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If you understand the brain, you can see how AI thinks!

Artificial neural networks, the core structure of artificial intelligence, were inspired by the structure of the human brain. This course insightfully explores the connection between AI's way of thinking and brain structure, and is a brain-cognitive-based AI principle exploration process for everyone who wants to 'properly' understand AI and apply it to practical work.

1 learners are taking this course

  • aidercollege
머신러닝
ai-리터러시
이론 실습 모두
뇌과학
인공신경망
Artificial Neural Network
CNN
AI
Data literacy
Generative AI

What you will learn!

  • Understanding how the human brain structure has influenced AI algorithms

  • Connection between AI technologies like CNN, RNN, Transformers and neuroscience concepts

  • Analysis of GPT's Memory Structure Based on Neural Networks GPT's memory structure operates through several key neural network mechanisms: ## 1. Transformer Architecture Foundation **Self-Attention Mechanism** - Each token attends to all previous tokens in the sequence - Creates dynamic memory representations through attention weights - Enables context-dependent information retrieval **Multi-Head Attention** - Multiple parallel attention mechanisms capture different types of relationships - Each head specializes in different aspects of memory (syntactic, semantic, positional) ## 2. Memory Types in GPT **Parametric Memory** - Knowledge encoded in model weights during training - Distributed across billions of parameters - Contains factual knowledge, patterns, an

Haven't you ever had this kind of question while learning AI?

  • "Can AI really think like humans?"

  • "How is GPT's memory possible?"

  • "Why is it called a Neural Network?"

In fact, the core structure of artificial intelligence started from the human brain.
CNN resembles the brain's visual cortex, RNN mimics feedback neural networks, and GPT is modeled after the human memory system.

This lecture insightfully explores the connection between neuroscience and AI,
opening your eyes to understanding AI not as mere technology but as a 'thinking system'.

Features of this course

  1. 🧠 Neuroscience × AI Structure Integrated Learning

    • Intuitively understand how AI technologies like CNN, RNN, and Transformers mimic actual brain structures


  2. 👤 Human vs Machine: Comparison of Cognitive Methods

    • "Can AI think like humans?"

    • Scientific Exploration of Similarities and Differences Between the Brain and AI

  3. 🔁 Intensive Analysis of Memory·Learning·Feedback Structure

    • Interpreting the 'Principles of Memory and Connection' that Made GPT Possible from a Neuroscientific Perspective

  4. 📌 Brain-based AI Philosophy + Practical Application

    • Not just memorizing simple concepts, but acquiring perspectives on AI and planning insights

I recommend this for people like this

Learners who want to explore the intersection of neuroscience and AI technology

From a neuroscientific perspective, AI

Non-majors and developers who want to understand

AI concepts for education planners who want a more intuitive understanding

After taking the course

✅ You can understand the big picture of how neuroscience has influenced AI algorithms.
✅ You can explain the neuroscientific origins of major AI architectures such as CNN, RNN, and Transformers.
✅ You can answer the question "Does AI remember like humans?" with scientific evidence.
✅ You can compare how GPT works with brain memory mechanisms and think critically about AI's possibilities and limitations.

You'll learn this kind of content.

Introduction Question

Recognize key issues and context in advance, and establish a reference point for thinking that allows you to follow the flow of the lecture.

Using Visual Materials

I structured it so you can intuitively understand actual research graphs, experimental photos, and various concepts.

Key Keyword Summary

We organize key concepts so you can review what you've learned at a glance.

Course Conclusion

Provides summary screens that organize key content for each course, making review and organization happen naturally.

The person who created this course

AIder College

Professor Lee Sang-wan

  • Current) Director of KAIST Neuroscience/AI Convergence Research Center

  • Currently) Associate Professor, Department of Bio and Brain Engineering, KAIST

  • 📖Books: 《How Artificial Intelligence and the Brain Think》

👉 Korea's top neuroscience and AI convergence expert teaches directly.

Recommended for
these people

Who is this course right for?

  • A general person who wants to learn about the connection between neuroscience and AI

  • Non-CS developers looking to enter the AI field

  • Professors and instructors who want to design AI education curricula

Hello
This is

Aider College는 ‘AI를 친근하게, 쉽게, 제대로’ 가르치는 AI교육전문 브랜드 입니다.

서울대, KAIST, 한양대, 서울여대 등 국내 최고 교수진이 직접 참여하여, 기술 + 철학 + 윤리 + 인사이트를 모두 담은 독창적인 커리큘럼을 통해 AI를 제대로 이해하고 활용하는 시민(Aider)을 양성합니다.
AI 시대, 단순한 사용법을 넘어 생각하고 판단할 수 있는 AI 역량을 함께 키워갑니다.

Curriculum

All

16 lectures ∙ (3hr 39min)

Published: 
Last updated: 

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