NVIDIA NVLM: ELIZA on Steroids
NVIDIA has entered the ring with NVLM – a powerful multimodal language model that understands images, writes code, and aims to rival GPT-4o. Yet under the hood, the same old structure remains: a predictive statistical model pretending to understand. Welcome back, ELIZA – now with 72 billion parameters.
What is NVLM?
- Architecture: Decoder-only LLM based on Qwen2-72B
- Multimodality: Text and images via InternViT-6B vision encoder
- Benchmarks: Outperforms GPT-4o in OCRBench, MathVista, ChartQA
- Open Source: Model weights and training code available (Hugging Face)
The Eliza Effect Reloaded
The original Eliza effect describes the illusion of understanding triggered by simple yet convincing dialog patterns.
NVLM perfects this illusion: bigger models, more data, image recognition, fluent responses.
But just like Eliza, it only pretends to understand.
Open Source or Open Deception?
- Pros: Transparency, reproducibility, community access
- Cons: More convincing deception via technical brilliance
- Question: Can openness legitimize what is structurally misleading?
What’s Missing: Thought, Meaning, Awareness
Despite its 72 billion parameters:
- No semantic understanding
- No intention, no consciousness
- Just probabilities – no meaning
Like Eliza – just more convincing, broader, and more dangerous.
A system that simulates, not comprehends.
Conclusion
NVLM is technically impressive – but structurally disappointing.
It’s another milestone in the GPT family, not a break from it.
More compute, more modalities – but still: ELIZA on Steroids.