Has Deep Learning Discovered Its Own “Newton’s Law”?

A new collaborative paper titled “There Will Be a Scientific Theory of Deep Learning” proposes a unified “Learning Mechanics” framework that connects solvable idealized models, tractable limits, empirical scaling laws, hyperparameter theory, and universal representation behavior, aiming to give deep learning a first‑principles scientific foundation.

Deep LearningNeural Networkshyperparameters

0 likes · 14 min read

Has Deep Learning Discovered Its Own “Newton’s Law”?

Architecture Breakthrough

Dec 22, 2025 · R&D Management

Why Theory Beats Experience: Harnessing Concepts for Faster, Better Development

The article argues that in organizations, especially among developers, grounding daily work in solid theoretical frameworks—such as design patterns, SOLID principles, and non‑functional requirement models—enables faster, higher‑quality outcomes and guides long‑term strategic growth, whereas relying solely on ad‑hoc experience leads to inefficiency and technical debt.

Non-functional RequirementsPracticeProject Management

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Why Theory Beats Experience: Harnessing Concepts for Faster, Better Development

Huawei Cloud Developer Alliance

Nov 20, 2025 · Artificial Intelligence

Top 12 Must‑Read Books Bridging Mathematics and AI

This article curates twelve classic textbooks that connect core mathematical concepts—linear algebra, calculus, probability, statistics, and optimization—with machine‑learning theory and practice, offering concise descriptions, author information, and direct links for readers seeking a solid mathematical foundation for AI.

AIBooksFoundations

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Top 12 Must‑Read Books Bridging Mathematics and AI

Model Perspective

Dec 15, 2023 · Fundamentals

What Are the Three Types of Mathematicians? Insights from Shing‑Tung Yau

The article explores Shing‑Tung Yau’s classification of mathematicians into three groups—those who create theory, those who uncover patterns from phenomena, and those who solve major problems—highlighting their distinct contributions to mathematical innovation, problem solving, and the pursuit of beauty.

historymathematiciansmathematics

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What Are the Three Types of Mathematicians? Insights from Shing‑Tung Yau

Model Perspective

Jul 30, 2022 · Fundamentals

When Does Mean Independence Imply Full Independence? A Deep Dive

This article defines independence for continuous random variables, introduces the weaker concept of mean‑independence, explains how it differs from linear uncorrelatedness, and presents key propositions and proofs showing that mutual independence implies mean‑independence while the converse does not hold.

independencemean-independenceprobability

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When Does Mean Independence Imply Full Independence? A Deep Dive

360 Quality & Efficiency

Jul 9, 2018 · Fundamentals

Reliability Redundancy, Gödel’s Incompleteness, and the Halting Problem: Foundations of Program Analysis

The article explores reliability engineering with redundant systems, explains Gödel’s incompleteness theorem and the halting problem, and introduces program static analysis techniques, illustrating how theoretical foundations guide practical approaches to detecting software defects through approximations and abstract interpretation.

ComputabilityGödelReliability

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Reliability Redundancy, Gödel’s Incompleteness, and the Halting Problem: Foundations of Program Analysis

Model Perspective

Jun 28, 2015 · Fundamentals

What Is a Decision Execution Model? A Step‑by‑Step Guide

This article explains decision execution models, defining the concept, outlining its ideal assumptions, comparing it to mathematical induction, and discussing why real‑world constraints make the model impractical while still offering valuable insights for improving decision‑making processes.

Managementdecision makingprocess modeling

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What Is a Decision Execution Model? A Step‑by‑Step Guide