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.

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 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.

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.

The main advantages of GPT-4 include faster response times, sharper reasoning that reduces misunderstandings, and more natural language that feels relatable rather than robotic.

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

GPT-4.5 is potentially more than 10 times the size of GPT-4, representing a step forward in both pre-training and post-training processes.

GPT-3 made headlines by smashing benchmarks previously considered out of reach for AI, excelling in software engineering, math, and PhD-level science questions.

The longer models like GPT-3 are able to think through complex problems, the better they perform.