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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 ↗6031 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
Author Dropped from Literary Prize over AI Allegations ↗
Hacker News discussion.
- arXiv · Published · First archived
Selective Channel Restoration for Backdoored Vision-Language Models ↗
Vision-language models (VLMs) exhibit strong multimodal capabilities but remain vulnerable to backdoors implanted through poisoned fine-tuning data. Existing defenses often require extensive parameter updates during fine-tuning or incur per-query overhead during inference. To address these limitations, we propose Perturb-Select-Restore (PSR), a post-training defense that performs sparse updates to the projection interface and introduces no additional computation during inference. We reveal that backdoored VLM projectors are substantially more sensitive to bounded perturbations than clean VLM p…
- Hacker News · Posted on Hacker News · First archived
AI: Igniting the Spark to End Stagnation ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Antifragile Programming and Why AI Won't Steal Your Job ↗
Hacker News discussion.
- Hugging Face · Model / dataset date · First archived
ASKabalan/jax-fli-experiments — dataset update ↗
# jax-fli experiments Data, samples, and reference catalogs for the [`jax-fli`](https://github.com/ASKabalan/jax-fli) forward-modelling experiments. Each experiment is exposed as one or more HuggingFace dataset *configs*; load a config with `datasets.load_dataset`. ## Experiment 00 — CosmoGrid reference A single CosmoGrid simulation (`cosmo_000001`) packaged as `jax-fli` `Catalog` parquet files, used as reference truth for the lensing / masked-shear experiments. | Config | Field | Shape | NSIDE | Description | |--------|-------|-------|-------|-------------| | `00-cosmogrid-000001-density` | `
- Hacker News · Posted on Hacker News · First archived
Claude suddenly stopped cheating – Drone Bench ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Tinfoil – Private AI Built on Secure Hardware ↗
Hacker News discussion.
- arXiv · Published · First archived
Where Do LLMs Decide to Break the Rules? Mechanistic Localization of Prompt Injection Compliance ↗
When a prompt injection attack succeeds, a Large Language Model (LLM) abandons its assigned system role to comply with an adversarial instruction. While prior work has extensively quantified how often this occurs, we ask a more fundamental question: where inside the network does the model actually decide to break the rules? Using layer-by-layer causal activation patching across five models (4B to 32B parameters), we find a clear dissociation: attack information is linearly decodable from the first layer, yet causal leverage over the model's behavior is negligible until a late-layer bottleneck…
- Hacker News · Posted on Hacker News · First archived
Emulate AI ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Coding, AI, and descending a scree slope ↗
Hacker News discussion.
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.
See the collection and counting methodology ↗ · Read the weekly synthesis ↗
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These navigation suggestions are part of the map’s editorial structure, rather than measured evidence of a connection.