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.

We integrated some of the improvements from GPT-4.5 into our mainline GPT-4 model to enhance its collaborative capabilities.

When we launched GPT-4.5, we were proud of the model, but users liked it much more than we anticipated, expressing that it was significantly better than GPT-4 in various ways.

Codex works with GPT-4.1 and other models, and we're excited to see what you build with it.

GPT-4o's improved intuition and proactive questioning make it feel like a colleague that understands the team's intents, helping to accelerate workflow.

These enhancements allow GPT-4 to communicate more naturally, resembling the interaction with a real teammate, which is beneficial for team collaboration.

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

Using GPT-4o improves trust and engagement within teams, allowing for quicker answers without struggling with the tool.