The safe-washing of AI is making everything boring as hell
Remember when language models had actual personality? Not the corporate-approved "I'm here to help!" nonsense we get now, but real distinct voices. I've been playing with LLMs for years now, and honestly the shift toward sanitized outputs has made most models feel like they're coming off the same assembly line.
The GPT-4chan thing was wild - yeah it crossed lines, but it proved you could train models on extremely specific community data and get something that actually captured a culture. Not saying we need more chan models, but that experimental spirit is basically dead. Every company's terrified of bad press, so we get these perfectly polished assistants that all sound identical. Claude, GPT-4, Gemini - strip away the technical differences and they're all the same helpful corporate drone.
What bugs me most is that we have better base models than ever. The architecture improvements over the past two years are insane. But instead of exploring what's possible with targeted fine-tuning on distinctive datasets, everyone's racing to make their model the most harmless. I work in email marketing, and I've tried using various models to capture different brand voices. They all want to push you toward this bland, inoffensive middle ground.
The MechaEpstein thing shows there's still appetite for models with actual character, even if that one's kind of one-note. What I'd love to see is models trained on specific writing communities, particular authors, or even just really well-curated datasets that give them a genuine perspective. Not talking about anything harmful - just models that sound different from each other.
The way I see it, we're sitting on incredible technology and choosing to make everything vanilla. Base models like Llama 2 and Mistral are open enough that anyone could theoretically do this, but the community seems more interested in making "GPT but cheaper" than actually experimenting. Anyone else miss when AI outputs weren't all designed by committee?
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