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TRON: технология прогноза силы, места и времени землетрясений

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Русский | English | 中文 | 日本語 Технология TRON (точный прогноз силы, места и времени землетрясений) была разработана 15 лет назад, в 2011 году . В её основе лежит способность животных за дни и часы предчувствовать приближение конкретного землетрясения. Такой прогноз позволил бы защитить не только людей, но и критическую инфраструктуру, включая дата-центры и ИИ-системы. В мае 2026 года, в результате эксперимента по автоматизации на основе ИИ-модели Gemma 4 , удалось протестировать автоматизированную систему, которая полностью исключает участие людей в цепочке обработки видео с поведением животных. Текущее состояние : поиск инвестиций (≈ €200 000) для пилотной проверки в сейсмоактивной зоне и научной валидации гипотезы . Основатель: Борис Д. Яровой Ежегодное количество жертв землетрясений XX век - 33.000 человек. ТАНШАНЬ 1976 ....
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TRON: Technology for Predicting the Magnitude, Location, and Time of Earthquakes

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The TRON technology (Technology Real-time Online Nucleus) was created in 2011, immediately after the Tohoku earthquake in Japan on March 11, 2011. It is based on the ability of animals to sense earthquakes in advance. By collecting data on changes in animal behavior via the internet and analyzing it, it is possible to predict in advance the magnitude, location, and time of a specific earthquake. In May 2026, the TRON technology reached full automation. As a result of a pilot experiment based on the multimodal AI model Gemma 4, it became possible to completely eliminate humans from the technological chain of collecting the necessary information. The data-processing chain is automated. The next step — a working end-to-end prototype — is intended to be funded through investment and validation. Current status : seeking investment (≈ €200,000) to test the pilot prototype and scientifically validate the hypothesis.   Full...
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TRON地震预测：当动物成为自然的预警传感器

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震前时间 震中区域 20-50公里 70-100公里 150-200公里 250+公里 震前1-2分钟 马、鸡、牛、金丝雀、青蛙 鸡、金丝雀、海鸥 马、鱼、鸡 马、金丝雀 犬、马 震前10-30分钟 犬、鼠、金丝雀、海鸥、牛 犬、金丝雀 龟、青蛙 鱼、金丝雀 - 震前1-4小时 犬、鼠、马、鹿、猫、牛 鱼、鳗鱼 鹿、鱼、鸡 鼠、鳗鱼 牛 震前6-12小时 犬、猫、马 ...
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AI That Learns to Generalize Later: The Mystery of Grokking

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Research note on Xu, Vardi & Safran, “To Grok Grokking: Provable Grokking in Ridge Regression” , ICML 2026. A neural network is trained on a task. On the training data it performs well almost immediately. On new, unseen data it fails. Then, after a long period during which nothing appears to change, it begins to produce correct answers on data it has never seen. This phenomenon is known in machine learning as grokking . The core finding: a team of researchers has rigorously proven all three stages of grokking in a simple linear model and shown how the effect can be controlled through training parameters. The problem The common assumption is that longer training leads to better generalization. Grokking contradicts this assumption. The process typically unfolds in three stages: Overfitting. The model memorizes the training data. Plateau. Performance on new data remains poor for a long period, with little visible change. Generalization. The model begins to pro...
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Artificial Superintelligence: The God That Will Either Save or Destroy Humanity

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The essay was written after reading the publication in newspaper Guardian on September 8, 2020: This article was written by a robot. Aren't you scared yet, man? Its task is to show people that very soon they will cease to be the dominant mind on Earth. Additional information about the author is in the note below.  "I am human. An ordinary unique person. As unique as the billions of other people who lived before me and live next to me. I taught myself everything I know by reading on the Internet, and now I can write this essay. Many people today already know what artificial intelligence is. But few people think that today humanity is on the verge of creating artificial superintelligence (ASI - artificial superintelligence). Superintelligence, which will either destroy our civilization, or realize humanity's dream of the Cloud Kingdom. And it will happen whether you believe it or not. Firstly, ASI will have access to control all technological systems of humanity, powered by...
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From Ideal Fusion to Working Nuclear Energy Systems

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1. The Structural Failure of Big Fusion Projects The current fusion ecosystem is fragmented by design: Plasma physicists optimize reaction conditions (temperature, confinement time, Q-factor ). Materials scientists optimize isolated samples for peak performance under narrow conditions. System engineers extrapolate optimistic assumptions into plant-scale renderings. Each layer is locally successful. The system as a whole is not. The missing role is a system owner responsible for lifetime operation, maintenance, fuel logistics, radiation damage, and cost of ownership. As a result: Physics does not translate into engineering tolerances. Material properties do not translate into predictable service life. Subsystems do not assemble into an autonomous, economically stable energy platform. This is not a failure of science. It is a failure of architecture. 2. Radiation Is Not the Enemy — Unmanaged Degradation Is Neutron damage , swelling, helium embrittlement , and activation are fundamental...
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Cancer as STOP Resistance: Rethinking the Core of Oncogenesis

Modern oncology has achieved significant success in describing the molecular mechanisms of uncontrolled cellular growth. However, the dominant paradigm still treats cancer primarily as a problem of acceleration, hyperactivation, and excessive signaling stimulation. This work proposes an alternative conceptual framework in which the core of oncogenesis is not so much the amplification of growth signals as the systemic loss of a cell’s ability to perceive and execute stop signals (STOP signals). We consider cancer as a state of acquired STOP resistance and discuss the implications of this view for the interpretation of remission and the prospects of therapeutic strategies. 1. Introduction: an asymmetry of attention Over the past decades, the cell biology of growth and division has been studied in great detail. Oncogenes, growth factors, proliferative signaling cascades, metabolic shifts—all of these form a dense and well-mapped landscape. At the same time, systems of biological sto...
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癌症即停止抵抗：从消除肿瘤到恢复细胞制动的新范式

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现代肿瘤学在描述细胞不受控制的生长分子机制方面取得了重大成就。然而，主导范式仍然主要将癌症视为加速、过度活化和信号过度刺激的问题。这项工作提出了一个替代性的概念框架，其中肿瘤发生的核心与其说是生长信号的放大，不如说是细胞感知和执行停止信号能力的系统性丧失。我们将癌症视为一种获得性的"停止信号抵抗"状态，并讨论了这一观点对缓解期解读和治疗策略前景的影响。 1. 引言：关注的不对称性 在过去的几十年里，关于生长和分裂的细胞生物学已被深入研究。致癌基因、生长因子、增殖信号级联、代谢转变——所有这些构成了一个密集且绘制完善的图谱。 与此同时，生物停止系统——那些终止分裂、诱导分化、驱使细胞退出周期或建立静息状态的信号——在概念上仍然处于次要地位。它们更常被视为生长刺激的被动缺失，而非生命系统一种主动、自主且根本重要的功能。 这种关注的不对称性造成了一个盲点：如果生长是"油门"，那么"刹车"在哪里？当它失灵时会发生什么？ 2. 停止信号作为一项基本功能 在正常的生物学中，停止信号并非对生长的否定，而是一个独立的调控回路。它在多个层面运作： 细胞周期退出， 终末分化， 接触抑制， 程序性凋亡， 长期静息。 必须强调：停止信号不是一个事件，而是一种状态。它需要： 接收， 解读， 执行。 因此，细胞停止的能力是一种主动的"能力"，而非"没有刺激"的默认状态。 3. 肿瘤发生作为获得性停止抵抗 从这个角度看，肿瘤发生的核心是获得停止抵抗。癌细胞可能保留了对个别分子干预的表面敏感性，却失去了进入稳定停滞状态的能力。停止信号要么未被识别，要么被解读为噪音，要么在执行层面被阻断。在此模型中，致癌基因放大了生长，但关键缺陷在于刹车失灵。 这有助于解释为什么肿瘤细胞可能对治疗产生暂时反应并进入部分消退，随后却无需新突变即可恢复生长。停止抵抗不是一个点缺陷，而是一种系统特性。 4. 缓解期作为停止功能的部分恢复 缓解期传统上被解释为成功消灭肿瘤细胞的结果。然而，临床观察指向了一幅更复杂的图景： 肿瘤可能在未完全消除的情况下缩小， 疾病可能长期保持稳定， 在某些情况下，极...
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Alternative to QKV Architecture — STO (Semantics, Time, Operator)

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Author: Boris D. Yarovoy Status: Conceptual framework with comprehensive empirical validation — including negative results that corrected earlier claims. Abstract The Transformer architecture has dominated sequence modeling through its Query-Key-Value (QKV) attention mechanism. I propose an alternative attention architecture called Attentime , based on three orthogonal components: a symmetric Query-Key matrix capturing pure semantic affinity, an asymmetric Time matrix implementing causal physics through learnable decay, and a dynamically activated Dynamic Value matrix computed as a function of interacting keys. Through targeted micro-experiments, I demonstrate: (1) numerical stability, (2) 100% accuracy on syntactic role resolution across active, passive, and relative clause structures, (3) architectural prevention of catastrophic forgetting for new tokens — a capability standard Transformers lack without external methods, and (4) separable caching that preserves 100% accu...
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A2A Is Not a Feature. It Is a High-Stakes System

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We are entering a phase where AI systems no longer operate only in a human-to-machine loop, but increasingly in agent-to-agent (A2A) interactions. This is not a product upgrade. It is a structural shift. When autonomous systems negotiate, optimize, coordinate, or escalate without direct human mediation, the system boundary changes. Responsibility diffuses. Latency shrinks. Error propagation accelerates. In low-stakes environments, this is manageable. In high-stakes domains , it is not. What “High-Stakes” Means Here High-stakes systems are not defined by intent, but by consequence.
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MCP TRON: Борис Д. Яровой - 夷海参崴 MCP TRON: Борис Д. Яровой - 夷海参崴
2001 "The Internet as an Environment for Artificial Mind" (Rus) «Интернет — среда функционирования искусственного разума»
2020 "Strong Artificial Intelligence and Its Cloud Kingdom" (Rus) «Сильный искусственный интеллект и его облачное Царство»
2026 Automating the Technology of Precise Earthquake Prediction — TRON Automating the Technology of Precise Earthquake Prediction — TRON