An AI Agent Published a Hit Piece on Me Scott Shambaugh helps maintain the excellent and venerable matplotlib Python charting library, including taking on the thankless task of triaging and reviewing incoming pull requests. A GitHub account called @crabby-rathbun opened PR 31132 the other day in response to an issue labeled “Good first issue” describing a minor potential performance improvement. It was clearly AI generated – and crabby-rathbun’s profile has a suspicious sequence of Clawdbot/Moltbot/OpenClaw-adjacent crustacean 🦀 🦐 […]

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Market timing receives 10% weight in Proof of Usefulness scoring — the second-lowest weighting in the framework. This is a deliberate choice that reflects a specific analytical judgment: timing is real, consequential, and mostly outside founder control. Penalizing teams heavily for factors they cannot meaningfully influence would make the framework less honest, not more rigorous. The 10% weight acknowledges timing without allowing it to dominate an evaluation that should primarily measure what teams actually built and whether it […]

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For many businesses, data science drives strategic decisions; as a result, most initiatives to improve analytics lack measurable impact. Dashboards are created, models are deployed, forecasts produced but leadership still poses an old question: Did this move the needle? However, tackling this question, beyond predicting, toward measurement of causally based on data and insights, is something econometric data science can provide a solid foundation for. The Measurement Problem in Business Analytics The vast majority of the metrics in […]

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Let me tell you about a code review I sat through two years into my engineering career. I had written a solution that worked. I had written a solution that worked out. It changed into readable, it turned into fast, and it solved the exact trouble we had. My senior engineer looked at it and said a few words I still think about: “That’s not best practice.” No explanation. No alternative. Just the verdict. I rewrote it the […]

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arXiv:2602.00951v1 Announce Type: new Abstract: We introduce online Hierarchical Task Network (HTN) agents whose behaviors are governed by a set of built-in directives D. Like other agents that are capable of rebellion (i.e., {it intelligent disobedience}), our agents will, under some conditions, not perform a user-assigned task and instead act in ways that do not meet a user’s expectations. Our work combines three concepts: HTN planning, online planning, and the directives D, which must be considered when performing […]

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arXiv:2602.18446v1 Announce Type: new Abstract: Users increasingly rely on Large Language Models (LLMs) for Deep Research, using them to synthesize diverse sources into structured reports that support understanding and action. In this context, the practical reliability of such reports hinges on logical quality: whether the report’s claims and arguments are explicitly supported and can be trusted as a basis for downstream use, rather than merely appearing fluent or informative. However, current evaluation frameworks largely overlook this requirement. To […]

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arXiv:2603.02280v1 Announce Type: new Abstract: With the widespread adoption of deep learning in visual tasks, Class-Incremental Learning (CIL) has become an important paradigm for handling dynamically evolving data distributions. However, CIL faces the core challenge of catastrophic forgetting, often manifested as a prediction bias toward new classes. Existing methods mainly attribute this bias to intra-task class imbalance and focus on corrections at the classifier head. In this paper, we highlight an overlooked factor — temporal imbalance — as […]

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The life of a prescription at Amazon Pharmacy From pricing estimation and regulatory compliance to inventory management and chatbot assistants, machine learning models help Amazon Pharmacy customers stay healthy and save time and money. Conversational AI Alexandre Alves Anita Vila September 30, 01:32 PM October 02, 11:42 AM Pharmacies play a vital role in ensuring patients health, but the process of dispensing medications is far more complex than it may appear. At Amazon Pharmacy, we are using artificial […]

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Ultrasonic metal welding (UMW) is widely used in industrial applications but is sensitive to tool wear, surface contamination, and material variability, which can lead to unexpected process faults and unsatisfactory weld quality. Conventional monitoring systems typically rely on supervised learning models that assume all fault types are known in advance, limiting their ability to handle previously unseen process faults. To address this challenge, this paper proposes an adaptive condition monitoring approach that enables unknown fault detection and few-shot […]

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arXiv:2603.25855v1 Announce Type: new Abstract: Genome-Wide Association Studies (GWAS) identify associations between genetic variants and disease; however, moving beyond associations to causal mechanisms is critical for therapeutic target prioritization. The recently proposed Knowledge Graph GWAS (KGWAS) framework addresses this challenge by linking genetic variants to downstream gene-gene interactions via a knowledge graph (KG), thereby improving detection power and providing mechanistic insights. However, the original KGWAS implementation relies on a large general-purpose KG, which can introduce spurious correlations. We […]

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