Biodefense in the Intelligence Age
An action plan for AI-powered biological resilience
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Rogue Trooper brings the Genetic Infantry to the silver screen
For more than 49 years, a comic called 2000 AD has been responsible for giving science-fiction junkies a weekly infusion of “thrill power.” Published in the UK, far from the action in Hollywood, its characters have crossed over from the page to the screen far less frequently than the superheroes belonging to Marvel and DC. Judge Dredd has two movies of varying quality, but attempts to follow the 2012 version with a TV show appear to have sputtered […]
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Monotone Optimisation with Learned Projections
Monotone optimisation problems admit specialised global solvers such as the Polyblock Outer Approximation (POA) algorithm, but these methods typically require explicit objective and constraint functions. In many applications, these functions are only available through data, making POA difficult to apply directly. We introduce an algorithm-aware learning approach that integrates learned models into POA by directly predicting its projection primitive via the radial inverse, avoiding the costly bisection procedure used in standard POA. We propose Homogeneous-Monotone Radial Inverse (HM-RI) […]
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Best practices for Reward Engineering in Autonomous Driving to avoid reward hacking and local optima?
Hi everyone, I am currently training an RL agent for an autonomous driving task, but I’ve hit a wall with Reward Engineering. Right now, I am stuck in a tedious, manual trial-and-error loop: The car stops completely to avoid risk -> I add a too_slow_penalty. The car then drives too aggressively at intersections -> I add an overspeed_penalty. As a result, my reward function is becoming bloated with too many heuristics and hyperparameters. Tuning one weight to fix […]
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Thermodynamic Liquid Manifold Networks: Physics-Bounded Deep Learning for Solar Forecasting in Autonomous Off-Grid Microgrids
The stable operation of autonomous off-grid photovoltaic systems requires solar forecasting algorithms that respect atmospheric thermodynamics. Contemporary deep learning models consistently exhibit critical anomalies, primarily severe temporal phase lags during cloud transients and physically impossible nocturnal power generation. To resolve this divergence between data-driven modeling and deterministic celestial mechanics, this research introduces the Thermodynamic Liquid Manifold Network. The methodology projects 22 meteorological and geometric variables into a Koopman-linearized Riemannian manifold to systematically map complex climatic dynamics. The architecture […]
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Deep Dive into Kafka Architecture: Understanding the Building Blocks and Design Principles
Introduction to Kafka and its Architectural Context Apache Kafka is a distributed event streaming platform designed to handle high-throughput, fault-tolerant data pipelines. It enables applications to publish and subscribe to streams of records in real time, providing a unified, durable, and scalable messaging backbone that supports both batch and stream processing workloads. Kafka is widely used in scenarios such as real-time analytics, where large volumes of event data must be processed with minimal delay; log aggregation, consolidating logs […]
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ProSoftArena: Benchmarking Hierarchical Capabilities of Multimodal Agents in Professional Software Environments
arXiv:2601.02399v1 Announce Type: new Abstract: Multimodal agents are making rapid progress on general computer-use tasks, yet existing benchmarks remain largely confined to browsers and basic desktop applications, falling short in professional software workflows that dominate real-world scientific and industrial practice. To close this gap, we introduce ProSoftArena, a benchmark and platform specifically for evaluating multimodal agents in professional software environments. We establish the first capability hierarchy tailored to agent use of professional software and construct a benchmark of […]
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From Consumption to Reflection: Designing Human-AI Relations for Stable Reasoning
arXiv:2606.11195v1 Announce Type: new Abstract: Large language models (LLMs) have transformed how humans access information, but not how we reason with it. Their fluency accelerates consumption while bypassing the slow, reflective processes that underpin sound judgment. This paper introduces Relational Reflective Intelligence (RRI), an inference-time governance layer that operationalizes reflection through auditable reasoning loops. RRI operates not inside the model but around it, providing a practical structure for stable, auditable reasoning between humans and LLMs. The core premise […]
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Quiz: The LEGB Rule & Understanding Python Scope
In this quiz, you’ll test your understanding of The LEGB Rule & Understanding Python Scope. By working through this quiz, you’ll revisit how Python resolves names using the LEGB rule, what the local, enclosing, global, and built-in scopes look like in practice, and how the global and nonlocal statements let you reach across scope boundaries. [ Improve Your Python With 🐍 Python Tricks 💌 – Get a short & sweet Python Trick delivered to your inbox every couple […]
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A Guide to One-Shot Learning
Passport checks at airports, automatic turnstiles in office centers, signature verification – all these tasks require face or object recognition. Historically, deep learning algorithms use a lot of labeled training data for simple tasks like identifying objects in photos or recognizing faces. But in the above situations, we normally do not possess a large variety of photos for each person for training the AI. Therefore, we need an ML algorithm that would be able to perform recognition with […]
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