Is DeepMind’s AlphaGeometry the Future of AI in Deep Reasoning?

By: Rooz Aliabadi, Ph.D.

Google DeepMind’s latest creation, AlphaGeometry, is an AI system making waves in mathematics, particularly geometry. This is inspiring news because, traditionally, math has been a challenging area for artificial intelligence. Geometry problems, filled with symbols and specific rules, are especially tough. They’re different from what most AI systems, which are better with words, usually handle. But AlphaGeometry is stepping up to the challenge and showing that AI can be good at math, too.

AlphaGeometry is unique because it combines two types of AI technology. The first part is like a language model, which is good at recognizing patterns, like the kind you see in sentences. The second part is a symbolic engine. This is the logical thinker of the pair, working with rules and logic to solve problems. Think of it as having a brainstorming buddy and a logic expert working together to solve a challenging puzzle.

To test how good AlphaGeometry is, DeepMind used problems from the International Mathematical Olympiad. These aren’t your everyday math problems; they’re hard and meant for the world’s brightest high school math students. AlphaGeometry did a fantastic job, solving 25 out of 30 issues. To put that in perspective, the best system before this could only solve 10. That’s a giant leap forward and shows we’re making significant strides in AI.

However, training AlphaGeometry was challenging. Because geometry problems are so specific and few are lying around, the DeepMind team had to create many new issues for the AI to learn from. They made nearly half a billion geometry diagrams and used them to teach AlphaGeometry how to solve these problems. This is like giving a student many practice questions so they get good at solving them.

The cool thing about AlphaGeometry is that it’s not just about solving math problems. This kind of technology can help in many other areas. For example, geometry can be super helpful in computer vision, which is how computers understand and process images. It’s also beneficial in fields like architecture, where designing buildings involves a lot of geometric planning, and in theoretical physics, where understanding the shapes and patterns of the universe is vital.

Even though AlphaGeometry is doing great, more work must be done. Right now, it’s good at solving high school-level problems, but the more abstract and complex issues that university students and researchers work on still need to be addressed. The dream is to have AI like AlphaGeometry that can tackle these advanced problems and develop new ideas or solutions that have yet to be considered.

This development in AI, where it’s starting to improve at logical thinking and problem-solving, is super important. It’s about more than just getting the correct answers in math. It’s about showing that AI can think and reason in ways that are similar to humans. With systems like AlphaGeometry, we’re moving closer to a future where AI can help us in various ways, from everyday problem-solving to unlocking new mysteries in science and mathematics.

This article was written by Rooz Aliabadi, Ph.D. (rooz@readyai.org). Rooz is the CEO (Chief Troublemaker) at ReadyAI.org

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