Noticias

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IAarxiv.org·hace 2 sem·auto

TACS-RF: Tool-driven Agentic Circuit Synthesis of RF and mmWave Modules

arXiv:2610.31882v1 Announce Type: new Abstract: We present the framework of TACS-RF - a Tool-driven Agentic Circuit Synthesis of RF and mmWave modules. In this framework, a large-language-model (LLM) coding agent (Claude Opus 4.8) directly drives industry-standard electronic-design-automation (EDA) tools such as Cadence Virtuoso/Spectre, Calibre, Cadence EMX, and Ansys HFSS to design RF and mmWave modules. We validate the framework through the agentic design of a 240-251 GHz sub-THz transmitter

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Softwarehnrss.org·hace 3 sem·auto

Show HN: VoidAccess – open-source dark web OSINT, from query to a graph

Hi HN! Im Katriel, and im a Security Researcher/Enthusiast and in the wave of AI, i wanted to build that next gen of security tooling that surpasses the current tools, and even the paid industries with an open source engine. I built MailAccess as well, which is going to be the best damn email osint tool out there, in another year. But just before building MailAccess i built VoidAccess, because i was delving a lot into DarkINT and the content inside the dark web is too difficult to navigate throu

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IAarxiv.org·hace 5 sem·auto

An Explainable Header-Centric Framework for Large-Scale Semantic Table Interpretation and Data Quality Assessment

arXiv:2610.10541v1 Announce Type: new Abstract: Knowledge Graph (KG) quality depends not only on downstream graph validation, but also on the quality of tabular metadata used before integration. In metadata-only Semantic Table Interpretation (STI), where cell values are unavailable, noisy, or unsuitable, column headers become a critical source of semantic evidence for traceable KG preparation. We present an explainable, header-centric framework for metadata-only Column Type Annotation (CTA) and

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Softwarehnrss.org·hace 6 sem·auto

Launch HN: Magnitude (YC S25) – Self-optimizing inference engine for agents

Hey HN, Anders and Tom here. We're building Magnitude, an inference engine for agents that optimizes itself to run as fast as possible on your hardware. It works on Mac, Linux, and Windows on any hardware and is up to 2x faster than llama.cpp. We're both software engineers and previously built an open source browser agent to 4k+ GH stars and 100k+ downloads. We increasingly wanted to run it on local models, but found that no inference engine worked for our use case. Inference engines today all m

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IAtechnologyreview.com·hace 6 sem·auto

“We’re not going to shoot ourselves in the foot” over hack fallout, says OpenAI’s chief research officer

Two months after the bombshell news that a swarm of its agents had broken their containment and hacked into the computers of the AI company Hugging Face, OpenAI is still putting out fires. A steady drip of disclosures about other hacks in the weeks since has kept OpenAI in the spotlight and raised serious questions…

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IAtechnologyreview.com·hace 6 sem·auto

Roundtables: The Deadly Failures of The Virtual Border Wall

Listen to the session or watch below The US has spent billions building a “virtual wall” of surveillance towers along its southern border over the past 25 years, promising they will help detect and apprehend border crossers and save lives. But a groundbreaking investigation by MIT Technology Review has documented over a thousand people who…

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Softwarehnrss.org·hace 8 sem·auto

Show HN: Capsule – Single-file web apps that save their data into SQLite

Hey HN, I always had the problem that building HTML pages is really simple now, but trying to save data required hosting it somewhere, and sharing it afterwards was not easy. Over the last few months, I've been building an app called Capsule (it’s also the file extension name) written in Rust with Tauri 2.0 that allows packing an HTML app and its data into a single SQLite file. The HTML file and any related assets are directly embedded in the database. User data can either be saved as a localSto

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IAarxiv.org·hace 9 sem·auto

Iris: Climbing to the Search Frontier

arXiv:2609.04304v1 Announce Type: new Abstract: We present Iris-mini and Iris-pro, two search agents trained at the 35B-A3B and 397B-A17B scales, together with the data pipeline and training recipe behind them. Tasks are reverse-constructed from the hyperlink structure of a web corpus: we author multi-hop chains over an entity graph distilled from a seed page and its out-links, rewrite every non-answer entity into a descriptive reference so that no clue can be resolved by string matching, and ad