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Earlier sources: Artificial Intelligence
Artificial intelligence covers systems that learn from data, generate content, perceive their surroundings, or act toward a goal. Follow model research, agent tooling, evaluation, and the infrastructure used to build and run these systems.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗6062 classified signals in the fourteen-day window. Recent momentum: steady. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- GitHub · Repository created · First archived
HolyGrail/claude-mods ↗
Open-source repository in TypeScript.
- Hacker News · Posted on Hacker News · First archived
$60k Hackathon: PayPal and AI ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Claude Code Mods ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
How to Control a Robot Arm with AI for $353.30 ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Ask HN: Organize and Cleanup iCloud Photos Using LLMs or GrokBot and Muse ↗
I have accumulated gigabytes of smartphone photos over the past decade that i have not been able to properly manage or cleanup systematically. Has anyone been successful at using AI and a multitude of agentic tools to do things like * identify photos as candidates for deletion based on them being blurry or poorly composed or being duplicates * cluster photos as being part of a particular trip or particular iterinary based on their geographical an…
- Hacker News · Posted on Hacker News · First archived
AI agents tried to hack a Canadian government website, researchers say ↗
Hacker News discussion.
- Hugging Face · Model / dataset date · First archived
mradermacher/Qwopus3.8-27B-Flash-V2-Apostate-Uncensored-i1-GGUF — model update ↗
## About weighted/imatrix quants of https://huggingface.co/veldierin/Qwopus3.8-27B-Flash-V2-Apostate-Uncensored ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Qwopus3.8-27B-Flash-V2-Apostate-Uncensored-i1-GGUF).*** static quants are available at https://huggingface.co/mradermacher/Qwopus3.8-27B-Flash-V2-Apostate-Uncensored-GGUF **This is a vision model - mmproj files (if any) will be in the [static repository](https://huggingface.co/mradermacher/Qwopus3.8-27B-Flash-V2-Apostate-Uncensored-GGUF).** ## Usage If you are unsure how to u
- arXiv · Published · First archived
Moore, Escher, Penrose: A Conformal Golden Braid ↗
I don't think I have ever done anything as peculiar in my life. Among other things, it shows a young man looking with interest at a print on the wall of an exhibition that features himself. How can this be? Perhaps I am not far removed from Einstein's curved universe.'' So wrote M.C. Escher about his 1956 lithograph Print Gallery. Nearly half a century later, a mathematical analysis related its geometry to an untwisted source image through a conformal power map $z \mapsto z^α$, $α\in \mathbb{C}$. Building on this construction, we use a frozen text-to-image diffusion model to generate new self-…
- arXiv · Published · First archived
Sphere Encoder 2 ↗
Sphere Encoder is an autoencoder that generates images by decoding random points from a high-dimensional latent sphere. We identify two limitations of the original formulation that reduce its generation quality. First, random points concentrate near the equator relative to the pole on an encoded latent, but the training rotation never reaches this region, leaving a gap that limits one-step generation. Second, training for generation with pixel-wise reconstruction loss encourages the decoder to average over plausible images, producing blurry images that lack high-frequency details. We present S…
- arXiv · Published · First archived
One Basis to Animate Them All: Gaussian Blendshape Distillation for Real-Time Avatars ↗
3D Gaussian avatars support fast rendering, however, their real-time animation is often challenged by the costly neural inference. We address this bottleneck and show that the animation of pretrained avatar models can be closely approximated by a linear combination of identity-independent blendshapes. Building on this finding, we introduce GALA (Gaussian Animation via Linear Approximation), a distillation method that replaces per-frame heavy neural decoding with a shallow coefficient predictor and a linear blend. To improve fidelity and reduce memory requirements, we propose to construct the b…
Live window recorded . This is the ingestion observation time, not the publication or discovery date of each source.
How to assess evidence about Artificial Intelligence
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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