Cloud providers must assign heterogeneous compute resources to workflow DAGs while balancing competing objectives such as completion time, cost, and energy consumption. In this work, we study a single-workflow, queue-free scheduling setting and consider a graph neural network (GNN)-based deep reinforcement learning scheduler designed to minimize workflow completion time and energy usage. We identify specific out-of-distribution (OOD) conditions under which GNN-based deep reinforcement learning schedulers fail and provide a principled explanation of why these failures occur. Through controlled […]

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Hello, readers! When it comes to developments in artificial intelligence, things are moving fast. It’s been less than two years since the public release of AI tools like ChatGPT, Midjourney, Stable Diffusion and Meta’s LLaMA. Regulators, lawmakers, and businesses are all beginning to wrap their heads around the implications of the use of generative AI tools. This includes news organizations and journalists, who have already started experimenting. Nieman Journalism Lab reported that 5 of the 45 unannounced finalists […]

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Venture capital (VC) investments in early-stage startups that end up being successful can yield high returns. However, predicting early-stage startup success remains challenging due to data scarcity (e.g., many VC firms have information about only a few dozen of early-stage startups and whether they were successful). This limits the effectiveness of traditional machine learning methods that rely on large labeled datasets for model training. To address this challenge, we propose an in-context learning framework for startup success prediction […]

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We entered the Release Candidate stage in the Godot 4.3 development cycle a week ago with 4.3 RC 1, which means that all features are in place, the most critical regressions have been tackled, and we’re confident that it’s now ready for general use in the vast majority of cases. A lot of users have been testing the RC 1 snapshot, reporting issues, many of which could be fixed. In the meantime, we’ve kept working on a few […]

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Era thinks that we will see many form factors of AI hardware, including glasses, rings, and pendants

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arXiv:2505.13660v2 Announce Type: replace-cross Abstract: This paper introduces a new constraint-free concave dual formulation for the Wasserstein barycenter. Tailoring the vanilla dual gradient ascent algorithm to the Sobolev geometry, we derive a scalable Sobolev gradient ascent (SGA) algorithm to compute the barycenter for input distributions discretized over a regular grid. Despite the algorithmic simplicity, we provide a global convergence analysis that achieves the same rate as the classical subgradient descent methods for minimizing nonsmooth convex functions in the […]

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Get Started With Rust: Structs In almost any programming language, you can create data structures – like classes or records – that pack a group of things together. Rust is no exception to this with structs. This article will show you how to use structs in Rust. By the end of this article, you’ll know: how to define and instantiate a struct; how to derive a trait for a struct; what are struct methods, and how to use […]

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arXiv:2603.20313v1 Announce Type: new Abstract: Large Language Models (LLMs) with tool-calling capabilities have demonstrated remarkable potential in executing complex tasks through external tool integration. The Model Context Protocol (MCP) has emerged as a standardized framework for connecting LLMs to diverse toolsets, with individual MCP servers potentially exposing dozens to hundreds of tools. However, current implementations face a critical scalability challenge: providing all available tools to the LLM context results in substantial token overhead, increased costs, reduced accuracy, and […]

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Medical multimodal representation learning aims to integrate heterogeneous data into unified patient representations to support clinical outcome prediction. However, real-world medical datasets commonly contain systematic biases from multiple sources, which poses significant challenges for medical multimodal representation learning. Existing approaches typically focus on effective multimodal fusion, neglecting inherent biased features that affect the generalization ability. To address these challenges, we propose a Dual-Stream Feature Decorrelation Framework that identifies and handles the biases through structural causal analysis introduced by […]

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Published on February 10, 2026 5:59 PM GMT Cross-posted from Telescopic Turnip Recommended soundtrack for this post As we all know, the march of technological progress is best summarized by this meme from Linkedin: Inventors constantly come up with exciting new inventions, each of them with the potential to change everything forever. But only a fraction of these ever establish themselves as a persistent part of civilization, and the rest vanish from collective consciousness. Before shutting down forever, […]

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