Why GPT Will Never Match a Freshman Mechanical Engineer
Why GPT Will Never Match a Freshman Mechanical Engineer
Why GPT Will Never Match a Freshman Mechanical Engineer
The Leo AI Team
Yann LeCun, one of the godfathers of modern AI, recently said:
“Large language models will never get to human level by just training on text. We’ve got to train models to understand the real world.”
For mechanical engineers, this statement feels like common sense.
It doesn’t matter how massive GPT becomes,
how many billions of dollars are invested in OpenAI,
or how much data it consumes from the internet —
it will never match the skills of a first-year mechanical engineering student at a community college when it comes to something as basic as matching a bolt to a hole.
Why LLMs Can’t Think Like Engineers
The reason is simple: GPT is a language model. And language can’t describe geometry.
Ask any engineer to explain a mechanical concept, and within a minute, they’ll grab a marker and sketch it on a whiteboard (badly, usually). We think in shapes, constraints, and spatial relationships — not just words.
From Words to Parts: Introducing the Large Mechanical Model (LMM)
That’s why at Leo AI, we built the first Large Mechanical Model (LMM).
Unlike LLMs that use words as tokens, the LMM uses mechanical parts as tokens. It’s designed to understand CAD — not just read descriptions of CAD.
This allows engineers to:
Search CAD parts across internal PLM systems and online catalogs using free language.
Understand geometric constraints and relationships between parts.
Soon: Generate assemblies and complete product designs directly from a description.
Why We Built It
We’re not building a new foundational model because we want to look cool.
We don’t care about writing patents for the sake of press coverage or publishing papers to collect citations.
We built it because we had no choice.
For engineers to search and design effectively with AI, the model must think in geometry — something LLMs will never do.
The Future of AI in Mechanical Engineering
Yann LeCun’s statement is a reminder that AI for engineering requires more than scaling up language models. It requires models that see and reason about the physical world — the way engineers do.
With Leo AI’s LMM, mechanical engineers finally have a tool that:
Speaks their language (geometry).
Works with their tools (CAD, PLM).
Supports their workflows (design, assembly, manufacturing).
Join thousands of mechanical engineers already using Leo AI’s LMM to design smarter and faster.
Try Leo AI free for and experience the difference of physics-aware AI in your workflow.
Book a demo: https://www.getleo.ai/contact
Try Leo Free: www.getleo.ai
Yann LeCun, one of the godfathers of modern AI, recently said:
“Large language models will never get to human level by just training on text. We’ve got to train models to understand the real world.”
For mechanical engineers, this statement feels like common sense.
It doesn’t matter how massive GPT becomes,
how many billions of dollars are invested in OpenAI,
or how much data it consumes from the internet —
it will never match the skills of a first-year mechanical engineering student at a community college when it comes to something as basic as matching a bolt to a hole.
Why LLMs Can’t Think Like Engineers
The reason is simple: GPT is a language model. And language can’t describe geometry.
Ask any engineer to explain a mechanical concept, and within a minute, they’ll grab a marker and sketch it on a whiteboard (badly, usually). We think in shapes, constraints, and spatial relationships — not just words.
From Words to Parts: Introducing the Large Mechanical Model (LMM)
That’s why at Leo AI, we built the first Large Mechanical Model (LMM).
Unlike LLMs that use words as tokens, the LMM uses mechanical parts as tokens. It’s designed to understand CAD — not just read descriptions of CAD.
This allows engineers to:
Search CAD parts across internal PLM systems and online catalogs using free language.
Understand geometric constraints and relationships between parts.
Soon: Generate assemblies and complete product designs directly from a description.
Why We Built It
We’re not building a new foundational model because we want to look cool.
We don’t care about writing patents for the sake of press coverage or publishing papers to collect citations.
We built it because we had no choice.
For engineers to search and design effectively with AI, the model must think in geometry — something LLMs will never do.
The Future of AI in Mechanical Engineering
Yann LeCun’s statement is a reminder that AI for engineering requires more than scaling up language models. It requires models that see and reason about the physical world — the way engineers do.
With Leo AI’s LMM, mechanical engineers finally have a tool that:
Speaks their language (geometry).
Works with their tools (CAD, PLM).
Supports their workflows (design, assembly, manufacturing).
Join thousands of mechanical engineers already using Leo AI’s LMM to design smarter and faster.
Try Leo AI free for and experience the difference of physics-aware AI in your workflow.
Book a demo: https://www.getleo.ai/contact
Try Leo Free: www.getleo.ai