The AI Naming Conundrum
Just six hours after OpenAI launched GPT-4.1, CEO Sam Altman was already apologizing for the model’s name. The issue wasn’t about AI hallucinations or bias, but rather the confusing nomenclature. GPT-4.1 seemed nonsensical to many, especially with previous models like GPT-4o and GPT-4.5 already in existence. Altman’s apology highlighted a broader problem in the AI industry: companies are struggling to come up with meaningful and coherent names for their models.
The history of AI model naming is a story of inconsistency and confusion. OpenAI initially used a numeric system, progressing from GPT-1 to GPT-4. However, they’ve now deviated from this linear progression, introducing models like GPT-4o and GPT-4.5. This has left users confused about which model is the most recent or what features they offer.
Other AI companies are facing similar challenges. Anthropic, founded by OpenAI alumni, has moved to decimal numbering for their Claude models, but also names individual models after literary works like Opus, Sonnet, and Haiku. Google’s Gemini model is named after the zodiac sign, symbolizing duality, but also has versions like Flash, Pro, and Ultra. Meta’s Llama family of models is named in a way that’s been described as overly smiley and cloying.
So, what makes a good AI model name? Ideally, it should reflect the company’s progress and hint at the model’s capabilities. A well-chosen name can also be a branding opportunity, conveying the company’s values or mission. Early AI companies like DeepMind and OpenAI understood this, with names that reflected their focus on depth and transparency.
To improve, AI companies need to rethink their naming strategies. Model names should be clear, consistent, and meaningful. They should help users understand the model’s purpose and features, rather than causing confusion. As the AI landscape continues to evolve, companies that get their naming conventions right may have an edge in establishing their brand identity.
Key Takeaways
- AI companies are struggling with naming their models in a clear and consistent manner.
- Confusing names can lead to user frustration and undermine the model’s credibility.
- A good name should reflect the model’s capabilities and the company’s values.
- Consistency in naming conventions is key to avoiding user confusion.
- Rethinking naming strategies can help AI companies establish a stronger brand identity.
