# Math and Logic

Published articles for Math and Logic.

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## GPT-5 and the future of mathematical discovery

DevFeed: [GPT-5 and the future of mathematical discovery](<https://devfeed.tech/articles/gpt-5-and-the-future-of-mathematical-discovery-6435.md>)

Original publisher: [Read original article](<https://openai.com/index/gpt-5-mathematical-discovery>)

Published: 2025-11-24T00:00:00Z

Content type: article

Language: en

Sources: [OpenAI News](<https://devfeed.tech/sources/openai-news.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Optimization](<https://devfeed.tech/topics/optimization.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [Algorithm](<https://devfeed.tech/topics/algorithm.md>), [Math and Logic](<https://devfeed.tech/topics/math-and-logic.md>), [OpenAI](<https://devfeed.tech/topics/openai.md>), [ChatGPT](<https://devfeed.tech/topics/chatgpt.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [future](<https://devfeed.tech/tags/future.md>), [gpt](<https://devfeed.tech/tags/gpt.md>), [large-language-model](<https://devfeed.tech/tags/large-language-model.md>), [llm](<https://devfeed.tech/tags/llm.md>), [math](<https://devfeed.tech/tags/math.md>), [math-and-logic](<https://devfeed.tech/tags/math-and-logic.md>), [openai](<https://devfeed.tech/tags/openai.md>), [optimization](<https://devfeed.tech/tags/optimization.md>), [speed](<https://devfeed.tech/tags/speed.md>)

### AI overview

The article describes how UCLA mathematician Ernest Ryu used GPT-5 to investigate a longstanding open problem in optimization theory involving the Nesterov Accelerated Gradient method. GPT-5 helped surface mathematical ideas and techniques quickly, contributing to an explanation of why NAG can accelerate optimization while remaining stable.

### Source excerpt

UCLA Professor Ernest Ryu and GPT-5 solved a key question in optimization theory, showcasing AI's role in accelerating mathematical discovery.

## What Are Gradient, Divergence, and Curl in Vector Calculus?

DevFeed: [What Are Gradient, Divergence, and Curl in Vector Calculus?](<https://devfeed.tech/articles/what-are-gradient-divergence-and-curl-in-vector-calculus-4507.md>)

Original publisher: [Read original article](<https://feeds.feedblitz.com/~/921714239/0/baeldung/cs>)

Author: Charles Udekwe

Published: 2025-07-15T22:24:11Z

Content type: tutorial

Language: en

Sources: [Baeldung - CS](<https://devfeed.tech/sources/baeldung-cs.md>)

Topics: [math](<https://devfeed.tech/topics/math.md>), [Computer science](<https://devfeed.tech/topics/computer-science.md>)

Tags: [math](<https://devfeed.tech/tags/math.md>), [math-and-logic](<https://devfeed.tech/tags/math-and-logic.md>), [math-and-logic-optimization](<https://devfeed.tech/tags/math-and-logic-optimization.md>), [optimization](<https://devfeed.tech/tags/optimization.md>), [physics](<https://devfeed.tech/tags/physics.md>), [tutorial](<https://devfeed.tech/tags/tutorial.md>), [vectors](<https://devfeed.tech/tags/vectors.md>), [wi-fi](<https://devfeed.tech/tags/wi-fi.md>)

### AI overview

This tutorial explains gradient, divergence, and curl in vector calculus. It introduces scalars, vectors, scalar fields, vector fields, Cartesian coordinates, and the Del operator, then illustrates gradient using Wi-Fi signal strength and discusses practical applications.

### Source excerpt

Learn about the gradient, curl, and divergence in vector calculus and their applications. The post What Are Gradient, Divergence, and Curl in Vector Calculus? first appeared on Baeldung on Computer Science. Related Stories What Is the Gradient Norm? The Method of Lagrange Multipliers How to Find the Maximum Value in Relational Algebra