technocracy

arXiv:2603.02420v1 Announce Type: new Abstract: Pluralistic alignment has emerged as a promising approach for ensuring that large language models (LLMs) faithfully represent the diversity, nuance, and conflict inherent in human values. In this work, we study a high-stakes deployment context – mulching – where automated systems transform selected individuals into nutrient-rich slurry for the dual purposes of food security and aesthetic population management. Building on recent pluralistic alignment frameworks, we introduce ValueMulch, a reproducible training, deployment, and certification […]

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Author(s): Hayanan Originally published on Towards AI. Unveiling the Magic of Gradient Descent, Feedforward Architectures, and Universal Function Approximation in AI Ne‌ural⁠ networks‌ form the backbone of mod‌ern artifici⁠al inte​lligence, powering b‍rea⁠kthroughs in computer v⁠ision, natur⁠al language pro‌cess‍ing,​ re‍commende‍r syst‌ems, and s⁠cientific disc​overy​.‍ Yet beneath today’s deep architectures lie simple mathematic⁠a‌l ideas developed deca‍de​s‌ ago. T‌his a‍rticle pr⁠esents a⁠ c‍omprehensive, e⁠nd-to-end jo​urney⁠ thro‌ugh the evolution of neur​al‍ net‍wo​rks fr‌om the foundational percep⁠tro‌n to sigmoid n​euro‌ns, g‌radient-based l‌earn‌ing, feedfo‍rwar⁠d​ […]

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arXiv:2602.07100v1 Announce Type: new Abstract: Automated floorplan generation aims to improve design quality, architectural efficiency, and sustainability by jointly modeling global spatial organization and precise geometric detail. However, existing approaches operate in raster space and rely on post hoc vectorization, which introduces structural inconsistencies and hinders end-to-end learning. Motivated by compositional spatial reasoning, we propose TLC-Plan, a hierarchical generative model that directly synthesizes vector floorplans from input boundaries, aligning with human architectural workflows based on modular and reusable […]

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Forgetting a subset in machine unlearning is rarely an isolated task. Often, retained samples that are closely related to the forget set can be unintentionally affected, particularly when they share correlated features from pretraining or exhibit strong semantic similarities. To address this challenge, we propose a novel two-phase optimization framework specifically designed to handle such retai-forget entanglements. In the first phase, an augmented Lagrangian method increases the loss on the forget set while preserving accuracy on less-related retained […]

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In this tutorial, we build and operate a fully local, schema-valid OpenClaw runtime. We configure the OpenClaw gateway with strict loopback binding, set up authenticated model access through environment variables, and define a secure execution environment using the built-in exec tool. We then create a structured custom skill that the OpenClaw agent can discover and invoke deterministically. Instead of manually running Python scripts, we allow OpenClaw to orchestrate model reasoning, skill selection, and controlled tool execution through its […]

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How are you, hacker? 🪐 What’s happening in tech today, April 17, 2026? The HackerNoon Newsletter brings the HackerNoon homepage straight to your inbox. On this day, we present you with these top quality stories. From The Engineer in the Machine: Neo Wants to Be a Kaggle Grandmaster in a Box to Veritasium Stole $10,000 From MKBHDs Locked iPhone. Apple and Visa Knew About the Bug for 5 Years., let’s dive right in. Veritasium Stole $10,000 From MKBHDs […]

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Have you ever had to take on a task that caused the previous developer to burn out and leave the company? Well, I happened to run into exactly that kind of task. The task of ensuring secure local storage for files that a user uploads into the application, for example while communicating with technical support in a chat. I will cover all the details and explain everything thoroughly in this article. Getting a file from the user There […]

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arXiv:2602.17693v1 Announce Type: new Abstract: Post-Training Quantization (PTQ) is crucial for efficient model deployment, yet its effectiveness on Ascend NPU remains under-explored compared to GPU architectures. This paper presents a case study of representative PTQ baselines applied to reasoning-oriented models such as DeepSeek-R1-Distill-Qwen series (1.5B/7B/14B) and QwQ-32B. We evaluate four distinct algorithms, including AWQ, GPTQ, SmoothQuant, and FlatQuant, to cover the spectrum from weight-only compression to advanced rotation-based methods. Our empirical results reveal significant platform sensitivity. While 4-bit […]

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