Why Everybody is Talking About ‘Q’ . . .
Q! This seems to be the letter of the day. Sam Altman made an intriguing announcement that has everyone in AI excited about what Q-star might be.
As most know, OpenAI, went through some major internal changes. After this, a report came out about a breakthrough at OpenAI involving a program called "Q-Star" or "Q*." This discovery seems to have played a role in the issues at OpenAI.
There’s talk that some of OpenAI employees had written to the company's board, warning about a powerful AI discovery related to Q that could be dangerous for humanity. This was one reason among others that led to Altman's removal from his position, according to anonymous sources.
Honestly, this story seems a bit wild. What is this Q program, and why did it cause so much trouble at OpenAI? Some suggest Q* could do basic math at a grade-school level, a significant step if true, because it might lead to bigger advances in AI. But OpenAI hasn't officially shared anything about Q, leaving us with guesses and rumors.
Some think Q might be linked to Q-learning, a type of machine learning. There are different ways to teach AI: supervised learning (like how ChatGPT was trained with lots of labeled data), unsupervised learning (where AI finds patterns in unlabeled data, used by companies like Netflix for recommendations), and reinforced learning (RL), where AI is rewarded for certain actions. Q-learning is part of RL, where AI learns through trial and error.
So, could Q* have used some form of Q-learning to do math? Maybe, but many experts here doubt AI can reliably solve math problems now. They also think being good at math doesn't necessarily mean an AI is close to general intelligence. Researchers have tried to get AI to solve math problems for years, but success is limited. Deep learning and neural networks are great at spotting patterns, but that might not be enough for solving math problems.
At the end of the day, we don't know much about Q. It's interesting, but some experts think the excitement might be overblown.
