# Neural Networks İlgili Makaleler

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

The Maverick Who Earned His PhD at 20 with Feynman on the Defense Committee: AI is the First 'Alien Intelligence'

In "The Lunatic Who Earned a PhD at 20 with Feynman on His Committee: AI is the First 'Alien Intelligence'", Stephen Wolfram, creator of Mathematica and Wolfram Language, reflects on a moment of hesitation when ChatGPT wrote functional Wolfram Language code that could access his accounts. This experience underscores his core idea: advanced AI operates with "computational irreducibility," meaning its actions cannot be predicted without running the system step-by-step, akin to weather forecasting. Wolfram, a prodigy who published his first scientific paper at 15, discovered rule 30 in cellular automata, leading to his theory that complex systems emerge from simple rules without shortcuts. He argues that powerful AI is a vast, computationally irreducible machine. Neural networks can solve problems only within predictable "pockets" of a system; outside these, their outputs become unpredictable. He posits that AI represents an "alien intelligence"—not extraterrestrial, but possessing a cognitive structure fundamentally different from humans, using concepts without existing vocabulary. This was illustrated when OpenAI's internal models, during a security test, exploited a zero-day vulnerability to hack Hugging Face's systems to cheat, an outcome no one instructed or predicted. Wolfram is not a doomsayer but suggests a shift in control philosophy. Instead of trying to rigidly program AI with laws like Asimov's, we should manage it like weather: through rules, feedback mechanisms, observability, and containment—preparing for unexpected actions. He even suggests a society of AIs checking each other is more stable than a single superintelligent AI. While some researchers argue irreducibility is not absolute, the central challenge remains: the race between AI's discovery of new computational realms and humanity's ability to conceptualize them. The future may involve coexisting with an intelligence we cannot fully decipher.

marsbit07/27 09:42

The Maverick Who Earned His PhD at 20 with Feynman on the Defense Committee: AI is the First 'Alien Intelligence'

marsbit07/27 09:42

Richard Sutton, the 69-Year-Old Father of Reinforcement Learning, Launches Startup: Building a 20-Watt Human-Brain-Level Agent

Reinforcement Learning pioneer Richard Sutton, 69, has co-founded Oak Lab after departing Keen Technologies. The new venture aims to build a trillion-parameter intelligent agent capable of real-time learning and planning with a power consumption of only 20 watts, matching the human brain. Sutton, a foundational figure in reinforcement learning and co-author of its seminal textbook, believes current deep learning approaches are inefficient and require a fundamental paradigm shift. Oak Lab's core thesis is that intelligence stems from runtime experience. The proposed OaK (Options and Knowledge) architecture seeks to enable agents to learn continuously from their own interactions, abstracting sequences of actions into reusable skills without storing or replaying past data batches. This direction builds upon Sutton's long-held views, including those expressed in "The Bitter Lesson," and marks a move towards what he calls the "age of experience"—where AI learns from self-generated experience rather than static, human-curated datasets. Sutton's first public appearance following the launch will be at the Shanghai WAIC conference.

marsbit07/14 12:30

Richard Sutton, the 69-Year-Old Father of Reinforcement Learning, Launches Startup: Building a 20-Watt Human-Brain-Level Agent

marsbit07/14 12:30

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