Why making Bigger LLMs Won’t Lead to AGI And What We’re Missing
Last Updated on December 9, 2025 by Editorial Team
Author(s): Sayan Chowdhury
Originally published on Towards AI.
Why making Bigger LLMs Won’t Lead to AGI And What We’re Missing
Every few months, a new AI model is released that feels smarter, faster, and more capable than the last. Chatbots can write essays, compose music, debug code, and even pass exams. Naturally, many people wonder:
The article discusses the reasons why larger language models (LLMs) do not inherently lead to artificial general intelligence (AGI), emphasizing the differences in understanding, real-world experience, goal-directed behavior, and the limitations that current AI models face. It outlines the necessary qualities for AGI, such as agency and the ability to set goals, while highlighting that LLMs are primarily advanced pattern recognition systems without true comprehension or autonomy. The text concludes by suggesting that while LLMs are valuable tools in the AI landscape, they are not sufficient on their own to achieve AGI, which requires a broader technological approach including embodied learning and true reasoning capabilities.
Read the full blog for free on Medium.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.
Published via Towards AI
Towards AI Academy
We Build Enterprise-Grade AI. We'll Teach You to Master It Too.
15 engineers. 100,000+ students. Towards AI Academy teaches what actually survives production.
Start free — no commitment:
→ 6-Day Agentic AI Engineering Email Guide — one practical lesson per day
→ Agents Architecture Cheatsheet — 3 years of architecture decisions in 6 pages
Our courses:
→ AI Engineering Certification — 90+ lessons from project selection to deployed product. The most comprehensive practical LLM course out there.
→ Agent Engineering Course — Hands on with production agent architectures, memory, routing, and eval frameworks — built from real enterprise engagements.
→ AI for Work — Understand, evaluate, and apply AI for complex work tasks.
Note: Article content contains the views of the contributing authors and not Towards AI.
Related posts
Recent Posts
