The “Perfect Decision” Trap We’re entering the era where AI doesn’t just answer questions — it selects actions. Supply chain routing. Credit risk. Fraud detection. Treatment planning. Portfolio optimisation. The pitch is always the same: “Give the model data and objectives, and it will find the best move.” And in a narrow, mathematical sense, it can. But here’s the catch: optimisation is a superpower and a liability. Because if a system can optimise perfectly, it can also optimise […]

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arXiv:2604.08569v1 Announce Type: new Abstract: Traffic simulation and digital-twin calibration is a challenging optimization problem with a limited simulation budget. Each trial requires an expensive simulation run, and the relationship between calibration inputs and model error is often nonconvex, and noisy. The problem becomes more difficult as the number of calibration parameters increases. We compare a commonly used automatic calibration method, a genetic algorithm (GA), with Bayesian optimization methods (BOMs): classical Bayesian optimization (BO), Trust-Region BO (TuRBO), Multi-TuRBO, […]

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Artificial Intelligence has its own way of impressing us with its potential and wonders. It is an incredibly growing field and will definitely have an immense effect on our lives. In my opinion, automating manual labor and work sounds like an amazing idea; people wouldn’t need to bother about whether there is going to be traffic in their route to work, or you wouldn’t have to review through spelling/grammar errors in your lengthly research paper for English. AI […]

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This paper presents a hybrid model that combines linguistic data summarization techniques, algorithms for constructing probabilistic trees, and various Generative Artificial Intelligence models for learning and generating linguistic summaries to aid decision-making. The proposal is validated using methodological triangulation techniques that demonstrate high consistency in the knowledge discovered. The proposal also compares different Generative Artificial Intelligence models; among the evaluated models, Gemini achieved the best performance. However, it is evident that in certain contexts and tasks, small language […]

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In this article, I’ll show you how to unlock the full power of GitHub Copilot agents inside VS Code. There are actually three main types of Copilot agents-most people only know about one, but I’m going to show you all of them. By the end, you’ll be able to create custom agents that act as your own specialized “sub-agents.” Getting Started: The Setup Before we dive into the agents, make sure your environment is ready. Update VS Code: Ensure […]

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In this quiz, you’ll test your understanding of Testing Your Code With Python’s unittest. By working through this quiz, you’ll revisit key concepts like structuring tests with TestCase, using assertion methods, skipping tests conditionally, parameterizing with subtests, and preparing test data with fixtures. [ Improve Your Python With 🐍 Python Tricks 💌 – Get a short & sweet Python Trick delivered to your inbox every couple of days. >> Click here to learn more and see examples ]

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arXiv:2602.10282v1 Announce Type: new Abstract: Large language models (LLMs) have shown potential in identifying qualitative causal relations, but their ability to perform quantitative causal reasoning — estimating effect sizes that parametrize functional relationships — remains underexplored in continuous domains. We introduce Linear-LLM-SCM, a plug-and-play benchmarking framework for evaluating LLMs on linear Gaussian structural causal model (SCM) parametrization when the DAG is given. The framework decomposes a DAG into local parent-child sets and prompts an LLM to produce a […]

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arXiv:2602.09181v1 Announce Type: new Abstract: Exploiting the analogy between Gaussian Distributions and Gaussian Processes’ posterior, we present how the weighted Wasserstein Barycenter of Gaussian Processes (W2BGP) can be used to unify, under a common framework, different exotic Bayesian Optimization (BO) tasks. Specifically, collaborative/federated BO, (synchronous) batch BO, and multi-fidelity BO are considered in this paper. Our empirical analysis proves that each one of these tasks requires just an appropriate weighting schema for the W2BGP, while the entire framework […]

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Simply put: It’s a big mess, and no off-the-shelf accounting software does what I need. So after years of pain, I finally sat down last week and started to build my own. It took me about five days. I am now using the best piece of accounting software I’ve ever used. It’s blazing fast. Entirely local. Handles multiple currencies and pulls daily (historical) conversion rates. It’s able to ingest any CSV I throw at it and represent it […]

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arXiv:2603.08726v1 Announce Type: new Abstract: Dataflow-based CNN accelerators on FPGAs achieve low latency and high throughput by mapping computations of each layer directly to corresponding hardware units. However, layers such as pooling and strided convolutions reduce the data at their output with respect to their input, strongly effecting the data rate of the following layers. This leads to underutilization in fully unrolled designs. While prior work introduced data-rate-aware layer-wise adaptation, determining the most efficient implementation remains challenging. This […]

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