AI safety is a big challenge. Imagine you have a button and a cup of tea. If you hit the button, the AI gets some reward. If it stops you and gets the tea, the AI gets a bigger reward. Now, what if you make the button reward equal to the tea reward? The AI might just shut down because that’s quicker and easier than getting the tea.
This idea shows how tricky it is to make AI safe. A video from 2017 discussed these problems. It’s crazy because things predicted back then are still problems now.
OpenAI needs to do more safety research. Recently, only Anthropic did some work in this area. They looked at how to control Claude, their AI, by making it think about specific things. More research like this is needed.
A recent paper talked about using synthetic data for AI. Synthetic data is fake data made by AI to train other AIs. This new research used AI to create math problems and their solutions. This helped train another AI in solving math proofs.
Math proofs are important but hard to make. AI could help, but it needs lots of examples. The researchers created many math problems and trained an AI on them. This AI did better than GPT-4. It proved 5 out of 148 problems from a tough math test, while GPT-4 proved none.
This shows synthetic data can boost AI’s skills in tough areas like math. The researchers plan to open-source their work. This means others can build on it. This approach suggests self-improving AI might be closer than we think.
Companies like OpenAI and Google are looking into this. They want AI to help with science, math, and physics. AI in these fields could really push our understanding of the world forward. The future of AI research looks exciting with these new developments.