April 2026

Building used to be the bottleneck. Now it’s everything that comes after. Image sourced from Abhiram Kakarla’s LinkedIn You ship a working product in twelve hours. Auth, payments, a clean dashboard, even some halfway-decent onboarding copy. The model keeps up, you keep prompting, and somewhere around hour ten you start feeling that specific kind of high — the one where you’re convinced this is the thing. You post the link. You lean back. You wait. Three days later, your only signups are you, […]

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In this quiz, you’ll test your understanding of Python’s __all__: Packages, Modules, and Wildcard Imports. By working through this quiz, you’ll revisit how wildcard imports work, what role the __all__ variable plays in modules and packages, and how to define a clean public API for your Python code. You’ll need to know the basics of Python modules and packages and the import system to get the most out of this quiz. Good luck! [ Improve Your Python With […]

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Purpose: With the growing interest in multimodal large language models (MLLMs) for medical image analysis, expanding the application scope of the unimodal TAIDE large-scale language model has emerged as a prominent and significant research direction. Methods: This study employed the SkinCAP multimodal dataset, which consists 4,000 images of skin lesions along with their associated textual descriptions. Two approaches for model training and evaluation are proposed: (1) A visual retrieval-augmented generation (RAG) method, which leverages transfer learning for image […]

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I am a research mathematician that has recently written a (in my opinion) pretty neat paper in theoretical computer science that is probably of more interest to machine learning researchers than to fellow mathematicians. I’m therefore seeking to place it in machine learning venues. It’s rather long (60 pages) and I have no particular desire to engage with conference culture, so therefore I’m thinking a journal rather than a conference. What are the good journals in ML or […]

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Introduction: The Cost Illusion AI agents look cheap and powerful at first. You send one request and get a smart answer. They can write emails, search information, automate tasks, and even make decisions. In demos, everything feels fast, simple, and scalable. But that is not how they actually work. What looks like one request is usually many steps happening behind the scenes. The agent does not just respond. It breaks the task down, decides what to do, tries […]

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Real-time scheduling of large-scale electric vehicle (EV) charging stations is essential for improving service efficiency, operational profitability, and grid coordination. However, most existing studies formulate charging scheduling as a single-stage unified decision problem that jointly handles discrete service access and continuous power control. Such a formulation fails to capture the inherently hierarchical operating mechanism of large-scale charging stations and often suffers from limited interpretability, enlarged action spaces, and reduced scalability under stochastic arrivals, dynamic departures, and time-varying resource […]

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This position paper argues that delegated AI must be evaluated and governed by transaction closure, rather than mere task completion. Agent economies emerge when AI systems execute externally binding commitments—such as purchases, bookings, or procurement orders—on behalf of authorized principals. Safe delegation at this boundary requires environments that support bounded mandates, reversible lifecycle states, verifiable receipts, and contestable failures. While AI-native platforms rapidly advance action closure, mature super-app ecosystems and enterprise suites currently offer the clearest testbeds for […]

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AI agents are rapidly evolving from static models into dynamic, decision-making systems capable of acting independently. Whether used in trading, customer service, cybersecurity, or market intelligence, these agents rely on one critical element: data that is constantly refreshed, validated, and updated. Without this, even the most advanced AI agent becomes outdated, inaccurate, and ultimately ineffective. This is where continuously regenerating data pipelines come into play. These pipelines ensure that AI agents are not just trained once but are […]

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UAV-based crack inspection of port quay walls is promising for efficient infrastructure maintenance, but its practical deployment remains hindered by frequent false positives caused by debris, stains, and irregular surface textures. This study proposes a false-positive reduction framework for a crack inspection system based on aerial images acquired by a small general-purpose UAV. The proposed method introduces anomaly detection after object detection so that detected crack candidate regions are re-evaluated based on their deviation from the learned feature […]

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