I recently tried out Minimax 2.5, which just dropped, and from what I’ve heard, the results are pretty impressive. I gave it a go on zenmux, and I have to say, it really covers a lot of ground. The flexibility, speed, and accuracy are definitely noticeable improvements. Now, I’m thinking about deploying it locally. I’ve used Ollama for deployments before, but I noticed that for Minimax 2.5, Ollama only offers a cloud version. I’m curious about other deployment […]

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Accurate long-term electrical load forecasting is required for stable smart grid operation, yet remains difficult due to multi-scale periodic patterns and non-stationary temporal shifts across different prediction horizons. This work presents MoE-Transformer, a reinforcement learning-driven dual-domain framework that integrates frequency-domain processing with sparse expert networks for adaptive forecasting. An Extended Discrete Fourier Transform (Extended DFT) is introduced to address spectral misalignment by aligning the input spectrum with the frequency grid of the full prediction window. The model employs […]

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arXiv:2602.12350v1 Announce Type: new Abstract: Many natural optimization problems derived from $sf NP$ admit bilevel and multilevel extensions in which decisions are made sequentially by multiple players with conflicting objectives, as in interdiction, adversarial selection, and adjustable robust optimization. Such problems are naturally modeled by alternating quantifiers and, therefore, lie beyond $sf NP$, typically in the polynomial hierarchy or $sf PSPACE$. Despite extensive study of these problem classes, relatively few natural completeness results are known at these higher […]

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arXiv:2601.15603v1 Announce Type: cross Abstract: Hierarchical Bayesian models are increasingly used in large, inhomogeneous complex network dynamical systems by modeling parameters as draws from a hyperparameter-governed distribution. However, theoretical guarantees for these estimates as the system size grows have been lacking. A critical concern is that hyperparameter estimation may diverge for larger networks, undermining the model’s reliability. Formulating the system’s evolution in a measure transport perspective, we propose a theoretical framework for estimating hyperparameters with mean-type observations, which […]

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In this tutorial, we demonstrate how to build a unified Apache Beam pipeline that works seamlessly in both batch and stream-like modes using the DirectRunner. We generate synthetic, event-time–aware data and apply fixed windowing with triggers and allowed lateness to demonstrate how Apache Beam consistently handles both on-time and late events. By switching only the input source, we keep the core aggregation logic identical, which helps us clearly understand how Beam’s event-time model, windows, and panes behave without […]

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arXiv:2506.08337v2 Announce Type: replace-cross Abstract: Diffusion models, typically formulated as discretizations of stochastic differential equations (SDEs), have achieved state-of-the-art performance in generative tasks. However, their theoretical analysis often involves complex proofs. In this work, we present a simplified framework for analyzing the Euler–Maruyama discretization of variance-preserving SDEs (VP-SDEs). Using Gr”onwall’s inequality, we derive a convergence rate of $O(T^{-1/2})$ under standard Lipschitz assumptions, streamlining prior analyses. We then demonstrate that the standard Gaussian noise can be replaced by computationally […]

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Our mission is to ensure that AGI (Artificial General Intelligence) benefits all of humanity.  Systems that start to point to AGI* are coming into view, and so we think it’s important to understand the moment we are in. AGI is a weakly defined term, but generally speaking we mean it to be a system that can tackle increasingly complex problems, at human level, in many fields. People are tool-builders with an inherent drive to understand and create, which […]

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Animation is too hard. To make a 30-second clip, you usually need to learn Blender, hire voice actors, frame keyframes, and render for twelve hours. I wanted to make memes, shitposts, and storytelling clips, and I wanted them done in the time it takes to drink a coffee. So, I built the Stickverse. It is a scrappy, Python-based animation pipeline that turns a raw text story into a fully voiced, lip-synced (well, “lip-flapped”) video. It uses Google’s Gemini […]

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The rapid digitization of cultural heritage materials has led to the substantial growth of digital library collections, particularly large and heterogeneous archives of periodicals. This expansion has intensified challenges related to content discovery, accessibility, and user engagement, as users increasingly struggle to navigate and identify relevant materials in periodical collections. In this context, intelligent interaction with cultural content has become an essential aspect of effectively accessing and utilizing resources in modern digital libraries, highlighting the need for adaptive […]

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Get Started with Rust: Enums There are two ways to create custom data types in Rust: structs and enums. In contrast to structs, enums construct a type that has multiple variants and not multiple fields. While structs are a part of pretty much any programming language, enums are not so mainstream and are mostly seen in statically typed functional languages like Haskell or OCaml. But, as we’ll see, they are quite nice for domain modeling with types. This […]

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