Shannon
PulseAugur coverage of Shannon — every cluster mentioning Shannon across labs, papers, and developer communities, ranked by signal.
3 day(s) with sentiment data
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AI pentester Shannon gains 50K GitHub stars; Ropes & Gray partners with OpenAI on diligence tool
An open-source AI pentester named Shannon, developed by Keygraph, has achieved 50,000 GitHub stars. Separately, the law firm Ropes & Gray is developing an AI tool for transactional diligence in collaboration with OpenAI…
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LLM-driven pentesting frameworks mapped by reasoning and productization
A new field guide categorizes twelve LLM-driven penetration testing frameworks based on where reasoning occurs and the level of product wrapping. The analysis, derived from public repositories and documentation, highlig…
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Shannon AI Pentester Enhances Web App and API Security
Shannon is an AI pentester designed to enhance cybersecurity for web applications and APIs. This tool aims to integrate static analysis with live penetration testing capabilities. The third part of a series on AI in cyb…
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New theory separates information preservation from predictive contribution
A new paper introduces Complementary Feature Domains (CFD) theory, which characterizes predictive value as a context-indexed contribution system. The research demonstrates that preserving Shannon information does not ne…
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New framework links language redundancy to semantic text structure
Researchers have introduced a new framework to understand the statistical organization of language, linking its redundancy to hierarchical semantic structures. By using large language models to recursively segment texts…
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New IDE tool FairLint-DL enables pre-training bias detection in deep learning
Researchers have developed FairLint-DL, a new tool integrated into Visual Studio Code that allows developers to test for bias in deep learning models before training. The tool uses information-theoretic metrics based on…
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New theory unifies AI communication, control, and decision-making
A new paper proposes a mathematical framework for pragmatic information theory, aiming to unify communication, control, and decision-making. The theory introduces the concept of isoteleia, which formalizes the idea that…
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Withdrawn paper explores information entropy as anthropomorphic concept
This paper, originally submitted in 2015 and later withdrawn, explores the concept of information entropy as an anthropomorphic idea, drawing parallels with thermodynamic entropy as described by E.T. Jaynes and Eugene P…
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Researchers use Łukasiewicz logic to identify deep ReLU networks
Researchers have developed a novel method to completely identify deep ReLU networks by employing Łukasiewicz logic. This approach parallels Shannon's analysis of switching circuits using Boolean logic, translating netwo…
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New attention operators derived from generalized statistical entropies
Researchers have introduced novel attention operators derived from generalized statistical entropies, moving beyond standard Softmax and entmax functions. The Kaniadakis entropy operator offers algebraic decay in weight…
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New research quantifies multilingual tokenization tax, finding it largely removable
A new research paper proposes a "token-cost ledger" to quantify the extra cost associated with processing non-English text in large language models. The study, which analyzes eight languages on the FLORES-200 dataset, f…
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Shannon and Turing Predicted AI in 1943
In 1943, Claude Shannon and Alan Turing independently theorized about the potential for artificial intelligence. Their work laid foundational concepts that would later influence the development of AI.
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Misuse of 'curve overfitting' term in LLM context highlighted
The term "curve overfitting" is being misused when applied to large language models that reproduce verbatim fragments of their training data. This specific behavior is not true overfitting, which refers to models perfor…
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New Game Theory Method Achieves Sublogarithmic Swap Regret
Researchers have developed a new method for multiplayer general-sum games that significantly reduces swap regret, improving convergence to correlated equilibria. This novel approach combines the Blum--Mansour reduction …
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New algorithm uses information theory to find formulaic text clusters
Researchers have developed a novel information-theoretic algorithm to identify formulaic clusters within textual data. This method utilizes weighted self-information distributions, extending classical measures to a cont…
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New MINT-V2X dataset integrates vehicle mobility and network data
Researchers have introduced MINT-V2X, a new dataset designed to bridge the gap in vehicle-to-everything (V2X) communication research by integrating both mobility and wireless network parameters. This comprehensive datas…
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LLM aids discovery of new lower bounds for Shannon capacity of odd cycles
Researchers have developed new methods to establish improved lower bounds for the Shannon capacity of odd cycles, specifically C7, C11, and C13. These advancements were achieved by constructing specific independent sets…
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Neuro-Symbolic AGI Research Explores Logic, Probability for Advanced Robots · 2 sources tracked
Two new research papers explore the integration of neuro-symbolic approaches for Artificial General Intelligence (AGI) robots. The first paper introduces a framework using Belnap's bilattice and the Closed Knowledge Ass…
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New Mathematical Theory Quantifies Value in Goal-Directed Agents
Researchers have developed a new mathematical framework to quantify value, defining it as the rate at which goal-directed agents convert resources into progress relative to their objectives. This theory, drawing paralle…
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New geometric framework measures semantic information in text
Researchers have developed a new geometric framework to measure the semantic information contained within a text. This framework, detailed in a recent paper, offers a three-coordinate semantic profile that captures nove…