Proprietary AI models reduce operational costs
The guest argued that fine-tuning and deploying proprietary AI models is significantly cheaper and more effective for specific business tasks than relying on generic frontier models.
The argument
He noted that Wix achieved a 1% to 30% cost reduction by training and running its own model for website generation. This approach also allows for a continuous feedback loop to improve quality based on specific user data.
The thesis, stress-tested
✓ What validates it
- ✓Wix reporting improved gross margins or lower infrastructure costs in subsequent quarterly reports
- ✓Increased user adoption and satisfaction metrics for Wix's AI-generated websites
▸ Risks discussed
- ▸High upfront R&D costs to train proprietary models
- ▸Rapid improvements in frontier models making proprietary models obsolete or uncompetitive
Hear it yourself
"So on Wix, when you generate a website today, we are running a model that we trained. And it's faster, it's cheaper, but it's also better, and it makes less errors. And we keep improving it because we have continuous, right, a continuous improvement loop, feedback loop because we see when customers like something."
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