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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 ↗5996 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
Prompting Claude Opus 5.5 ↗
Hacker News discussion.
- arXiv · Published · First archived
Deep kernel hedging ↗
We introduce a deep kernel hedging framework that combines the flexibility of deep learning with the structural inductive bias of kernel methods. The hedging functional is restricted to a reproducing kernel Hilbert space whose kernel is parameterized through a neural network embedding of the input features. The framework minimizes a regularized empirical risk under convex loss functions and can accommodate path-dependent information through truncated time-augmented signature features. We derive a generalized representer theorem for the joint hedging problem, reducing the empirical optimization…
- GitHub · Repository created · First archived
kaithoughtarchitect/titration ↗
Let your coding agent fix a prompt until it actually works, and prove it did. A self-hosted MCP server: cross-vendor judges, frozen baselines and memory.
- Hugging Face · Model / dataset date · First archived
kennyhyder/sportsbookish-daily-odds — dataset update ↗
# SportsBookISH Daily Kalshi vs Sportsbook Odds > Real-time pricing snapshot comparing Kalshi event-contract probabilities against US sportsbook consensus across nine sports. ## Description Daily-refreshed JSON / CSV export of every active Kalshi market alongside the de-vigged book median across 13+ US sportsbooks. Covers golf (PGA Tour), NFL, NBA, MLB, NHL, EPL, MLS, UEFA Champions League, and FIFA World Cup. ## Source Live data plane: - JSON: https://hyder.me/api/data/daily-odds - CSV: https://hyder.me/api/data/daily-odds-csv Refreshed hourly server-side; this Hugging Face mirror is updated
- Hugging Face · Model / dataset date · First archived
voves/GigaChat3.5-432B-A28B-Reasoning-NVFP4 — model update ↗
# GigaChat3.5-432B-A28B-Reasoning-NVFP4 NVFP4-quantized version of [ai-sage/GigaChat3.5-432B-A28B-Reasoning-bf16](https://huggingface.co/ai-sage/GigaChat3.5-432B-A28B-Reasoning-bf16). Please refer to the original model card and the usage license before use. > All scores were obtained on our own inference setup (sglang, TP=4 across 4 GPUs) > as close as possible to the bf16 card, though differences in system prompts, answer parsing, and token > budgets are possible. Some of the card's benchmarks are not reproducible outside the vendor. ## Comparison with the bf16 reference All runs: temperature
- Hugging Face · Model / dataset date · First archived
RAS-LAB/GLM-4.7-Flash-24B-A3B-KREAP — model update ↗
# GLM-4.7-Flash-24B-A3B-KREAP — Force-Fit Ablation Korean-priority one-shot MoE Expert pruning of [zai-org/GLM-4.7-Flash](https://huggingface.co/zai-org/GLM-4.7-Flash), produced with [K-REAP](https://github.com/Chedrian07/K-REAP). [한국어 요약](README_ko.md) Routed Experts were pruned **64 → 48 per layer (25.0%)** while top-4 routing was kept unchanged. This percentage is the reduction in routed Expert count, not total model parameters. `A3B` follows the base model's approximate active-parameter class because top-4 routing is unchanged, not a new active-parameter measurement The checkpoint contains
- Hacker News · Posted on Hacker News · First archived
Show HN: FAB – A benchmark for AI agents doing financial due diligence ↗
The world economy around us depends on complex financial work. How well can AI do it? We(a team of ex-EY employees) built FAB - Finance Agents Benchmark, testing AI Agents on the work behind financial due diligence. Agents can find the relevant facts, but still struggle to carry them through to a complete, reliable analysis. We’ll keep expanding FAB to more companies and testing more models. Building and running this benchmark isn’t cheap, so we’…
- Hacker News · Posted on Hacker News · First archived
Using AI to develop software while being Anti-AI ↗
Hey yall, so I've kinda started understanding why people tend to hate on AI, I found myself in a situation where I would stop thinking myself, I stopped evaluating whether my issue could be fixed by just using my damn brain. So I just wanted to stop for a few months, just see what will happen. Tho my biggest issue now: I am a Full-Stack Dev and of course I could again write my code 100% myself, tho using Tools like Claude for writing pipelines te…
- Hacker News · Posted on Hacker News · First archived
Show HN: I Made Agent Office ↗
A pixel-art office where your Claude Code sessions come to life as coworkers. Found myself staring at nothing while working and prompting so I thought I could make my agents "look alive" at least
- Hacker News · Posted on Hacker News · First archived
LLM capabilities can transfer through unrelated text ↗
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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