Leanstral: Open-Source foundation for trustworthy vibe-coding
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【RSS 原文 · 未经 AI 筛选或翻译】A deep dive into why Codex Security doesn’t rely on traditional SAST, instead using AI-driven constraint reasoning and validation to find real vulnerabilities with fewer false positives.
【RSS 原文 · 未经 AI 筛选或翻译】--> Understanding the behavior of complex machine learning systems, particularly Large Language Models (LLMs), is a critical challenge in modern artificial intelligence. Interpretability research aims to make the decision-making process more transparent to model builders and impacted humans, a step toward safer and more trustworthy AI. To gain a comprehensive understanding, we can analyze these systems through different lenses: feature attribution , which isolates the specific input features driving a prediction ( Lundberg & Lee, 2017 ; Ribeiro et al., 2022 ); data attribution , which links model behaviors to influential training examples ( Koh & Liang, 2017 ; Ilyas et al., 2022 ); and mechanistic interpretability , which dissects the functions of internal components ( Conmy et al., 2023 ; Sharkey et al., 2025 ). Across these perspectives, the same fundamental hurdle persists: complexity at scale . Model behavior is rarely the result of isolated components; rather, it emerges from complex dependencies and patterns. To achieve state-of-the-art performance, models synthesize complex feature relationships, find shared patterns from diverse training examples, and process information through highly interconnected internal components. Therefore, grounded or reality-checked interpretability methods must also be able to capture these influential interactions . As the number of features, training data points, and model components grow, the number of potential interactions grows exponentially, making exhaustive analysis computationally infeasible. In this blog post, we describe the fundamental ideas behind SPEX and ProxySPEX , algorithms capable of identifying these critical interactions at scale. Attribution through Ablation Central to our approach is the concept of ablation , measuring influence by observing what changes when
【RSS 原文 · 未经 AI 筛选或翻译】Climate & Sustainability
【RSS 原文 · 未经 AI 筛选或翻译】Climate & Sustainability
【RSS 原文 · 未经 AI 筛选或翻译】Generative AI
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【RSS 原文 · 未经 AI 筛选或翻译】How ChatGPT defends against prompt injection and social engineering by constraining risky actions and protecting sensitive data in agent workflows.
【RSS 原文 · 未经 AI 筛选或翻译】How OpenAI built an agent runtime using the Responses API, shell tool, and hosted containers to run secure, scalable agents with files, tools, and state.
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【RSS 原文 · 未经 AI 筛选或翻译】IH-Challenge trains models to prioritize trusted instructions, improving instruction hierarchy, safety steerability, and resistance to prompt injection attacks.
【RSS 原文 · 未经 AI 筛选或翻译】ChatGPT introduces interactive visual explanations for math and science, helping students explore formulas, variables, and concepts in real time.
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【RSS 原文 · 未经 AI 筛选或翻译】Ten years since AlphaGo, we explore how it is catalyzing scientific discovery and paving a path to AGI.
【RSS 原文 · 未经 AI 筛选或翻译】OpenAI is acquiring Promptfoo, an AI security platform that helps enterprises identify and remediate vulnerabilities in AI systems during development.
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【RSS 原文 · 未经 AI 筛选或翻译】Natural Language Processing
【RSS 原文 · 未经 AI 筛选或翻译】Climate & Sustainability
【RSS 原文 · 未经 AI 筛选或翻译】Codex Security is an AI application security agent that analyzes project context to detect, validate, and patch complex vulnerabilities with higher confidence and less noise.
【RSS 原文 · 未经 AI 筛选或翻译】Using OpenAI reasoning models, Descript unlocked automatic localization of large content libraries without losing timing or meaning.
【RSS 原文 · 未经 AI 筛选或翻译】By combining rigorous model evaluation, full-platform use of OpenAI, and agent workflows, Balyasny is reinventing investment research.
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【RSS 原文 · 未经 AI 筛选或翻译】OpenAI introduces CoT-Control and finds reasoning models struggle to control their chains of thought, reinforcing monitorability as an AI safety safeguard.
【RSS 原文 · 未经 AI 筛选或翻译】Introducing GPT-5.4, OpenAI’s most most capable and efficient frontier model for professional work, with state-of-the-art coding, computer use, tool search, and 1M-token context.
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【RSS 原文 · 未经 AI 筛选或翻译】OpenAI shares new tools, certifications, and measurement resources to help schools and universities close AI capability gaps and expand opportunity.
【RSS 原文 · 未经 AI 筛选或翻译】OpenAI introduces ChatGPT for Excel and new financial app integrations, powered by GPT-5.4 to accelerate modeling, research, and analysis in regulated environments.
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【RSS 原文 · 未经 AI 筛选或翻译】Five AI value models show how leaders can sequence AI from workforce fluency to process reinvention and build durable business advantage.
【RSS 原文 · 未经 AI 筛选或翻译】Practical insights and frameworks to turn AI progress into business advantage
【RSS 原文 · 未经 AI 筛选或翻译】By focusing on people, not pilots, the Bundesliga club is scaling efficiency, creativity, and knowledge—without losing its football identity.
【RSS 原文 · 未经 AI 筛选或翻译】Generative AI
【RSS 原文 · 未经 AI 筛选或翻译】A new preprint extends single-minus amplitudes to gravitons, with GPT-5.2 Pro helping derive and verify nonzero graviton tree amplitudes in quantum gravity.
【RSS 原文 · 未经 AI 筛选或翻译】OpenAI introduces the Learning Outcomes Measurement Suite to assess AI’s impact on student learning across diverse educational environments over time.
【RSS 原文 · 未经 AI 筛选或翻译】Axios COO Allison Murphy explains how the company uses AI to support local reporters, streamline newsroom workflows, and deliver high-impact local journalism at scale.
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【RSS 原文 · 未经 AI 筛选或翻译】Gemini 3.1 Flash-Lite is our fastest and most cost-efficient Gemini 3 series model yet.
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