Open AI released their new “Strawberry” system with advanced reasoning capability. The launch of this o1 model came with a couple of impressive looking charts about its performance.
I loved reading Prof Ethan Mollick’s blog post about his experience as a preview user. He shares a great example of Strawberry in action when he gives the model a challenging crossword puzzle.
The AI “thinks” about the problem first, for a full 108 seconds (most problems are solved in much shorter times). You can see its thoughts, a sample of which are below (there was a lot more I did not include), and which are super illuminating – it is worth a moment to read some of it.
The LLM iterates repeatedly, creating and rejecting ideas. The results are pretty impressive, and it does well..
He goes on to explain that it isn’t without its limitations. Errors and hallucinations still happen for example. And it still seems to be limited by GPT 4o’s “intelligence.”
But jhe ends with a thought provoking note on where we’re headed.
Using o1-preview means confronting a paradigm change in AI. Planning is a form of agency, where the AI arrives at conclusions about how to solve a problem on its own, without our help. You can see from the video above that the AI does so much thinking and heavy lifting, churning out complete results, that my role as a human partner feels diminished. It just does its thing and hands me an answer. Sure, I can sift through its pages of reasoning to spot mistakes, but I no longer feel as connected to the AI output, or that I am playing as large a role in shaping where the solution is going. This isn’t necessarily bad, but it is different.
As these systems level up and inch towards true autonomous agents, we’re going to need to figure out how to stay in the loop – both to catch errors and to keep our fingers on the pulse of the problems we’re trying to crack. o1-preview is pulling back the curtain on AI capabilities we might not have seen coming, even with its current limitations. This leaves us with a crucial question: How do we evolve our collaboration with AI as it evolves? That is a problem that o1-preview can not yet solve.
I read this with fascination as I spend a significant part of my day thinking through how to apply the power of these models to make it easier for hirers and jobseekers to get matched to the right opportunity.
And the rate of change we’re seeing in the intelligence of these models ensures the learning curve continues to be steep.
