AI ภาคธุรกิจ 2025: องค์กรยังใช้ ML/DL มากกว่า LLM เช่น ChatGPT?

Summary

Public attention has gone to large language models, but inside organisations most of the work still runs on conventional machine learning and deep learning.

The reason is accuracy and reliability, which matter more than general capability wherever the stakes are real.

The talk sets out which kind of AI suits which task, with examples from Thailand and abroad.

Key points

1. 01

   Generality and accuracy are different objectives

   A model that can do everything is not the model that does one thing best.

2. 02

   Measurable work still belongs to conventional ML

   Demand forecasting, fraud detection and quality control need numbers you can trust.

3. 03

   LLMs excel where there is no single right answer

   Summarising, drafting and searching are tasks where flexibility beats absolute precision.

4. 04

   The right question is which tool for which job

   This is not new technology replacing old, but matching the instrument to the work.