The core idea behind GPT-1 was that using a transformer to predict the next word would provide enough signal to generate coherent text, a concept that seemed obvious in hindsight but was initially doubted.

In testing GPT-4.5, we found it has nuanced abilities that were unexpected, indicating it is more intelligent in ways that are hard to characterize ahead of time.

The GPT architecture excels at efficiently absorbing and generalizing data, but as compute resources grow, data becomes the bottleneck, necessitating algorithmic innovations to learn more from the same amount of data.

GPT-4's extensive knowledge comes from multiple copies running on different hardware, allowing them to share learning efficiently, unlike human brains.

The recent advancements in unsupervised learning, particularly with models like GPT-2, indicate that we are approaching a point where machines exhibit a form of consciousness.

GPT-4.5 is OpenAI's largest and most humanlike model to date, representing a significant step in scaling up unsupervised learning and achieving a deeper understanding of the world and human experience.

The defining characteristics of the GPT paradigm are that you can predict the test loss, and it scales predictably, leading to greater intelligence in various intangible ways.

GPT-4.5 shows that scaling unsupervised learning continues to yield valuable improvements in accuracy, emotional intelligence, and creativity, even if these gains are now more incremental than before.

The release of GPT-4 marked a significant turning point, as it performed much better than previous models, achieving results that surpassed 90% of test takers in legal assessments.