technocracy

Understanding and predicting microstructure evolution is fundamental to materials science, as it governs the resulting properties and performance of materials. Traditional simulation methods, such as phase-field models, offer high-fidelity results but are computationally expensive due to the need to solve complex partial differential equations at fine spatiotemporal resolutions. To address this challenge, we propose a deep learning-based framework that accelerates microstructure evolution predictions while maintaining high accuracy. Our approach utilizes a fully convolutional spatiotemporal model trained in a […]

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arXiv:2507.17544v3 Announce Type: replace Abstract: Differential privacy has become a cornerstone in the development of privacy-preserving learning algorithms. This work addresses optimizing differentially private kernel learning within the empirical risk minimization (ERM) framework. We propose a novel differentially private kernel ERM algorithm based on random projection in the reproducing kernel Hilbert space using Gaussian processes. Our method achieves minimax-optimal excess risk for both the squared loss and Lipschitz-smooth convex loss functions under a local strong convexity condition. We […]

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arXiv:2510.09676v2 Announce Type: replace-cross Abstract: Inverse problems, where the goal is to recover an unknown signal from noisy or incomplete measurements, are central to applications in medical imaging, remote sensing, and computational biology. Diffusion models have recently emerged as powerful priors for solving such problems. However, existing methods either rely on projection-based techniques that enforce measurement consistency through heuristic updates, or they approximate the likelihood $p(boldsymbol{y} mid boldsymbol{x})$, often resulting in artifacts and instability under complex or high-noise […]

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Hi everyone, happy new year! I have a project where I’m training a DQN with stuff relating to pricing and stock decisions. Unfortunaly, I seem to be running into what seems to be some kind of forgetting? When running the training on a pure random (100% exploration rate) and then just evaluating it (just being greedy) it actually reaches values better than fixed policy. The problem arises when I left it to train beyond that scope, especially after […]

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In most enterprise Databricks environments (like in MSC or large analytics ecosystems), system tables such as system.jobrunlogs or system.cluster_events may be restricted or disabled due to security or governance policies. However, tracking cluster utilization and cost is crucial for : Understanding how efficiently jobs use compute Identifying idle clusters or cost leaks Forecasting infrastructure budget Building custom cost dashboards This blog demonstrates a step-by-step approach to compute cluster utilization and cost using only Databricks REST APIs — no […]

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arXiv:2601.12224v1 Announce Type: new Abstract: Enabling intuitive, language-driven interaction with surgical scenes is a critical step toward intelligent operating rooms and autonomous surgical robotic assistance. However, the task of referring segmentation, localizing surgical instruments based on natural language descriptions, remains underexplored in surgical videos, with existing approaches struggling to generalize due to reliance on static visual cues and predefined instrument names. In this work, we introduce SurgRef, a novel motion-guided framework that grounds free-form language expressions in instrument […]

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The WordPress Theme Problem Nobody Warned You About WordPress powers roughly 43% of all websites on the internet, according to W3Techs’ latest data. That number sounds impressive until you realize what it actually means for anyone trying to build AI tooling on top of it: there is no single “WordPress” to target. There are thousands of variations, each one a unique snowflake of themes, page builders, custom post types, and plugin interactions. If you have ever tried to […]

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arXiv:2602.13252v1 Announce Type: new Abstract: Robotic middleware serves as the foundational infrastructure, enabling complex robotic systems to operate in a coordinated and modular manner. In data-intensive robotic applications, especially in industrial scenarios, communication efficiency directly impact system responsiveness, stability, and overall productivity. However, existing robotic middleware exhibit several limitations: (1) they rely heavily on (de)serialization mechanisms, introducing significant overhead for large-sized data; (2) they lack efficient and flexible support for heterogeneous data sizes, particularly in intra-robot communication and […]

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OpenAI has made tech waves in the recent years given the prominences of the ChatGPT family of models, and the remanent of LLMs as search engine reindexing algorithms. They were a private research entity that became a titan now competing with the likes of Google. However, their story is less than glamorous. They started out as a non-profit funded by Musk only to be insanely profit-driven. In fact, they are a cash-burn enterprise, and on top of that […]

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