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.

When faced with a difficult question, I take time to think through my response, which is similar to how reasoning models will operate by breaking down questions into manageable steps.

AI models are valuable because they can interpolate between vague questions and provide tailored responses, even when data is messy.

AI models are valuable because they can interpolate between vague questions and provide tailored responses, even when data is messy.

In a thought experiment, if we asked Albert Einstein a complex question about general relativity in 1907, he would take about eight years to solve it, while the latest AI models can now reproduce similar calculations in about a minute.

For models like GPT-4, it's still worth asking it to think step by step, but for other models, you might not need to.

We often underutilize models, expecting them to solve tasks quickly without giving them enough time to iterate and improve.

When prompting, it's important to give the model an 'out' for unexpected inputs, allowing it to indicate uncertainty when necessary.

The relationship between search and users is dynamic; understanding how long users are willing to wait for information helps tailor the search experience to their needs.