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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 ↗5205 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.
- Hacker News · Posted on Hacker News · First archived
Ask HN: How to deal with just being a PR reviewer for LLMs nowadays ↗
I know .. architecture is important and yes it is also fun to figure it out, but apart from that all that was fun for me is done by AI nowadays and I am basically a PR reviewer for Claude now. And I hate it. I am looking at a terminal window half of the day and have to figure out what the LLM wants to do ... depending on much Anthropic nervs the model, this can be easy or it still invents words and I have to check every detail. My brain feels lik…
- Hacker News · Posted on Hacker News · First archived
Man charged with planting 'sophisticated' recording device in OpenAI office ↗
Hacker News discussion.
- Hugging Face · Model / dataset date · First archived
mradermacher/oh-dcft-v3.1-gemini-1.5-flash-qwen-GGUF — model update ↗
## About static quants of https://huggingface.co/mlfoundations-dev/oh-dcft-v3.1-gemini-1.5-flash-qwen ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#oh-dcft-v3.1-gemini-1.5-flash-qwen-GGUF).*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/oh-dcft-v3.1-gemini-1.5-flash-qwen-i1-GGUF ## Usage If you are unsure how to use GGUF files, refer to one of [TheBloke's READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for more details, including on how to concatenate multi-part files. ## Pro
- Hugging Face · Model / dataset date · First archived
mradermacher/gemma3-4b-tolkien-GGUF — model update ↗
## About static quants of https://huggingface.co/berkaygkv54/gemma3-4b-tolkien ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#gemma3-4b-tolkien-GGUF).*** weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion. ## Usage If you are unsure how to use GGUF files, refer to one of [TheBloke's READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for m
- GitHub · Repository created · First archived
zr9959/auto-xhs ↗
小红书全自动化运营发布（适配muse、Dots、Grok Bot）
- Hacker News · Posted on Hacker News · First archived
Character.ai's Bankruptcy Documents Show the Economics of AI Don't Work ↗
Hacker News discussion.
- Hugging Face · Model / dataset date · First archived
mradermacher/MiniCPM-V-4.7-35B-A3B-GGUF — model release ↗
## About static quants of https://huggingface.co/openbmb/MiniCPM-V-4.7-35B-A3B ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#MiniCPM-V-4.7-35B-A3B-GGUF).*** weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion. ## Usage If you are unsure how to use GGUF files, refer to one of [TheBloke's READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) f
- Hugging Face · Model / dataset date · First archived
lackonendes/PAW-125B-FLASH-NEXT-X3.1 — model update ↗
# PAW-125B-FLASH-NEXT-X3.1 _If this model is useful to you, support the work by following [@nawariokra](https://x.com/nawariokra) on X._ **`Qwen/Qwen3.8-Flash-Next` (125B MoE, 6B active) on one or two 24 GB GPUs plus CPU, with the full 262,144-token context.** Two GGUF shards: **47.5 GiB of weights** and a 48.3 GiB n-gram table (95.8 GiB in all). It runs on our own engine [TRUSS](https://github.com/irawanw/truss). | | | |---|---| | model | Qwen3.8-Flash-Next: 48 layers (36 Gated DeltaNet + 12 sparse-attention), 512 experts per layer, 10 routed + 1 shared per token | | experts | 24,576 routed e
- Hugging Face · Model / dataset date · First archived
huihui-ai/Huihui-Qwen3.8-27B-Coder390-EfficientThink-abliterated-GGUF — model release ↗
# huihui-ai/Huihui-Qwen3.8-27B-Coder390-EfficientThink-abliterated-GGUF This is an uncensored version of [nerkyor/Qwen3.8-27B-Coder390-EfficientThink-Opus5.5-GPT6Astra-Grok4.7-DSV4Pro-K3-SFT-RLOO-MTP-DFlash2](https://huggingface.co/nerkyor/Qwen3.8-27B-Coder390-EfficientThink-Opus5.5-GPT6Astra-Grok4.7-DSV4Pro-K3-SFT-RLOO-MTP-DFlash2) created with abliteration (see [remove-refusals-with-transformers](https://github.com/Sumandora/remove-refusals-with-transformers) to know more about it). This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using Transforme
- GitHub · Repository created · First archived
HY-LiYihan/agentic_rsr ↗
Agentic RSR: Real-to-Sim-to-Real through Scene Reconstruction and Execution-Grounded Robot Policies
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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