The Challenge of GPT-4: The Direction of OpenAI’s Next-Generation Models as Indicated by gpt2-chatbot

GPT-4 Performance and Challenges

OpenAI’s GPT-4 demonstrates excellent performance as a commercial-grade large language model (LLM). However, there is now a demand for models that are efficiently created by improving the quality of training data and reducing operational resources. Due to its resource-intensive nature, GPT-4 could ironically become a hindrance to OpenAI.

The Need for New Models

For OpenAI, creating new models early on is crucial. The GPT-4 lineage, being initially quantity-focused rather than quality-focused, resulted in a super inefficient model. Llama3, a 70B model created with improved training data, exhibits GPT-4 equivalent performance in English alone and can be run on a home PC. Continuously maintaining GPT-4 would be incredibly wasteful, and OpenAI likely aims to complete and release high-efficiency models.

The recently discussed ‘gpt2-chatbot,’ speculated to be a new high-efficiency model under development by OpenAI, may surpass GPT-4 in performance, hinting at possibilities for OpenAI’s next-generation models like GPT-4.5 or GPT-5.

Achievements and Issues of GPT-4

At the time, creating high-performance models with a high number of parameters through extensive training data was the norm, justifying the existence of GPT-4. While GPT-4 has contributed to the birth of current high-performance models, its status as a high-parameter model also poses resource usage issues. Further investing resources into the resource-hungry GPT-4 would strain management.

Future Direction of OpenAI

OpenAI likely aims to release models with improved training data quality and reduced parameters. This would allow reallocating resources from current GPT-4 operations to training new models. Taking Llama3 as an example, training it primarily in English at 70B would suffice, even if extended to five languages, only requiring 350B.

The emergence of gpt2-chatbot may serve as evidence of OpenAI progressing in this direction. If gpt2-chatbot serves as a precursor to GPT-4.5 or GPT-5, OpenAI is steadily approaching the completion of high-efficiency models.

Conclusion

While acknowledging the accomplishments of GPT-4, OpenAI should focus on developing new high-efficiency models to overcome its challenges. Creating models with reduced parameters using high-quality training data is crucial for efficiently utilizing resources while achieving high performance.

The emergence of gpt2-chatbot suggests that OpenAI is steadily advancing in this direction. The future direction of OpenAI will be closely watched.