History and Development of LLMs
It explains in detail the various language models developed in the process, starting from the beginnings of natural language processing technology to the latest LLM models.
21 learners are taking this course
Level Beginner
Course period Unlimited
NLP
NLP
RNN
RNN
self-attention
self-attention
transformer
transformer
LLM
LLM
NLP
NLP
RNN
RNN
self-attention
self-attention
transformer
transformer
LLM
LLM
Notice of Revised Video Posting Schedule
# Lecture 07. History and Development of LLMs
## Notice of New Lesson Postings
Hello, students! For this course, **82** new lessons (across a total of 13 sections) are scheduled to be posted sequentially. Since I am producing multiple courses simultaneously, I am proceeding by posting **a little bit of each course alternately**, rather than uploading one entire course at once. Below are the posting principles and the schedule for each section of this course.
> For your reference, the lessons being posted now are not entirely new content, but part of the production of **revised editions (2nd or 3rd editions)** that reinforce existing lectures.
## Posting Principles
- Currently, I am rotating through a total of 19 courses in order (circular method), posting one lesson per course alternately.
- Postings take place on weekdays (Mon–Fri), with a total of 5 new lessons uploaded daily across all courses.
- For this course, the next lesson will be posted each time its turn comes around in the rotation.
- While the posting speed may feel slow compared to other courses, all courses are progressing together in the same manner.
## Posting Schedule by Section (13 Sections Total)
| Section | Number of Lessons | Start Date | End Date |
|---|---|---|---|
| Section 1. Origins and Early Development of Language Models | 2 | 2026-07-02 | 2026-07-08 |
| Section 2. Emergence of Distributional Hypothesis and Evolution of Word Representation | 7 | 2026-07-13 | 2026-08-13 |
| Section 3. Limitations of Static Embeddings and Recognition of the Need for Context | 6 | 2026-08-19 | 2026-09-15 |
| Section 4. Tokenization Methods and Solving the Out-of-Vocabulary (OOV) Problem | 7 | 2026-09-21 | 2026-10-22 |
| Section 5. ELMo - The Beginning of Contextual Embeddings | 7 | 2026-10-27 | 2026-11-27 |
| Section 6. Transformer and Self-Attention Mechanisms | 7 | 2026-12-03 | 2027-01-04 |
| Section 7. BERT - The Revolution of Bidirectional Contextual Learning | 7 | 2027-01-08 | 2027-02-05 |
| Section 8. Variant Models of BERT | 6 | 2027-02-10 | 2027-03-03 |
| Section 9. GPT and Expansion to Sentence-Level Representation - The Peak of Contextual Embeddings | 8 | 2027-03-08 | 2027-04-05 |
| Section 10. The Transformer Revolution and the Era of Large Language Models | 4 | 2027-04-08 | 2027-04-20 |
| Section 11. Latest LLM Models and Technological Advancements | 7 | 2027-04-23 | 2027-05-18 |
| Section 12. LLM Efficiency Technologies and Advancements in Model Optimization | 7 | 2027-05-20 | 2027-06-14 |
| Section 13. LLM Applications, System Integration, and Future Outlook | 7 | 2027-06-16 | 2027-07-08 |
## Estimated Completion
Based on the current pace, the estimated completion date for all postings in this course is around **July 2027**. (The actual schedule may be moved up or delayed depending on production progress.)
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