The reasoning models push the capabilities of GPT models further, allowing for better performance by thinking step by step.

OpenAI revealed GPT-4.5 as a model capable of reasoning and systematically thinking through complex problems, clearly surpassing GPT-4 in mathematics, coding, and logical tasks.

By allowing models to think longer, large language models can leverage more compute on the fly, enhancing their intelligence for complex problems.

With the release of GPT-3, it seems the sky is the limit for this new paradigm of scaling large language models.

The evolution of language models, particularly with the introduction of GPT-3, has demonstrated a significant leap in their ability to perform language tasks, even though they do not possess real-world knowledge.

A model that combines the knowledge and intuition of GPT-4.5 with advanced reasoning capabilities would be exceptionally powerful, making GPT-4.5 a crucial bridge towards that future.

Research indicated that previous models like GPT-3 were undertrained; despite their size, they hadn't been trained on enough text to reach their full potential. For instance, Chinchilla, a model smaller than GPT-3, outperformed larger models by being trained on four times more data.

GPT-3 represents a huge leap forward, not just a small improvement over its predecessors, and researchers believe this trajectory will continue.

The ability to allow AI models to reason for extended periods, rather than just providing quick answers, can lead to significantly better outcomes for complex questions.