The video discusses rumors that OpenAI may be withholding the release of GPT-5 to leverage its internal version for data generation and model improvement, suggesting a greater return on investment from keeping it private. It also highlights a similar strategy by Anthropic, which opted to enhance its Claude 3.6 model using an internal version of Opus 3.5, indicating a shift in AI development towards efficiency and performance rather than just increasing model size.
The video discusses rumors surrounding GPT-5, suggesting that OpenAI may have developed the model but is withholding its release for strategic reasons. The presenter references an article by Alberto Romero, which posits that OpenAI’s internal version of GPT-5 is already influencing the AI landscape without being publicly available. The hypothesis is that the return on investment (ROI) for keeping GPT-5 internal is greater than releasing it to the public, as the company may be leveraging it for data generation and model improvement rather than immediate financial gain.
The video also touches on the mysterious absence of Anthropic’s Opus 3.5 model, which was expected to compete with GPT-4. Instead of releasing Opus 3.5, Anthropic introduced an updated version, Claude 3.6, which reportedly outperformed existing models. The presenter suggests that Anthropic may have used Opus 3.5 internally to generate synthetic data, enhancing the performance of Claude 3.6. This practice of model distillation, where a more powerful model is used to improve a smaller, more efficient one, is becoming a common strategy among AI labs.
The discussion highlights how both OpenAI and Anthropic are navigating the challenges of developing advanced AI models while managing operational costs. The video emphasizes that the trend is shifting from simply increasing model size and parameters to improving efficiency and performance through distillation. Smaller models, like GPT-4 and Claude 3.6, are reportedly outperforming their larger predecessors, indicating a new paradigm in AI development that prioritizes cost-effectiveness and performance over sheer size.
The presenter speculates that OpenAI may be following a similar path as Anthropic, potentially using GPT-5 internally to enhance future models while avoiding public release. This strategy could allow OpenAI to maintain a competitive edge without the financial