Earlier this week, OpenAI released their "most advanced image generator yet" and made it available through ChatGPT using the GPT-4o model. ChatGPT previously relied on Dall-E to generate images. According to OpenAI, the improved 4o model is able to produce precise, accurate, and photorealistic results. They claim that it's also particularly good at rendering text, following instructions precisely, and even understanding the context of a chat. All of this includes the transformation of uploaded images or using uploaded images as visual inspiration.

These types of models are most effective at solving complex problems, so if you have any PhD-level math problems you're cracking away at, you can try them out. Alternatively, if you've had issues with getting previous models to respond properly to your most advanced prompts, you may want to try out this new reasoning model on them. To try out o3-mini, simply select "Reason" when you start a new prompt on ChatGPT. Although reasoning models possess new capabilities, they come at a cost. OpenAI's o1-mini is 20 times more expensive to run than its equivalent non-reasoning model, GPT-4o mini. The company says its new model, o3-mini, costs 63% less than o1-mini per input token However, at 1.10 per million input tokens, it is still about seven times more expensive to run than GPT-4o mini.

Today OpenAI is releasing a new and improved version of its Codex AI model to the public. Codex is a descendant of OpenAI's GPT-3, which was released last summer. While Codex shares the same data as its predecessor, it has an added advantage in that it can read and then complete text prompts submitted by a human user. The Codex is like the GPT-3 language engine, but it was only trained on coding. In the latest, OpenAI has made some big changes to Codex by now accepting commands in plain English as well. This allows someone who is building a game or web app without naming any variables whatsoever, and they get live working code back quickly with no hassle.