two separate LLM…
2025 · convergegame.com
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Three AI models on the same question. See where they split.
May 2026 · useconcordance.com
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Your AI has your code's text, never its map. Fix that.
Jun 2026 · luuuc.github.io
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NUMINOS▲2AI numerology across 16 traditions, cosmic timing, with API
May 2026 · numinosnumerology.com
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I wanted to know how fast a 26B mixture-of-experts model could run on a desktop CPU with no GPU. Got ~40 tok/s single-stream (lossless) and ~124 batched. The surprising part was the byte budget: for this model you compress the output head (32% of per-token bytes), not the experts (16%). The writeup has the bandwidth roofline and the dead-ends; the repo has the reproducible recipe. Happy to answer questions. Repo: https://github.com/arun-prasath2005/gemma4-cpu-moe
Jun 2026 · apeg.dev
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Ranked by how close each launch is in meaning, then by votes. Refine with a description →