# Adaptation İlgili Makaleler

HTX Haber Merkezi, kripto endüstrisindeki piyasa trendleri, proje güncellemeleri, teknoloji gelişmeleri ve düzenleyici politikaları kapsayan "Adaptation" hakkında en son makaleleri ve derinlemesine analizleri sunmaktadır.

Turing Award Laureate Sutton's New Work: Using a Formula from 1967 to Solve a Major Flaw in Streaming Reinforcement Learning

New research titled "Intentional Updates for Streaming Reinforcement Learning" (arXiv:2604.19033v1), involving Turing Award laureate Richard Sutton, addresses a core challenge in deep reinforcement learning (RL): the "stream barrier." Current deep RL methods typically rely on replay buffers and batch training for stability, failing catastrophically when learning online from single data points (streaming). The authors propose a fundamental shift: instead of prescribing how far to move parameters (a fixed step size), their "Intentional Updates" method specifies the desired change in the function's output (e.g., a 5% reduction in value prediction error). It then calculates the step size needed to achieve that intent. This idea is inspired by the Normalized Least Mean Squares (NLMS) algorithm from 1967. Applied to value and policy learning, this yields algorithms like Intentional TD(λ) and Intentional AC. The method inherently stabilizes learning by adapting the step size based on the local gradient landscape, preventing overshooting/undershooting. In experiments on MuJoCo continuous control and Atari discrete tasks, Intentional AC achieved performance rivaling batch-based algorithms like SAC in a streaming setting (batch size=1, no replay buffer), while being ~140x more computationally efficient per update. The work demonstrates significant robustness, reducing reliance on numerous stabilization tricks. A remaining challenge is bias in policy updates due to action-dependent step sizes. Overall, this approach advances efficient, online, "learn-as-you-go" RL, enabling adaptive systems without massive data buffers or compute clusters.

marsbit05/10 06:28

Turing Award Laureate Sutton's New Work: Using a Formula from 1967 to Solve a Major Flaw in Streaming Reinforcement Learning

marsbit05/10 06:28

2026 is Not the Year of AI, But the Starting Point of a Great Reshuffle of Human Professions

The author, an AI entrepreneur and investor, argues that 2026 will not be the "Year of AI" but rather the starting point of a massive reshuffling of human professions. He states that the current pace of AI advancement, driven by a small number of researchers at companies like OpenAI and Anthropic, is exponential and will soon impact nearly all white-collar industries, not in a decade but within 1-5 years. He provides a personal account of how the latest models (e.g., GPT-5.3 Codex, Opus 4.6) can now autonomously complete complex tasks, such as writing flawless code for an entire software application and testing it, with human-level judgment and decision-making. The author emphasizes that public perception lags far behind reality, as those using free, outdated models are unaware of the capabilities of current paid versions. Key points include: AI is now involved in its own development, creating a feedback loop that accelerates progress ("intelligence explosion"); it will replace cognitive work across law, finance, medicine, and more; and the common belief that AI cannot replicate human judgment, creativity, or empathy is becoming uncertain. The author advises readers to act now by: 1) Seriously using top-tier AI tools in their daily work, 2) Gaining a competitive advantage in their careers by mastering AI before others, 3) Strengthening their financial resilience, 4) Focusing on skills AI cannot easily replace (e.g., building trust, in-person work), 5) Rethinking education for children to emphasize creativity and AI collaboration, and 6) Pursuing personal dreams with AI's help. He concludes that this is a pivotal moment for civilization, posing both immense opportunities (e.g., curing diseases) and existential risks (e.g., uncontrollable AI, weaponization). The future is already here for the tech industry and is imminent for everyone else. Success belongs to those who embrace this reality with curiosity and urgency.

marsbit03/12 00:43

2026 is Not the Year of AI, But the Starting Point of a Great Reshuffle of Human Professions

marsbit03/12 00:43

How Can Ordinary People 'Survive' the Impact of the AI Wave?

In this urgent warning, HyperWrite CEO Matt Shumer argues that AI advancement is progressing far faster than most people realize, with transformative impacts imminent across all sectors. He draws a parallel to the rapid onset of the COVID-19 pandemic, suggesting the current technological shift is even more profound. Shumer, an AI industry insider, states that a small group of researchers at leading labs like OpenAI and Anthropic are driving exponential progress. He shares his personal experience: recent models like GPT-5.3 Codex and Claude Opus 4.6 can now autonomously build and test complex software applications from a simple English description, requiring zero human correction. This represents a qualitative leap from being an assistant to a superior executor. He emphasizes that this disruption, which began with coding, will soon affect all knowledge work—law, finance, medicine, writing, and analysis—within 1-5 years, not decades. Free versions of AI tools are outdated; the paid, cutting-edge models are vastly more capable. Metrics show AI's autonomous task-completion time is doubling every few months. Crucially, AI is now used to build and improve subsequent AI models, creating a self-accelerating feedback loop toward artificial general intelligence (AGI). Shumer's advice for "surviving" is to start using the most powerful AI tools *now*. Subscribe to premium models, integrate them into core professional tasks, and experiment daily. Financial prudence and developing adaptability are key. He concludes that while AI poses immense risks (from job loss to security threats), it also offers unprecedented opportunities for creativity and problem-solving if approached with curiosity and urgency. The time to prepare is immediately.

marsbit02/18 04:27

How Can Ordinary People 'Survive' the Impact of the AI Wave?

marsbit02/18 04:27

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