🎛️ EQ: A Video About All Forms of Equalizers
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🧠 Hallucinations Are Inevitable—but Can Be Statistically Negligible
A thought-provoking bridge between theory and practice, this work explains how deep learning systems can approach—but never fully reach—perfect factuality, providing a roadmap for minimizing hallucinations in real-world LLMs.
Atsushi Suzuki and collaborators explore why hallucinations in large language models (LLMs) are theoretically unavoidable according to computability limits, yet can be reduced to negligible rates with improved data and algorithmic design. The paper connects the boundaries of computability with practical approaches informed by information theory, offering a balanced view between theoretical constraints and applied optimization.
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💹 AI Trading in the Real Market
A pioneering experiment that shifts AI evaluation from simulation to live markets, offering a rigorous test of real-world decision-making and risk-aware intelligence in financial environments.
NoF1.ai launches Alpha Arena, a live benchmark where AI models manage $10,000 of real cryptocurrency under identical market conditions. Competing models such as GPT-5, Claude 4.5, and Gemini 2.5 Pro are evaluated on profitability, risk management, and adaptability, with full transparency through publicly available trade logs.
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