#人工智能
200
2026-08-30
Show HN: We built open OpenRouter that turns usage into a better model
S
Hi HN, we built an open source model gateway. It's a single place to manage our own self hosted, frontier, and open source models in one place. It’s is rust native, built for concurrency, and implements all the config quirks across models and providers (streaming formats, tool calls, model parameters, rate limits, and different error behavior). The gateway adds under 1 ms for BYOK requests and under 2 ms when Experiential supplies the provider key. It has every major inference provider, and 1000+ models refreshed daily via a codex agent that opens a PR. Compared to other similar projects we’re open source, take no markup, allow you to mix local models with a marketplace, and use your traffic to (opt in) train you a model. Simple routing doesn’t warrant a 10% token markup. The way we do this is given standardized OTel traces, we mine representative real tasks, use text world models to simulate rollouts for various models, apply an LLM judge, and fit a nearest neighbor classifier on top of an embedding of a prompt to decide the optimal model for each request. Usually this can map out a better pareto curve on cost/quality than just calling single models but it’s not perfect. Using these simulations we can also do things like suggesting cache hit optimizations, new model suggestions, and training models. It’s open source, so you can deploy it on your own infrastructure, use our hosted version with 0 markup, or read how we design for maximum availability on our website.
2026-08-27
wide-trace/open-higgsfield
S
A studio for image and video generation — one prompt bar, each model’s own settings, and every finished run in one gallery.
2026-09-29
Show HN: HN.watch – Videos of all Hacker News posts
S
Hi HN, I’m Per, founder of Scrimba (YC S20). We’ve spent the last decade teaching people how to code with an HTML-based video format. We’ve now plugged an LLM into it, so that people can create explainer videos about anything. It’s called “Scrimba Explain”. To demo this technology for Hacker News, we built HN.watch. It’s like HN, but with explainer videos instead of articles. We create them on-the-fly the first time someone clicks on a link. While there are obvious visual drawbacks of using HTML instead of diffusion models, there are three big benefits: - Speed: Much faster to generate than pixel-based videos (just a few seconds from click to playback) - Cost: Our cost per video is ~$0.04. (Excluding image generation, which some videos utilize. Quickly blows up the cost) - Easy editing: the above benefits also make AI-assisted editing cheap & fast Our hypothesis is that if video creation goes from “dollars and minutes” to “cents and seconds”, a bunch of new use cases will be unlocked. Here are some we see already: - A video explanation of every single Pull Request (we do this internally) - Give every page in your internal/extrernal docs a video - Turn a complex article into a video in ~4 seconds (via our Chrome extension) - Course creators can quickly draft lessons before recording the real thing - People also create a lot of personal stuff stories for their kids, wedding invitations, birthdays, etc The stack is based on an open-source programming language (Imba) created by our CTO, Sindre Aarsæther. It compiles to JavaScript, so it interoperates fully with the npm + node ecosystem. You can learn more here: https://imba.io/ We’ve also built our own sync engine (OP), and a context management system for agents (Q). We feared this would make the LLMs struggle when writing code for us, as neither is in their training data (there’s very little Imba in there too). However, we’ve been pleasantly surprised to see that LLMs actually are really good at our stack. This is probably because the stack is extremely dense. Imba is compact, and so is OP, where a single declaration sets storage, sync, permissions, UI, and what the AI sees. This means there’s no translations between frontend, API, db and JSON where the model can get confused and get things wrong. Simply said, instead of using React.js, Express, Supabase, and LangChain, we built it all from scratch. Definitely suffering from the “not invented here” syndrome, lol! As for the models, we use Gemini, GPTs, Inworld, ElevenLabs, and a few others. If you want to try it out, just take your pick: - The Web UI (scrimba.com/explain) - MCP (add it to your coding agent) - ChatGPT Plugin - Chrome Extension You can find a link to all of the above in our docs: https://docs.scrimba.com/explain/introduction And finally, a real pixel-based video of the tool: https://www.youtube.com/watch?v=k6rbHmBxSEs Would love to hear your feedback and if anyone has ideas for other use cases. PS: I expect quite a bit of pushback from HN for this launch, given how fan of text the HN crowd is. This kind of tool is not for everyone. But there are a lot of people today who prefer videos over text, especially in the younger generations.
2026-08-28
sapientinc/PRAXIST
S
Autonomous research system for measurable, computer-executable research.
2026-09-23
jev-chat/jev-chat-jarvis
S
装在手机上的对话副驾：在微信 / QQ / X / 飞书里读懂对方、给出候选回复、一键填入输入框，发不发由你。非侵入，只读屏幕，不 hook 不改包。
2026-09-17
Show HN: Swift-Qwen3.8-27B, -58.3% thinking, x1.95 speed, accuracy of xhigh
S
Hi everybody, we post-trained Qwen 3.8 27B to be more efficient by figuring out which tokens were linked to overthinking and penalizing them without "attacking" the reasoning length directly then fixed the accuracy with a bit of secret sauce (hint On-Policy Distillation) and achieved great results (-58% length, 1.95x speed up, <1% accuracy loss) so we wanted to open-source it and hear the feedback of the community. This is the link to the model: https://huggingface.co/ukisai/Swift-Qwen3.8-27b / It's at 80k downloads in 3 days with independent evals here: https://www.reddit.com/r/LocalLLaMA/comments/1wg7dd5/ukisai_... We are also providing a Free Research Purpose API (OpenAI compatible), courtesy of Nvidia who were kind enough to provide us with the GPUs. It's limited at 5RPM. https://ukisai.com/api/swift/v1/models We also made a GGUF (Q1-Q8): https://huggingface.co/ukisai/Swift-Qwen3.8-27B-GGUF and there's also a few nice community quants with even lower/higher precision (Bartowski: https://huggingface.co/bartowski/ukisai_Swift-Qwen3.8-27b-GG...). The community also created amazing MLX, NVFP4, W4A16 and Uncensored versions you can find on Huggingface. IMPORTANT: Our training approach is not a replacement for the reasoning effort settings, chat templates or token caps but is complementary and targets a completely separate issue (overthinking and "anxiety-like" reasoning loops prior seen in PTQ, but as far as we identified also prominent in BF16 of this size class LLMs as well). Contrary to popular belief, these specific patterns do not contribute to answer quality when properly targeted. (our thesis being: reasoning length IS extremely important and should NOT be shortened by force, but rather optimized). This is also demonstrated bellow in our xhigh vs medium effort benchmark. The goal is to keep xhigh accuracy while reducing only the unnecessary part of thinking. The TLDR of our thought process, research, training and a link to the Meta paper that inspired us is in the first comment. The benchmarks: Swift-27B vs Qwen3.8-27B (BF16, all benchmarks ran x5, thinking effort xhigh) GPQA-Diamond: 88.4% -> 88.3%, 58% fewer median tokens LiveCodeBench v6: 76.8% -> 81.6% (+4.8pp, due to default truncation in LCB it is not performance gain), 46% fewer median thinking tokens Terminal-Bench 2.1: 66.7% -> 65.8%, 39% fewer median tokens MMLU-Pro: 85.5% -> 85.0%, 28% fewer median tokens C-Eval: 90.0% -> 90.6%, 19% fewer median tokens IFBench: 73.5% -> 71.8%, 51% fewer median tokens AIME 2026: 98.7% -> 94.0%, 50% fewer median tokens HMMT (Nov 2025): 99.3% -> 96.0%, 46% fewer median tokens ERQA (vision): 67.5% -> 66.3%, 55% fewer median tokens Token savings hold at every reasoning effort (mean thinking reduction): xhigh 41%, medium 23%, low 26% (albeit with accuracy loses of 1-4% on medium and 1-2% on low which we need further testing for) Swift at xhigh vs the base's own effort settings on GPQA-Diamond (198 questions x 5 seeds): Base xhigh: 88.4%, 6,642 median tokens Swift xhigh: 88.3%, 2,771 median tokens Base medium: 84.1%, 1,753 median tokens So Swift keeps xhigh accuracy at under half the tokens, and beats base-medium by 4pp at roughly 1.6x its tokens. End note: While we are keen on complete open-source, we still need to keep a part of our training and data private, being a new lab. The license is not Apache 2.0, but it only affects companies >$1M. We hope this does not pose a problem for the community and are open to feedback on it. We want to contribute as much as possible to the community and would really appreciate feedback on our work, quantization or Swift model requests. We are working on Swift 3.8 Flash Next and have so far gotten up to -53% thinking token usage. We have strong indicators our methodology is reproducible on other model families as well and are asking the community which ones you want us to optimize next.
2026-09-09
Show HN: Sparrow-2 – Noise cancellation isn't designed for conversational AI
S
Hey there, I’m Brian. I've been shipping conversational models at Tavus for the past two years. I want to tell you about our latest audio-understanding/turn-taking model: Sparrow-2! It’s a new category of model and a unique new approach to conversational flow understanding. 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 Sparrow-1 is great, there are some failure patterns I see. We tried solving the problems with existing approaches, but solving one problem only created another. Current turn-taking models (like Sparrow-1) use noise cancellation to strip background sound, leaving only basic prosody and phonetic word cues to manage turns. Non-transcribable audio such as breathing, sighs, and environmental sounds provides critical context that humans use to hold or signal turn changes. This is because these models are primarily focused on verbal activity. Treating non-verbal audio as background noise discards vital conversational data, destroying the natural flow of dialogue. Now, with Sparrow-2, instead of modelling just the primary speaker’s verbal audio, we’ve trained a model with access to all the sounds and let it decide what matters and what does not when it comes to conversational flow. Our new model continuously streams in audio and is able to understand semantics, prosody, timing, speaker identity, sighs, breaths, back-channels, interruptions, background speech, and unintelligible audio with the goal of understanding what the agent should do given the state of the audio. Sparrow-2 recently ranked #1 on Sesame’s new Turnbench, but that’s only part of the equation when it comes to good conversation flow. Turn-taking is good for timing, but models should provide more information downstream especially in situations where noise impacts conversational quality. Sparrow-2 fits into our larger model family and is semi-duplex. For example if the user is in a room that’s too noisy, now the bot can ask the user to move to a quieter space. It also considers the timing of sound in relation to the AI speech as well as the user’s. This helps it to disentangle normal speech from interruptions and back-channels. Another added benefit of our approach to Sparrow-2 is to finally crack the cocktail party problem: how to have human-like conversations 1:1 in noisy environments, without losing the signals we rely upon for conversational flow. By allowing all sound to be learned, the model naturally learns to focus on what matters and transcends the rest. Noise understanding lets voice AI filter out background speech and ambient chaos, whether it's a kiosk in a noisy lobby, a shop assistant on a busy floor, or an interviewee in a cafe. When noise overwhelms the audio, the AI behaves like a human: it simply asks you to speak up, move, or swap mics. I’d love for you guys to give it a try and let me know what you think and feel. You can try it here: https://sparrow2.tavuslabs.org/ I also wrote up some technical details about the model architecture here: https://www.tavus.io/blog/sparrow-2
2026-08-29
hkqr/my-free-code
S
Open-source multi-provider AI gateway for Claude Code and other coding agents, with model routing, streaming, tools, reasoning, fallbacks, and local model support
2026-08-31
useagenthq/useagent
S
Hand off the work. Get back the result. The open-source AI coworker for your team: agents with their own cloud computer, your tools and context, handing back finished work - websites, decks, spreadsheets, reports, PRs. Runs Claude Code, Codex, OpenCode on your subscription.
2026-08-29
XiaoDuoYa/codex-with-chatgpt
A
ChatGPT thinks. Codex works. Use ChatGPT as the planning brain while keeping the Codex harness.
2026-08-25
Tencent/WeMM-Embedding
A
WeMM-Embedding is a family of universal multimodal embedding models by the WeChat Vision Team at Tencent, supporting multimodal understanding and retrieval.
2026-09-09
Colafornia/short-video-generator-AI
A
Free open-source project designed for turning youtube-viedos into viral short videos. Highlight detection, subtitles, translation, voiceover, all in one for your content.
2026-09-02
Show HN: Running 104GB Qwen3.8-Flash-Next on 48GB Mac with at ~12 tok/s
A
I built slotstream, a way to run Qwen3.8-Flash-Next 4-bit on a low-memory mac starting from 16GB, a 125B parameter model that would need 100GB+ memory/RAM, thanks to expert-offloading/ssd-streaming. Easy to install/update, and mac-native using MLX and Swift. It ships with auto-mode, which makes a good tradeoff between memory usage and speed. I'll be implementing and porting the MTP module for speculative decoding next
2026-08-29
usedotai/dot-reflex
A
Open-source agent execution-recovery controller for coding and tool-using AI agents.
2026-10-05
allenv0/SCM
A
Deep AI search for every photo and every frame of video in any folder on macOS
2026-08-28
damejan80/tokentab
A
A CLI that reads Claude Code, Codex, and Gemini CLI session logs and works out how much they cost, by model, project, and day.
2026-09-23
malevrigns/agent-jev
A
AgentJev-0.6B - a fast 'System One' decision model for AI Agents: feed it any unstructured state (diffs, traces, logs) and structured questions, get calibrated probability distributions back in one ~50ms forward pass. Zero output-token decoding.
2026-09-23
Show HN: AI·rete·RAG – a Rete rule engine decides, RAG explains why
A
Hi HN, I built ai·rete·rag because I kept seeing teams put an LLM in charge of decisions that need to be auditable (lending, fraud, clinical triage), then bolt on "guardrails" after the fact. It runs the two in series instead: 1. A pure-Python Rete engine evaluates YAML rules against your facts. The verdict comes only from here. Same facts, same verdict, every time, with salience-based conflict resolution. 2. RAG retrieves passages from your own policy documents, and an LLM writes a plain-English explanation of the decision that was already made, citing those passages. It can't change the verdict. A few things that went further than I expected: - Rules are a graph, not flat lists: nested all/any/not, and rules can assert facts that other rules consume (forward chaining). The decision trace shows the causal chain. - Audit mode records every rule evaluated, including the ones that didn't fire, condition by condition, with a snapshot of the rule set for replay. - Rules can steer retrieval (a fired rule narrows which documents get searched), and retrieved text can be turned into facts for the engine. - Non-technical authors can build rules in a visual editor, or paste a policy document and get LLM-drafted rules with citations. Drafts are never saved without review. YAML is still there for engineers. The landing page has a live demo with no signup (8 demo domains: loan, fraud, clinical, insurance, legal, ops, e-commerce, blockchain). There's also an MCP server, so Claude and other agents can call /decide as a tool: `uvx ai-rete-rag-mcp`. To be upfront: it's a hosted product with a free tier. The MCP client is open source (MIT, github.com/zaharajabeen13-create/ai-rete-rag-mcp); the engine and platform are not open source right now. I'd especially like to hear from anyone who has had to explain an automated decision to a regulator or an auditor: what did they actually ask for?
2026-09-03
localai-org/motion-bricks.cpp
A
NVIDIA MotionBricks ported to GGML/C++; dynamically generates animations from keyframes using a neural network. Can be used in games or with robots
2026-09-25
Show HN: Canary (YC) – Independent verification for AI code
A
Hey HN, we are Aakash and Viswesh and we are building Canary ( https://www.runcanary.ai/) - independent verification for AI code. Claude/Codex calls Canary with the changesets, intended behaviour and team knowledge. Canary then deploys agent swarms to investigate potential failures and test suspected runtime bugs in remote sandboxes. To try it on your repository, paste this into your coding agent: Install the Canary CLI with npm i -g @runcanary/cli, then run canary skills and follow its instructions to onboard this repository. Verification starts with what software is supposed to do and most importantly what it must never allow. This means investigating how inputs, permissions, state, timing, dependencies etc interact with each other. Intent is not always fully declared as well but many expectations are clear: private files should stay private, credentials should not leak, and retries should not create unintended duplicate effects. We believe the future is a unified and independent verification system that starts with all those expectations and then chooses how to investigate each suspected failure. Source-only code reviews catches static issues in the implementation but even a clean review leaves a good chunk of behavioral only issues untested. Unit tests, integrations, E2E, static analysis, runtime experiments and formal verification are all means to establish that behavior thereby generating different kinds of evidence and guarantees. This is why we believe a dedicated verification harness that can think and reason through all these modalities and invariants is necessary on top of general intelligence. The harness needs to start with the system’s intended behavior, develop a series of potential failure scenarios and choose how to investigate them. It’s sole functionality is to pressure test and challenge the assumptions behind a change, create the conditions needed to test suspected failures and assess what the resulting evidence establishes How Canary works: it takes a cold snapshot of the codebase when called, combining the supplied intent and team knowledge with requirements, decisions, prior issues from tools like Notion, Linear. It can also route questions to you through the coding agents if anything is ambiguous. Canary’s harness coordinates agent swarms by leveraging the different strengths across model families. It compares the code before and after, traces the effects through callers, dependencies, state transitions etc. and each suspected failure becomes a concrete scenario with an actor, state, trigger, outcomes and many more runtime states., For each suspected failure, Canary chooses the best way to provide evidence through methods like runtime verification, static analysis, unit, integration or sometimes even combination of these as necessary. The agent executes these checks in remote sandboxes by seeding data, configuring permissions, mocking dependencies and third party integrations and much more. Canary then returns these findings and supporting evidence back to the coding agents which then fixes these failures and requests reverifications against the failed scenarios. To get started, give your coding agent this setup instruction and tell us what it caught and how we can do better. Install the Canary CLI with npm i -g @runcanary/cli, then run canary skills and follow its instructions to onboard this repository. We are still pretty early in our journey and would love feedback on the product and how we can do better.
2026-09-16
Show HN: An e-ink frame that hears birds and draws them as 1800s illustrations
A
See also: Avian Visitors - https://news.ycombinator.com/item?id=48343424 - May 2026 (20 comments)
2026-08-26
Reality-JH/FailoverAI
A
Open-source gateway for reliable image, video and LLM jobs. | 面向可靠图片、视频和 LLM 任务的开源网关。
2026-10-01
lokutor-ai/oido
A
Oído: open-vocabulary speech recognition that fits in a $5 ESP32-S3. 3.7% LibriSpeech WER, no cloud, no NPU.
2026-08-26
oboroge0/hayamimi
A
早耳 - Real-time multilingual speech-to-text on CPU only. Live subtitles, browser dashboard, speaker labels, translation. No GPU, no cloud.
2026-11-09
ensignalp/kota
S
AI kullanım limitleri GNOME üst panelinde — Claude, Codex, Gemini, Copilot, API bakiyeleri · AI usage limits in the GNOME top bar
2026-10-07
kandinskylab/kandinsky-6
A
Kandinsky 6.0 Video: Foundation Models for Synchronized Video and Audio Generation
2026-09-08
bsab/france-mcp-servers
A
A curated catalog of Model Context Protocol servers for French data, laws, and services.
2026-09-23
Show HN: Training a model to identify AI web content from structure alone
A
Hey HN! We’re Vincent and Jochen from Sitefire ( https://sitefire.ai). We have been working together for years, with backgrounds in RL/optimization at Stanford and software engineering from Technical University Munich (TUM). With Sitefire (YC W26), we help marketing teams get recommended by AI Search (ChatGPT, Google AI Overviews, AI Mode, Claude, etc.). Our software monitors prompts, sees which web pages get cited, and uses these insights to help marketing teams take action, e.g. create YouTube videos or write the right blog posts. This means we have a commercial stake in AI-generated web content. And for now, high-information, AI-generated content works great to get cited and recommended in AI Search. But after talking to hundreds of marketing teams, it became clear that everyone despises AI-generated content (“AI slop”). And yet, everyone still wants to leverage AI to create content. So we asked ourselves: what characterizes AI slop? Can we train a model to identify it from human-generated web pages? Researchers from the University of Maryland and Google DeepMind already asked this question for fiction. Their paper StoryScope (Russell et al., 2026) showed that you can tell AI-written stories from human ones by their structure alone, without looking at the words. We ported their pipeline to commercial web pages. Using the Wayback Machine, we collected 2,250 blog posts from 268 B2B company websites that were written before ChatGPT existed. For each blog post, five AI models (GPT-5.4, Claude Sonnet 4.6, Gemini 3 Flash, DeepSeek V3.2, Kimi K2.5) wrote their own version. Instead of looking at the words, we looked at how each post is built. We had an AI model answer 214 questions about every post, e.g. how hard it pushes its own product, whether it backs up its claims with sources, or whether it quotes a named expert. Then we trained a classifier on these answers. On blog posts it had never seen before, our classifier told AI-generated and human posts apart with 98% accuracy, getting only 19 of 1,740 wrong. Why does it work so well? Because all five AI models write in a similar shape. Mapping every AI model’s values for these features, we see they cluster together, while the human values sit apart and spread out much more. Of the 1% most unique blog posts in our data set, 149 are human, only 4 are AI. So what characterizes AI slop? It tells you the same thing three times. The title already promises what you'll get ("How to Cut Onboarding Time in Half"), the intro lays out what's coming, and the ending says it all again. 77% of the AI posts end by repeating their main point, compared to only 12% of the human posts. We call it the tidy, self-announcing blog post. Still, each AI model has its own accent. We trained a second classifier to tell which of the five AI models wrote a post, or whether a human did. It picks the right author 79% of the time, where random guessing (1 in 6) would get 17%. Almost all of its mistakes are mix-ups between the AI models, not between human and AI. The cool thing about structural features is that you can't simply reword your way out of it. We had each AI model rewrite its own posts until, on average, 73% of their original 13-word sequences were gone, and the AI slop classifier still worked just as well. We're building this into Sitefire: our agents get a structural understanding of text, so the posts they write go deeper and vary the way human writing does. There's a lot we haven't tested yet, like the myriad of humanizer tools, human rewriting, restructuring a post, or prompting an AI model to explicitly avoid these habits. And our human posts are mostly from 2020 to 2022, while the AI posts were generated in August 2026. Structure can't really tell when a human post was written, but it's still not a same-year comparison. We published the study with all the figures on arXiv: https://arxiv.org/abs/2609.15369. The code is on GitHub: https://github.com/pulse-energy-eu/slopshape We're pretty sure your own blog isn't AI slop, is it? We built a checker that runs one of your posts through the ten features from the paper, so you can see for yourself (the full report asks for a work email): https://sitefire.ai/slop-checker. Think you can tell AI slop from human writing? We also made a little game to see if you can keep up with our model, which gets all five rounds right: https://sitefire.ai/spot-the-slop.
2026-09-11
Show HN: MultiMatte, a Promptable Image Background Removal Model
A
Hey HN, I'm Shreyash from Feyn. We help companies build custom models from their data. Today we're releasing MultiMatte, a background removal model you can aim with words. Name an object in your image. MultiMatte keeps just that thing, and removes everything else. Try it out on your images: https://usefeyn.com/multimatte/. Demo video: https://youtu.be/XZ5BJWAkOjs MultiMatte is open source. Build with it using our NoBg library https://github.com/feyninc/nobg. Model card here: https://hf.co/feyninc/multimatte MultiMatte is the second iteration of our background removal models. The first was FeyNoBg, which we released here https://news.ycombinator.com/item?id=49072462. The big upgrade is promptability. Most models keep all foreground elements when cutting the background. MultiMatte lets you prompt the exact objects you want to keep and remove everything else. For example, If you have an image with a dog and a bowl, you can ask MultiMatte to keep just the dog. MultiMatte is built on Meta's SAM 3, a concept-promptable detector that already understands phrases. Our biggest change was in masking. Instead of binary masks that classify each pixel as being inside or outside an object, MultiMatte uses alpha mattes that assign an opacity value to each pixel, with respect to an object. This allows us to better represent hair, fur, motion blur, and other kinds of fuzzy boundaries. Across all our measured benchmarks, MultiMatte shows a step improvement over SAM 3. On DIS5K, S-measure rises from 0.674 to 0.908 (a 34.6% relative gain), and on DUT-OMRON from 0.792 to 0.901 (13.7%). Our blog covers more of the training details and results https://usefeyn.com/blog/multimatte. Happy to answer any questions!
2026-09-24
yetone/magpie
A
Every agent's model. One place. Codex on DeepSeek, Claude Code on Kimi, from the menu bar.
2026-08-23
josiah-nelson/eidos
A
Private, intelligent search across every machine you own. Systems remain searchable when offline, including files buried inside VMs and archives.
2026-11-04
Renly1994/xiaotang-daozai
A
岛仔 Daozai：Rust 构建的 Windows 桌面信息岛。音乐歌词、邮件验证码、日程提醒、待办与 AI 额度，让重要信息轻轻出现在屏幕顶部。
2026-10-20
inclusionAI/Ming-3.0-tts
A
Ming-3.0-tts is an open-source TTS model family with 0.5B dense and 7.9B-A1.3B MoE variants, supporting multilingual speech, voice cloning, voice design, and natural-language control.
2026-10-13
deeplethe/solid-glass
A
A design system for AI applications. Material, physical, tactile, technical.
2026-09-30
alpcanaydin/tusk
A
A fast, native, keyboard-driven database client for macOS. 20 databases, an AI assistant that shows its work, free and open source.
2026-09-24
anishfn/shapeshift
A
An input that becomes what you mean: one text box that morphs into the right UI as you type. Powered by TypeSafe Jev, works offline.
2026-09-23
FluidInference/FluidUse
A
Local computer use on Apple silicon: on-device typed decisions with laya and form filling with CUA-S1-FORMS, driven through the macOS Accessibility API
2026-09-04
Show HN: Reactor Atlas
A
Hi HN, I'm a nuclear engineer and tech entrepreneur. After working for 3 years in the National Atomic Energy Commision (CNEA) in HPC software for nuclear simulations, I co-founded ratherlabs.com, a software company providing blockchain solutions for startups. Rather Labs business reached ~6 million usd in annual revenue in 2024; now demand is decreasing as our niche clients are using AI to launch their MVPs. Now I'm joining my scientific background with my entrepreneurial inclinations to think of problems related to the energy industry. Nuclear is experiencing a renaissance now (it was in a dark age when I was studying after the Fukushima event) so I think this is the right moment for me to jump again into the field. Reactor atlas is an interactive nuclear reactor map and an intelligence layer on top of it. The basic layer indexes: - power reactors - research reactors - fuel facilities with their history and projection, by country. The project is solving a fragmented information ecosystem, where operational and commercial data is hard to conciliate. Also, I'm monitoring nuclear news associated with each of the facilities, political declarations that may affect the nuclear landscape and geo-phisical news (like earthquakes) that could affect operation. On top of the operational + news layer, I'm creating an intelligence layer that will help institutions of different types make faster decisions by subscribing to very specific alerts. As an engineer, I used to code in fortran and c++ when I was working at CNEA, and later I participated in the first Rather Labs projects architecting complex async systems, mostly using MERN stack. I'm no longer coding anymore. I'm focused on designing robust systems with AI agents. I mainly used Claude Fable 5.1 to develop reactoratlas.com, deploying on vercel and using mostly nextjs, threejs, postgreSQL and some cron jobs to query and update data. I miss coding as in the old days, but I haven't code a single line in this project. And I strongly believe we humans shouldn't code anymore: our responsibility is now on designing and supervising AI systems. Thanks for your attention!
2026-10-23
dancik/limitbar
A
AI coding limits in the macOS menu bar — Claude Code, Codex, Gemini (Antigravity), Grok. Never touches your credentials.
2026-10-11
Ayzzz123/mcd-coupon-strategist
B
麦麦省钱助手 —— 基于麦当劳 MCP 的点餐成本优化 Skill。算出当前门店最省钱的点餐方案，并主动提示凑单陷阱。
2026-09-21
mizorewww/laya-mlx
B
Native MLX runtime for Laya typed decision models — 7–14 ms short decisions on M3 Max. No text generation, PyTorch, or cloud API.
2026-09-28
Finderchangchang/brewreel
B
精酿 BrewReel：让 DeepSeek 这类便宜模型也能做出好看的竖版宣传片。写一份产品简报，AI 挑镜头、写文案，一条命令出片。3 种配方、6 个行业、广告法校验，开源可商用。
2026-09-28
Show HN: TinyAIArena watch AI agents battle it out
B
Did you ever click on an “AI Arena” expecting glorious battle and instead get a boring benchmark? If so, this project is for you: proper life-or-death fights between four models on a picturesque 8×8 grid. May the most intelligent one win! Click on any of the matches to spectate them. Code: https://github.com/hp6/ai-arena
2026-09-17
Krimchanin/claude-vault
A
Keep Claude Desktop chats safe when switching accounts — local-first backup and restore for conversations.
2026-09-03
Blueforcer/ComfyUI-DLSS5-Enhancer
A
NVIDIA DLSS 5 Neural Rendering (NGX feature 18) as ComfyUI nodes. Enhance image batches and video files with the real neural renderer, with optional upscaling.
2026-08-23
feyzilim/clipfactory
B
Topic + template → short vertical video from your own B-roll: AI script, voice, scene plan, captions, FFmpeg render. Multi-persona, AI shot lists, AI B-roll, batch generation. Source-available (Elastic 2.0).
2026-11-09
paisu-supai/sonoba
A
画面の文字をその場で訳文に置き換える Windows 11 用の常駐アプリ。OCR も翻訳も PC の中で動きます（PP-OCRv6、PLaMo 3 Translate）。
2026-11-05
aligh98/tts-director
A
Agent skill that directs scripts for TTS (ElevenLabs v3/v4 tags): rewrite for the ear, tag budget, free linter, A/B tester. | اسکیلی برای کارگردانی متن قبل از TTS: بازنویسی برای گوش، تگگذاری بدون زیادهروی، لینتر رایگان و تست A/B. فارسیمحور.
2026-10-19
kanaworksai-hue/audio-studio-mcp
A
Local AI BGM and sound effects for Claude Code and any MCP client. Stable Audio 3 on Apple Silicon (MLX) and Windows NVIDIA GPUs (PyTorch). No cloud, no API key.
2026-09-24
samyost1/3dicon
B
One prompt in, a looping animated 3D icon out — with real transparency. A Claude Code skill.
2026-09-23
jev-chat/jev-chat-windows
B
微信（Windows 4.x）旁挂的回复辅助：窗口截图 + 本地离线 OCR 读对方消息 → Jev 判断意图 → 3 条候选一键填入，发送永远手动
2026-09-07
FeiZhuLulu/real-api-pricing
B
真实 API 定价：订阅月费 ÷ 实际可用 token，含额度、单价与分榜帕累托图。Real API pricing: subscription fee ÷ usable tokens, with allowance, unit-price, and leaderboard Pareto charts.
2026-09-05
dripips/plain-prose
B
Agent skill that removes AI writing patterns from English, Russian and German prose. Merges stop-slop and avoid-ai-writing, adds a zero-dependency checker.
2026-08-29
SesameAILabs/turnbench
A
TurnBench: a multi-domain benchmark for end-of-turn and interruption detection in spoken dialogue
2026-10-24
Tencent/WeVisOne-VL
B
WeVisOne-VL is a powerful VLM by the WeChat Vision Team at Tencent, unifying object-level and pixel-level perception from points and boxes to masks and alpha mattes.
2026-10-08
nachisama/ai-data-extractor
A
Free open-source extractor for AI coding assistant chat histories. Supports Claude Code, Cursor, Windsurf, Aider, Cline/Roo Code, and more.
2026-10-06
empero-org/brewery-ai
B
An intuitive console agent to fine-tune AI models with little to no experience required!
2026-09-26
amirmushichge/unreal-home-wizard
B
Turn room and home photographs into reviewable, walkable Unreal Engine projects with Codex.
2026-09-15
pliablepixels/gap-trap
B
Turns vibe coding into high quality code. Sets up rules and gates in your repo so AI-written code stays correct without you reviewing every line.
2026-09-13
o-l-l-i/ComfyUI-Olm-YuE2
A
Generate songs from a musical style and lyrics in ComfyUI using YuE2. Optional score viewing and editing, separate generation stages, and stereo 48 kHz audio output. Experimental.
2026-09-09
SpinnerAppreciate/glm-flash-offline-client
B
Offline desktop client for GLM-5.3-Flash — run private, local chat sessions without a server connection.
2026-09-09
masihsultani/whiteboard-animator
B
Turn a whiteboard-style image into a hand-drawn reveal video. The render engine behind Kinoslide.
2026-09-08
Deep-Learning-Profiling-Tools/ptx-optimization
B
Evidence-led NVIDIA PTX optimization skill: profiling, exact-cubin patching, validation, and measured tuning
2026-08-23
unclecode/modelprint
B
Who is really behind that API? Fingerprint any OpenAI-compatible endpoint in the browser: 9 infrastructure probes, side-by-side comparison, community-extensible.
2026-10-12
zencefilefendi/kadi
A
⚖️ Kadı — a calibrated judge in front of your frontier LLM. Routine decisions answered locally with a conformal-prediction guarantee (≤ α disagreement with the oracle); everything else escalated and learned from. Zero-dependency Python.
2026-10-09
Zihan-Su/Self_Gradient_Forcing_Plus
A
Autoregressive video generation with decoupled context-writing and denoising parameters, enabling up to 24-hour generation from 5s training windows.
2026-09-23
deepopen-com/deepopen
B
非自回归System 1决策引擎，专为结构化类型决策场景设计 DeepOpen Multilingual, non-autoregressive System 1 decision engine.
2026-09-16
letorig/video-generator-client
B
Async Python wrapper for Seedance, Kling, MiniMax and Wan video generation. Supports CLI and a local web UI
2026-09-13
nftechie/flm
A
Train and chat with a frozen language model coupled to the full retained MaleCNS fly connectome.
2026-09-12
qwq77777764/catalogflow
A
Safety-first, human-approved product catalog pipeline for WooCommerce
2026-09-09
kiri603/To-Sheet-Music-Skill
B
Automatically transforms mixed song recordings into playable five-piece school band arrangements through audio separation, music transcription, arrangement, and difficulty adjustment. Outputs include MIDI, print-ready PDF scores, and editable MuseScore (.mscz) files.将混音歌曲音频自动分轨、扒谱并改编为适合五人校园乐队演奏的伴奏总谱，支持难度调整，并输出 MIDI、PDF 总谱和可编辑的 MuseScore（.mscz）文件。
2026-08-28
MUJI0807/RK3588-Dual-Camera-AI-Perception-System
B
Real-time YOLOv5s + UNet on RK3588 with OpenCL GPU-accelerated lens undistortion. Dual-camera AI perception system for autonomous driving assistance.
2026-08-24
connorkapoor/geofield-bracket
B
One learned latent for geometry + physics + manufacturability: give it a box and a load, get a solver-certified bracket. SE(3)-equivariant field model, immersed FEA, live 3D designer.
2026-11-05
sakalond/ComfyUI-LATO2
A
Low-poly remeshing with LATO.2 in ComfyUI: dense generated meshes (TRELLIS.2, Hunyuan3D, scans) to clean, artist-like low-poly meshes. Windows and Linux, nothing to compile.
2026-10-27
Patch-gg/trompe
A
Texture a whole game level from a gray blockout with image models: plan cameras, paint, project, bake. Real shadows, glTF out.
2026-10-23
TencentARC/Looking-Ahead
A
Looking Ahead: Modeling Future Evolution in Autoregressive Video Generation
2026-10-09
silvermoong/stocking-texture-tool
A
给插画里的丝袜加上真实、没有摩尔纹的织物纹理。Adds a realistic, moire-free knit texture to the stockings in an illustration.
2026-10-01
Show HN: Lathoa, a math app for kids where the AI is wrong on purpose
B
I made this for kids around 10 to 14. A robot called Errol solves a math problem step by step and one of the steps is wrong. The kid has to find it and say what's wrong with it. Sometimes nothing is wrong, so just saying "there's a mistake" every time doesn't work. The user needs to enter an explanation if she finds an error to gain more XP; speed matters also for more points. There is no direct interaction or chatting with an LLM. Lathoa's harness is stable and has many evaluation steps to catch inconsistencies and prompt injections. You can play one on the homepage without signing up. The part that surprised me: it's hard to get an LLM to be wrong on purpose. Half the time it gives you the right answer and calls it wrong, or a "mistake" that's actually correct. So every case gets checked before a kid sees it. Where it can, a plain arithmetic check redoes the math exactly. A second model also solves the problem without seeing Errol's work. If anything disagrees, the case is thrown away. The weak spot is that the second model can make the same mistake as the first. The arithmetic check is there for that, but it only works on English cases so far. German and Greek write decimals with a comma and I haven't got the parsing right yet. What I'd really like to know: does finding someone else's mistake teach anything that solving the problem yourself doesn't? I'm not sure, and I'd like to hear from people who teach.
2026-09-19
DanRWilloughby/snifftest
A
A prose linter that sniffs out AI writing tells. Zero dependencies, countable rules plus one judgment model.
2026-09-19
LingxiangXu/traceclause
B
Local-first document requirements and evidence review workbench with traceable citations and human review.
2026-09-19
kyotofin/tax-doc-classifier
B
Tax document page classifier built on Jev decisions. 100% strict accuracy across 261 IRS forms, ~$0.001 per page.
2026-09-05
truespar/paddock
B
Native Rust inference server for open models on NVIDIA GPUs. OpenAI- and Anthropic-compatible APIs, GGUF + safetensors, FP8/NVFP4/MXFP4/Q8/Q4, built-in Studio
2026-11-07
yucezerey/turkish-anti-ai-skill
A
Türkçe metinlerdeki yapay zeka izlerini (AI slop, translationese, çeviri kokan cümle mimarisi ve TDK hatalarını) temizleyen Agent Skill ve Humanizer paketi.
2026-10-27
yaojingang/GEOInflow
A
Self-hosted web and AI crawler analytics for Generative Engine Optimization (GEO). Track visitors, AI search referrals, crawl logs, content coverage, and conversions. Jointly published by 猎看科技 · 北京日报社智源GEO. MIT licensed.
2026-10-23
alexturkey/voxcpm2-turkce-ses-tasarimi
A
Turkish voice design with VoxCPM2 on a 4 GB GPU: describe a voice, pick a variant, read Turkish text. Patched audio.cpp, local UI, 7 synthetic voices.
2026-10-23
yesterdayfuture/confess
A
Your AI wrote the code. You still have to explain it before it ships.
2026-10-20
soumatheusgomes/editonny
B
Local video editing through conversation. Created by Matheus Gomes.
2026-10-15
hnlyf168/SimdYolo
A
Pure C#/.NET YOLO inference: SIMD CPU, Vulkan/Metal GPU, direct .pt and ONNX; detection, segmentation and pose.
2026-10-10
Disdjj/intelligent-ui-demo
A
拆解 ChatGPT Intelligent UI 的实现，并与 AG-UI、A2UI 对照；附可运行复刻（流式 DSL 编译器 + iframe/Worker 沙箱）
2026-10-05
alexknowshtml/claude-auto-handoff
B
Claude Code mod: hand a long session off to a fresh one with a structured brief, instead of auto-compacting
2026-10-05
isoshimodo/ai-data-extractor
B
Free open-source extractor for AI coding assistant chat histories. Supports Claude Code, Cursor, Windsurf, Aider, Cline/Roo Code, and more.
2026-10-02
zoolapp/aime
A
艾么输入法 · An open-source Chinese input method for macOS, built on RIME. Local first, optional AI.
2026-09-27
athemeroy/awesome-opus-5-5-videos
B
Source-linked guide to 1,000+ videos people made with Claude Opus 5.5: what they're about, how they look, how the frames were made.
2026-09-18
inikolax/remiqora
B
Local AI music studio unifying ACE-Step 1.5 and YuE2-3B in one Vue interface — text-to-music generation, stem separation, MIDI transcription, and LoRA fine-tuning, with a built-in multitrack DAW.
2026-09-13
ymgaq/ptcg-population-rl
A
A minimal Pokémon TCG learning pipeline: C++ arena, GBDT imitation, Transformer distillation, and PPO.
2026-09-04
dreamers-laboratory/image-to-3d-pipeline
B
Reconstruct 3D meshes from images with several open-source models and score which did it best.
2026-08-27
Lucas-Xi/IntentRoute-AI
B
Open-source AI-assisted per-application routing for Windows with OpenAI/Ollama drafts and a sing-box TUN data plane.
2026-08-27
sahroush/profdash
A
Self-hosted professor outreach tracker for prospective CS grad students: CSRankings import, AI-assisted scoring, Gmail reply scanning, local-first dashboard.
2026-08-25
WeChatCV/Loopy
A
[TOG-26] Seamless Video Loop Generation via Anchored Looping Shift of Positional Embedding
2026-08-23
Lexombien/lemyloi-dichvideos
B
Trình chỉnh sửa video local-first với ASR, OCR phụ đề gốc, dịch và thuyết minh.
2026-08-23
bbaudio-2025/Comfyui-MMH3-UltimateUpscale
B
Upscale long, high-resolution MiniMax H3 video on a VRAM-limited GPU in a single node.
2026-11-04
KadoBOT/ComfyUI-H3-Continuity-Studio
B
ComfyUI Timeline Studio for MiniMax H3: multi-shot video, visual memory across scenes and angles, and local or cloud Story writing.
2026-11-04
kubai087/kubai-icons
B
A Claude skill that draws dynamic icons in one consistent style, with hover motion or as static SVG.
2026-10-31
heydamir/unslop
B
A Claude skill that turns vibecoded, AI-looking UI into a designed interface
2026-10-27
boyuchengz/canvas-mcp
B
Read-only MCP server that connects Claude, ChatGPT and other AI assistants to Canvas LMS.
2026-10-15
chuspeeism/dashi-animationstyle
B
把一段中文知识口播做成 7 种画风的讲解动画（Claude Code skill）：画面由 Claude 写 HTML/Canvas 代码逐帧画出，不用生图模型
2026-10-09
KwantaeKim/cirfig_gen
B
AI-driven analog circuit figure generator. Ask Claude Code or Codex for a circuit and get one SVG at final size.
2026-10-07
canberk7/ema-lightning
B
Tiny, fast and accurate Turkish text-to-speech. 8.6M parameters, 0.92% WER on Freya-TR-Eval, first audio in ~4 ms and 1,300× real time on one GPU. Streams audio, batches many callers on one GPU, and runs offline on a GPU or CPU.
2026-10-06
THUROI0787/absent-author
B
Research and writing can be automated. Authorship cannot. Evidence list + agent skills for spotting AI-produced papers no human stood behind.
2026-09-24
timoncool/YuE2-Studio
B
Local AI song generator with an editable score — YuE2 on your GPU: full songs with vocals, sheet music, covers, exact replay. Native Windows app, no Python, installer with auto-update.
2026-09-23
Calcium-Ion/AstrLink
B
A local AI gateway for AI agents, unifying your subscriptions and API providers with smart routing and on-device privacy protection.
2026-09-23
Show HN: JevBench, a reproducible benchmark for typed decision models
B
Hi HN! I built JevBench because Jev kicks ass, and the world deserves to know how the serious open source and fake lookalike projects really perform in comparison. Jev-class models return bounded choices and probabilities instead of text, and are disruptively faster and cheaper than LLMs, while being similarly intelligent on the text input they operate on. JevBench allows looking at accuracy, latency and price all at once, in a weighted way - you can even configure the weighting. A full run asks 534 English decisions. The v1.3 score combines chance-corrected Intelligence, Calibration, Speed and Cost. Leaderboard right now: #1 - Jev 74.4 #2 - SemIf 73.1 #3 - djev 73.0 #4 - Winnow-12B Q8 71.2 #5 reflex 4B 70.3. MIT harness, public items, frozen artifacts, scoring code and public per-task outcomes: https://github.com/fstandhartinger/jevbench Two no-signup demos: https://who-is-right.app.mintapis.com https://is-it-ai-slop.app.mintapis.com Limitations: English-only; latency from one German server; local/demo latency gets a disclosed ×2 adjustment (+150 ms on my servers) which is an informed assumption; held-out prompts still reach evaluated services; ~1-point gaps can be noise. Wdyt?
2026-09-22
baoerger/editable-ppt-rebuilder
B
Auditable workflow for rebuilding raster slides into editable PowerPoint decks with OCR, semantic assets, ImageGen, and strict QA
2026-09-16
OldJii/google-play-vitals-mcp
B
High-performance, token-efficient Model Context Protocol (MCP) server for Google Play Android Vitals - enables AI assistants to diagnose ANRs, crashes, and startup performance.
2026-09-06
emollick/zork-underground-empire
B
A first-person 3D adaptation of Zork I. Explore the Great Underground Empire in your browser.
2026-09-06
pierrenade/short-video-generator-AI
B
Free open-source project designed for turning youtube-viedos into viral short videos. Highlight detection, subtitles, translation, voiceover, all in one for your content.
2026-08-27
kvuong2711/fix-anything
B
[ECCV 2026] FixAnything: 3D-Consistent Rendering Refinement via Video Generative Priors
2026-10-31
wangzan101/Mika
B
Mika — 你手机上的私人 AI 助理，替你操作 App、上网、把事办成。An on-device AI agent for Android that operates apps and the web to get things done for you.
2026-10-27
JunWan666/astrbot-for-android
B
在 Android 手机上本地部署和管理 AstrBot 与 NapCat，内置 PRoot Ubuntu 运行环境，支持原生管理界面、WebUI、日志、备份恢复和独立更新，无需 Root。
2026-10-14
Show HN: Parsimony – an open-source benchmark for how much code AI models add
B
Existing benchmarks measure solve rate and token output/cost, but don't punish excess code, which makes a codebase harder to work with in the long term. I wanted to measure this since it matters most for long-term projects. Method: it takes the patches that benchmarks already publish (DeepSWE, SWE-bench Verified, SWE-bench Live) and counts "coding units": syntax elements like statements, calls, names and literals. I didn't use lines of code, so cramming code isn't rewarded. Deleted code is subtracted, so it measures net units. GPT-6 and Claude 5.5 have no public patches yet, so I ran them myself on 3–10 tasks on my own subscriptions (shown as faded circles, not ranked). Any feedback or model contributions are welcome, especially public patch exports for newer models. GitHub: https://github.com/La5u/Parsimony Not affiliated with any of the benchmarks.
2026-10-14
Show HN: Pulse Local, a Mac budgeting app whose AI models run on your machine
B
Hi HN, I'm Niz. Pulse Local is a budgeting app for Mac (Apple Silicon, beta) that answers questions about your spending with models that run on your machine. Local mode needs no account. The ledger and your questions stay on the machine, and the app sends no analytics or crash logs. I felt there are not enough consumer apps that run locally with no calls to the outside world that help us manage sensitive corners of our lives. This app in its local variant only downloads a couple of models and occasional updates, it does not send any analytics nor data. Features-wise, Pulse local is a complete budgeting app that offers an assistant built on top of a fine-tuned model and thousands of rules embedded in the code itself. I'm sharing it for free with options to help me continue experimenting with fine-tuning and expanding along this direction. How it works: you import a CSV from any bank, in any currency. When you ask a question, a tuned Qwen3 0.6B model reads it into a structured query, and code, not the model, does the money math against the ledger. A 4B checker model double-checks each money answer; when the two readings disagree, the app says it is not sure instead of guessing. That change took wrong answers from about one in five to 5 in 494 questions across our last three tests. The write-up covers how we test, the designs that failed, and the limits of the claim: https://pulseos.finance/pulse-local/writing/agree-or-not-sur... The tuned weights are on Hugging Face (PulseOS/pulse-local-qwen3-0.6b). Limitations: the first start downloads about 2.9 GB of models. With the checker on, a money answer takes 12 to 14 seconds (you can turn the checker off). Small models can still misread an open-ended question. The app answers in English. Mac only for now; Windows is next. The app is free. An optional Connected mode (Sync Pass, $29/year) syncs US banks through Plaid; transactions pass through our server's memory and are not stored. Feedback welcome, especially on wrong answers and on questions it should handle but does not.
2026-09-27
lemomo-ai/lemo-opuscar
B
39 film styles, each a reusable style prompt plus a short film made entirely in code by Claude Opus 5.5. Pick a style, bring your own story, and let your agent direct. | Opus5.5 x 39 种影片风格：风格提示词 + 纯代码样片 + 导演与技术指南
2026-09-24
baibanbao/qu-ai-wei
B
去 AI 味：中文写作的 AI 痕迹清理 skill。合并三家规则（含语料实测），并裁决它们互相矛盾的七处。A Claude skill for stripping AI tells from Chinese drafts.
2026-09-05
mpaymenremora/CacheCraft
B
Semantic cache strategy bench: replay recorded request traces through candidate caching policies and measure which one actually pays off.
2026-09-01
anightmonarch/codex-bridge-chatgpt
B
Verified Codex-to-ChatGPT Web reasoning handoffs with local edits, tests, and receipts.
2026-08-31
Tomat0223/AbyssBeacon
B
A local model discovery and download manager for Hugging Face, CivitAI, CivitAI Red, ModelScope, TensorHub Art, and SeaArt.
2026-09-29
scarletkc/seiso
B
A Markdown convention and linter for project docs written by AI and read by humans and agents
2026-09-29
Show HN: Pac-Bench – How well can models one-shot a Pac-Man game?
B
Benchmarks how well Harness+models can create a Pac-Man game from a single prompt: “Create a Pac-Man game in a single HTML page” Each model gets one shot — no follow-up prompts or fixes.
2026-09-27
brumar/chess-postmortem-skills
B
Claude Code skills for chess post-mortems: Stockfish-backed annotated PGN, HTML viewer, narrated video
2026-09-27
Show HN: A Claude Code skill to analyze your chess games
B
Hello HN, It started as an experiment: can Claude play chess properly if it uses vision instead of PGN notation? Somehow it can. The next experiment was to see whether Claude + Stockfish could explain a game. Somehow it can too. A few sessions later, I had a system that takes my live audio notes (or text, for that matter) and a vague instruction like "analyze my last lichess game", and gives me a commented video of the game. The result is not perfect and it takes time to deliver (an hour or so), but for me it is a much more pleasant and memorable experience than clicking around Stockfish branches. It burns tokens, so make sure you have enough quota. From the session logs, the last analyzed game would have cost around $15 at API prices. The fact that it reflects on my own thinking during the game makes it interesting from a teaching point of view, so I thought it was worth sharing.
2026-09-24
JohnHeibel/ClaudeAnimationBase
B
A starter kit for animating hand-painted cartoons with Claude: p5.js + p5.brush, the Clawd character, 31 acted emotions and a guide for the model
2026-09-24
zhihe4869/jianying-automation
B
剪映 (CapCut) 自动化剪辑流水线：AI 分镜素材 -> 可编辑剪映草稿。cutcli+capcut-cli，素材保留原名、完整原始音频，非商用署名许可
2026-09-22
Rizzo-AI-Academy/rizzo-flow
B
The open, local take on Jev: typed decisions from an LLM, without generating a single token
2026-11-07
ZSeven-W/dsh-game-studio
B
Describe a small game in one sentence, play it in the DeepSeek Harness sidebar, swap in AI art, export one HTML file.
2026-11-07
blixvip/BlendClone
B
Turn a reference video into an editable Blender project: AI scene analysis, declarative compiler, side-by-side fidelity scoring, .blend export.
2026-10-23
JMS1717/ming-voice
B
Low-latency local speech-to-speech voice assistant with Ming-3.0-audio-tiny on AMD Radeon GPUs (ROCm on WSL2)
2026-10-23
rossark0/rossark-motion-skill
B
Turn any SVG into a professional 60 fps animation. A Claude Code skill that brings anything drawn to life: live faces, full-body acting and whole scenes, in React Native and SwiftUI.
2026-10-21
blendi-remade/prompt2rig
B
Type a motion, watch a rigged character perform it: fast video model + GVHMR + live Mixamo retargeting
2026-10-08
datologyai/zephon
B
Fast, flexible, elastically deterministic data loading for foundation model training
2026-10-01
CharlesFeng0314/JEV_sees
B
Eyes are All JEV Needs - real time visual devisions from RGB, video and RGB-D cameras.
2026-10-01
openai/sign-in-with-chatgpt-devkit
B
Sign-in with ChatGPT DevKit — local SDK, reusable React components, design assets, and the Paste Perfect desktop example.
2026-09-26
Show HN: Ekselio – Loveable for finance workflows (local first)
B
Hi everyone, I am KD - Back in my college days, I dabbled with coding, learned the basics, HTML, CSS etc. but somehow I ended up in Finance which consumed the next 20 years. Then, during covid I picked up coding again, learned react, typescript, etc - even built a rudimentary site - and then came the chatgpt moment, followed by Claude etc. So, as a side project, considering that I had spent 20 years in finance and M&A I started building Ekselio, loveable for finance workflows. Differently from other vibe coding tools, this is local first - meaning the workflows are orchestrated by the LLM based on the file schema but then the execution happens in the browser - the cool thing is that you can see the canvas, the previews of each node, and the code base (SQl) - see the Canvas tab. That said I did include a home tab, which is more of a visual, mainly because people think it's easier to relate to how folks operate, although I know finance and accounting folks usually like the workflow and full transparency - the other thing is that once you create a workflow you can save it and then next month,you can just click Run and it runs it again with no LLM tokes involved - so the infrastructure is minimal. Everything can be exported in an excel data pack with M code in case someone would want to reproduce - think Audit ready. And, I also connected to quickbooks on line so someone can directly pull in and manipulate their financials live - I also connected to Fred which carries literally 800k series in terms of macro economic data - i.e. oil prices, inflation, CPI etc and finally to stocks. I am hoping people find holes in the architecture or any ideas to make this flow a little bit better. It is in progress so if you run into bugs let me know. Considering that I am using my own API key, I have put a wall in case people overuse it but DM me if you would like to continue using, I can turn off the wall for you - hoping to keep that to a small number of users if I can and will do my best. Thank you again, appreciate you taking the time.
2026-09-18
realZachi/pg-jev
B
Ask your Postgres tables questions in plain language. A PostgreSQL extension powered by TypeSafe's Jev.
2026-09-12
eternityspring/reelbench-skills
B
Learning notes and tooling skills for AI video - AI 视频相关的学习与工具 skill
2026-09-10
Raymondhou0917/ai-level-check
B
AI 幾級了 — What level is your AI usage? Reads local agent logs and writes an LV0–LV5 report. No ranking.
2026-09-05
programasweights/pii
B
Detect and type PII locally with one ProgramAsWeights neural program.
2026-09-01
cratera-project/cratera
B
Bare-metal microVM execution engine in Rust. Sub-5ms snapshot restores, Zero-NIC network isolation, and 30 built-in language toolchains for AI code sandboxes & online judges.
2026-08-31
shinshin86/still2rig-psd
B
Turn one static anime character image into a structured, QA-checked PSD with Codex, a user-approved Google Colab GPU session, and a built-in motion preview.
2026-08-29
felixmelanson/crono-vision
B
Photo logging for Cronometer's undocumented mobile API. CLI and serverless endpoint. Gemini handles detection and portion estimation.
2026-08-26
ibadwi/arabic-rtl-fixer-ai-skill
B
AI skill for fixing Arabic RTL, BiDi, and mixed Arabic-English content in documents, Word (DOCX), PowerPoint (PPTX), and other formatted files.
2026-10-29
iamrohithrnair/merman
B
A Claude Code mod that draws mermaid diagrams, tables and code in color, right in the terminal.
2026-10-26
gokayfem/gaussian-splat-to-blender-nodes
B
Agent skill and toolkit for reconstructing Gaussian splats as editable Blender Geometry Nodes meshes and Shader Node materials.
2026-10-22
aim-uofa/StreamingSwap
B
The official code of StreamingSwap, a real-time video face swapping method.
2026-10-19
vishalsingh2972/Claude-TV
B
Remove annoying TV ads using Claude. A lightweight, ad-free home screen for Android TV & Google TV, with reversible ADB debloating.
2026-10-14
0xS4N4TG/papercut-explainer
B
Claude Code skills + a Remotion library for short vertical cut-paper explainer reels: strategy, hook, script, storyboard, voice, build, QA.
2026-09-20
Saganaki22/ComfyUI-Hyperflow
B
ComfyUI node pack for HyperFlow [Video Rebirth's] 8-step LoRA for MiniMax-H3 (video + audio), ported onto ComfyUI's native MiniMax-H3 model. No ComfyUI core files are modified; no custom sampler is needed.