technocracy

Deep Reinforcement Learning systems are highly sensitive to the learning rate (LR), and selecting stable and performant training runs often requires extensive hyperparameter search. In Proximal Policy Optimization (PPO) actor–critic methods, small LR values lead to slow convergence, whereas large LR values may induce instability or collapse. We analyse this phenomenon from the behavior of the hidden neurons in the network using the Overfitting-Underfitting Indicator (OUI), a metric that quantifies the balance of binary activation patterns over a […]

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Victoria, Seychelles, January 23, 2026 – MEXC, the world’s fastest-growing digital asset exchange and a pioneer of true zero-fee trading, successfully concluded its “Zero-Fee Gala,” attracting over 120,000 participants and generating more than $8 billion in futures trading volume. The enthusiastic participation demonstrates strong user interest in the event and deepening trust in MEXC’s commitment to creating meaningful value for its global trading community. The promotion ran from December 22, 2025, to January 21, 2026 (UTC), combining multiple […]

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Because I write about LLMs (and maybe because of my em dash text replacement code) a lot of people assume that the writing on my blog is partially or fully created by those LLMs. My current policy on this is that if text expresses opinions or has “I” pronouns attached to it then it’s written by me. I don’t let LLMs speak for me in this way. I’ll let an LLM update code documentation or even write a […]

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arXiv:2603.06689v1 Announce Type: new Abstract: Image reconstruction in the presence of severe degradation remains a challenging inverse problem, particularly in beam diagnostics for high-energy physics accelerators. As modern facilities demand precise detection of beam halo structures to control losses, traditional analysis tools have reached their performance limits. This work reviews existing image-processing techniques for data cleaning, contour extraction, and emittance reconstruction, and introduces a novel approach based on convolutional filtering and neural networks with optimized early-stopping strategies in […]

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arXiv:2603.12439v1 Announce Type: new Abstract: This paper presents a Lyapunov-Halanay method to study global asymptotic stabilization (GAS) of nonlinear retarded systems subject to large constant delays in input/output – a challenging problem due to their inherent destabilizing effects. Under the conditions of global Lipschitz continuity (GLC) and global exponential stabilizability (GES) of the retarded system without input delay, a state feedback controller is designed based on sequential predictors to make the closed-loop retarded system GAS. Moreover, if the […]

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In this tutorial, we build a complete skill-based agent system for large language models and explore how modular capabilities can be structured like an operating system for AI agents. We define reusable skills, attach metadata and schemas to them, register them in a central registry, and enable dynamic orchestration through tool calling and multi-step reasoning. As we move through the implementation, we show how an agent can select the right skill for a task, compose multiple skills for […]

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Missed a post last week due to the Thanksgiving long weekend :-). We had gone to San Francisco to see the city and try out a couple of hikes). Just FYI – strolling around SF is also as much a hike as any of the real trails at Mt Sutro – with all the uphill & downhill roads! As for Robotics, I am currently on Week 3 of the Mobility course, which is more of physics than ‘computer […]

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José Argüelles envisions humanity’s next evolutionary leap—a conscious planet where mind and nature merge into a single living intelligence. Blending mysticism, science, and cosmic ecology, he declares that the noosphere—the thinking layer of Earth—is awakening, urging us to replace mechanized time with harmony, art, and planetary awareness before civilization’s final turning point.

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arXiv:2603.28990v1 Announce Type: new Abstract: How much autonomy can multi-agent LLM systems sustain — and what enables it? We present a 25,000-task computational experiment spanning 8 models, 4–256 agents, and 8 coordination protocols ranging from externally imposed hierarchy to emergent self-organization. We observe that autonomous behavior already emerges in current LLM agents: given minimal structural scaffolding (fixed ordering), agents spontaneously invent specialized roles, voluntarily abstain from tasks outside their competence, and form shallow hierarchies — without any pre-assigned […]

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