In a new paper in Nature, DeepMind revealed that AlphaGeometry was able to solve 25 out of 30 benchmark geometry problems from past International Mathematical Olympiad (IMO) competitions within the standard time limits. This nearly matches the average score of 26 problems solved by human gold medalists on the same tests.

The AI system combines a neural language model with a rule-bound deduction engine, providing a synergy that enables the system to find solutions to complex geometry theorems.

AlphaGeometry took a revolutionary approach to synthetic data generation by creating one billion random diagrams of geometric objects and deriving relationships between points and lines in each diagram. This process – termed “symbolic deduction and traceback” – resulted in a final training dataset of 100 million unique examples, providing a rich source for training the AI system.

According to DeepMind, AlphaGeometry represents a breakthrough in mathematical reasoning for AI, bringing it closer to the level of human mathematicians. Developing these skills is seen as essential for advancing artificial general intelligence.

Evan Chen, a maths coach and former Olympiad gold medalist, evaluated a sample of AlphaGeometry’s solutions. He said its output was not just correct, but also clean, human-readable proofs using standard geometry techniques—unlike the messy numerical solutions often produced when AI systems brute force maths problems.

While AlphaGeometry only handles the geometry portions of Olympiad tests so far, its skills alone would have been enough to earn a bronze medal on some past exams. DeepMind hopes to continue improving its maths reasoning abilities to the point it could pass the entire multi-subject Olympiad.

Advancing AI’s understanding of mathematics and logic is a key goal for DeepMind and Google. The researchers believe mastering Olympiad problems brings them one step closer towards more generalised artificial intelligence that can automatically discover new knowledge.

(Photo by Dustin Humes on Unsplash)

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The move is seen as a strategic way for Google to maintain its edge in the competitive AI industry and compete with OpenAI. By combining the talent and resources of both entities, Google DeepMind aims to accelerate AI advancements while maintaining ethical standards.

The new unit will be responsible for spearheading groundbreaking AI products and advancements, and it will work closely with other Google product areas to deliver AI research and products.

Google Research, the former parent division of Google Brain, will remain an independent division focused on “fundamental advances in computer science across areas such as algorithms and theory, privacy and security, quantum computing, health, climate and sustainability, and responsible AI.”

Demis Hassabis, CEO of DeepMind, believes that the consolidation of the two AI research labs will bring together world-class talent in AI with the computing power, infrastructure, and resources to create the next generation of AI breakthroughs and products boldly and responsibly.

Hassabis claims that the research accomplishments of Google Brain and DeepMind have formed the foundation of the current AI industry—ranging from deep reinforcement learning to transformers. The newly consolidated unit will build upon this foundation to create the next generation of groundbreaking AI products and advancements that will shape the world.

Over the years, Google and DeepMind have jointly developed several groundbreaking innovations. The duo’s achievements include AlphaGo – which famously beat professional human Go players – and AlphaFold, an exceptional tool that accurately predicts protein structures.

Other noteworthy achievements include word2vec, WaveNet, sequence-to-sequence models, distillation, deep reinforcement learning, and distributed systems and software frameworks like TensorFlow and JAX. These cutting-edge tools have proven highly effective for expressing, training, and deploying large-scale ML models.

Google’s acquisition of DeepMind for $500 million in 2014 paved the way for a fruitful collaboration between the two entities. With the consolidation of Google Brain and DeepMind into Google DeepMind, Google hopes to further advance its AI research and development capabilities.

Google’s chief scientist, Jeff Dean, will take on an elevated role as chief scientist for both Google Research and Google DeepMind. He has been tasked with setting the future direction of AI research at the company, as well as heading up the most critical and strategic technical projects related to AI, including a series of powerful multimodal AI models.

The creation of Google DeepMind underscores Google and parent company Alphabet’s commitment to furthering the pioneering research of both DeepMind and Google Brain. With the race to dominate the AI space becoming more intense, Google DeepMind is poised to accelerate AI advancements and create groundbreaking AI products and advancements that will shape the world.

(Image Credit: Google DeepMind)

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