AI Models - A Race To The Bottom
AI Summary
Summary of Video Transcript
Token Costs: Costs for AI tokens have dropped dramatically from $60 per million tokens to mere cents per million tokens in two years since GPT-3’s release.
Industry Impact:
- Competition: The AI industry is experiencing intense competition, primarily on output quality and pricing, with other factors like speed, UI/UX, and product features also being important.
- Model Wars: There’s a distinction between those who can create models (limited to those with specific resources) and those who can innovate in other areas.
- Assumptions Challenged: The belief that only model creators could profit in AI has been proven wrong as others are successfully building better products using existing models.
- Competing on Context Window: Mostly model makers can impact this, but there are ways to “hack” it from the outside.
Quality vs. Price:
- Quality: OpenAI has set the bar for quality, with other companies racing to catch up. The gap in quality is closing as competitors release models that approach the quality of OpenAI’s offerings.
- Price: There’s been a significant drop in price, with competitors often starting at lower price points and engaging in a race to the bottom.
Model Wars Breakdown:
- Quality Over Time: GPT-3 marked a significant leap in quality, but subsequent improvements (3.5, 4, 4.1) have seen diminishing returns.
- Price Over Time: The cost has plummeted, with alternatives consistently undercutting OpenAI’s pricing.
Market Dynamics:
- OpenAI’s Position: OpenAI leads in quality but is being forced to catch up on price due to competitive pressures.
- Strategic Pricing: OpenAI’s pricing decisions, such as with GPT-3.5 and GPT-4, are influenced by competition.
- Cost of Running Models: OpenAI’s subscription costs are not purely profit-driven; they reflect the high costs of running the models.
Industry Trends:
- Commoditization: As AI models become more commoditized, the competitive advantage shifts away from model creation to product development.
- Ease of Switching: The ease of switching between AI models for developers means that providers must compete fiercely on both quality and price.
- Future Focus: Companies like OpenAI may shift focus from competing on models to competing on products due to the commoditization of AI models.
Personal Involvement: The speaker has been motivated by the competitive pricing and quality of models like DeepSeek V3 to create their own AI app, T3 chat.
Conclusion: The AI industry is undergoing rapid changes with a focus on lowering prices and improving quality, leading to a highly competitive market where product innovation may become the key differentiator.
Detailed Instructions and URLs
- No specific CLI commands, website URLs, or detailed instructions were provided in the transcript.