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COMPLEX COGNITIVE CREATURES AREN’T BLANK SLATES.

Ernest Davis • Rebooting AI: Building Artificial Intelligence We Can Trust

On Jagged AGI: o3, Gemini 2.5, and everything after

The symbolists’ master algorithm is inverse deduction, the connectionists’ is backpropagation, the evolutionaries’ is genetic programming, the Bayesians’ is Bayesian inference, and the analogizers’ is

Pedro Domingos • The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World

Indeed, we may already be running into scaling limits in deep learning, perhaps already approaching a point of diminishing returns. In the last several months, research from DeepMind and elsewhere on models even larger than GPT-3 have shown that scaling starts to falter on some measures, such as toxicity, truthfulness, reasoning, and common sense

Gary Marcus • Deep Learning Is Hitting a Wall

Japanese martial arts traditions call these three stages of learning shu-ha-ri: first following rules faithfully (shu), then breaking from tradition (ha), and finally transcending formal structure altogether (ri). What makes this framework so revelatory for any AI doomsday discussion is how it illuminates the evolving relationship between algorithm

Deepak Pathak looks at the success of deep learning and sees one glaring weakness: each system—be it for machine translation, or object recognition, or even game playing—is purpose-built.

Brian Christian • The Alignment Problem

The Master Algorithm is neither genetic programming nor backprop, but it has to include the key elements of both: structure learning and weight learning.

Pedro Domingos • The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World

OpenAI’s Sam Altman on Building the ‘Core AI Subscription’ for Your Life

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Artificial Intelligence

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