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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 ↗5927 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
Welcoming Jürgen Schmidhuber to Sakana AI ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
AI doomers may be wrong but the skeptics seem even wronger ↗
Hacker News discussion.
- arXiv · Published · First archived
Era by Eon: Benchmarking Enterprise Agents on Hidden Knowledge ↗
In the Era by Eon benchmark, each question states the rules for its answer, and code computes the answer from a generated company's data. When agents can run code, the four strongest models each answer 22 to 25 of 27 such questions, so the benchmark barely separates them. We add eight question templates that depend on hidden facts. No question or document states a hidden fact, and the records that seem to hold it show something else. Other data implies it. For example, the sales system says a customer dropped a purchase because of timing. On a recorded call, the customer blames an outage. For…
- arXiv · Published · First archived
Style, Not Self: Surface Cues Explain Zero-Shot Code Attribution by Large Language Models ↗
If a language model can recognize code it wrote, it may favor that code as a judge, and instances of one model monitoring each other could collude. We test this zero-shot on current commercial models. Five LLMs generate solutions to MBPP, HumanEval, and DS-1000, seven more to MBPP, and models act as evaluators in four tasks: picking their own solution from a pair, judging whether a single solution is their own, identifying which of two solutions a named model wrote, and judging quality blind. In the single-solution task, balanced accuracy is 49-58% for all 15 model-benchmark combinations, whil…
- arXiv · Published · First archived
AERIAL: Adversarial Evaluation of Robustness in Accuracy-Preserving Low-Precision EEG Decoders ↗
Deployment-oriented compression is attractive for resource-constrained brain--computer interfaces (BCIs), but whether it changes adversarial vulnerability remains unclear. On BCI Competition IV-2a, we compare 32-bit floating-point (FP32) EEGNet and ShallowConvNet models with global magnitude pruning and simulated INT8 post training quantization (PTQ) and quantization-aware training (QAT) across nine subjects and three seeds. Simulation provides differentiable quantize--dequantize models for white-box attacks and gradient analysis, while native TensorRT deployment is used for validation. Accura…
- Hacker News · Posted on Hacker News · First archived
I Have a Confession: I Built This Site with AI – Please Forgive Me ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Show HN: Trify3D – Compare AI 3D engines on one input and keep the best mesh ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
AI Evals: Everything You Need to Know ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Show HN: Potluck – Run local AI across the computers you own ↗
Hey All, my name is Rob and i've been working on Potluck for a couple of months. The idea is pretty simple... I can't afford a huge cluster of machines, nor can I afford a bunch of GPUs or cloud instances. But I do have a couple of laptops, a couple of gaming computers and I figured why can't I just map those machines together to run larger models? Potluck allows you to do this very thing. The goal and what i'm working on currently is to have a n…
- Hacker News · Posted on Hacker News · First archived
Agent-Manager: Reviewing code while an AI agent is still rewriting it ↗
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.
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These navigation suggestions are part of the map’s editorial structure, rather than measured evidence of a connection.