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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 ↗5962 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
Anthropic/OpenAI sound alarm on AI safety and seek to shape how to control it ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Ask HN: What am I missing with Siri AI? ↗
I have a lot of experience with LLM’s and have seen them become very good at interacting with tools within an environment. I’m truly amazed at how poorly the new Siri is at handling very basic requests for basic interactions with different parts of the ecosystem. I’m really beginning to question whether LLM technology is being leveraged at all here. What am I missing with this? I have tons of examples where it fumbles softball requests. For examp…
- Hacker News · Posted on Hacker News · First archived
Google OpenAI Anthropic Begin Forming SAFA – Standards Authority for Frontier AI ↗
Hacker News discussion.
- arXiv · Published · First archived
Autonomous phase discovery ↗
Understanding quantum phases of matter has long relied on physicists' intuition and mathematical tools such as symmetry and topology. Remarkably successful as these approaches have been, they provide no universal way to explore a Hamiltonian space whose organizing principle is not known in advance. In this work, we introduce a fully autonomous system combining differentiable programming and unsupervised learning for quantum phase discovery. The search evaluates ground-state data along an adaptive trajectory rather than on a predetermined parameter grid. We demonstrate the system with three dif…
- Hacker News · Posted on Hacker News · First archived
The NSA Is Spending Billions to Test AI Models, Classified Estimates Show ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Deming in the machine running an AI assisted film ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
SNL Weekend Update: Anthropic CEO Dario Amodei on A.I.'S Threat to Humanity [video] ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Calling the AI bluff: Adding "Do not guess" cut made-up claims from 71% to 20% ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Show HN: Claude on a 2007 Nokia 6300 (Java ME app, TLS 1.0, private CA) ↗
Hacker News discussion.
- arXiv · Published · First archived
Taming the Greeks: Option Portfolios with Inductive Biases ↗
We present an end-to-end deep learning framework for systematic options trading that directly embeds hedging behavior through explicit control of portfolio-level risk exposures. While neural networks trained to optimize risk-adjusted performance have been shown to outperform traditional rules-based strategies, such approaches remain agnostic to the sensitivities of the resulting portfolios with respect to specific underlying risk factors. We propose a general training objective that combines a performance-driven loss with a differentiable risk-sensitivity penalty, enforcing neutrality to selec…
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.