Key Takeaways
- Google DeepMind’s Dreamer has learned to mine diamonds in Minecraft.
- The task is seen as a key milestone for self-learning AI.
- Games are increasingly used to test and train AI.
In efforts to build more capable, agentic AI systems, researchers have turned to games as an ideal learning environment.
Following this strategy, Google DeepMind’s AI platform, Dreamer, recently mastered a key task researchers have used to assess AI capabilities—obtaining diamonds in Minecraft.
AI Overcomes Minecraft Diamonds Challenge
For AI researchers, Minecraft is useful for teaching AI problem-solving and spatial reasoning.
For AI systems that may one day be called on to interact with physical environments, the game provides a more lifelike alternative to traditional performance benchmarks.
While relatively easy for human players, obtaining diamonds in Minecraft is a complex task for AI. To mine diamond ore, users must make a strong enough pickaxe, which requires multiple steps.
OpenAI managed to achieve the feat in 2022 by training a neural network on 70,000 hours of labeled gameplay video.
In contrast, Dreamer’s recent breakthrough is noteworthy because the AI is dropped into the game without prior experience and must learn skills independently through trial and error.
Games as AI Benchmarks
As interest in reinforcement learning and real-world AI applications grows, Minecraft isn’t the only game researchers use to test and train AI.
Previously, Dreamer learned to perform actions on classic Atari games and DeepMind’s DM Lab, a suite of 3D navigation and puzzle-solving tasks.
Chatbot Showdown
While reinforcement learning agents like Dreamer are specifically designed to operate in virtual environments, in an era of rising AI computer use, even general-purpose chatbots can learn to play games.
In February, a Twitch channel called ClaudePlaysPokemon started streaming videos of Anthropic’s chatbot playing Pokemon Red and Blue.
The project leverages Claude’s multimodal capabilities, relying on computer vision to interpret screenshots of the game and linguistic reasoning to determine its course of action.
Using the same technique, other popular consumer AI platforms can also learn to play games.
For example, the Hao AI Lab at the University of California, San Diego, has started comparing the performance of different platforms, such as Anthropic, Google, and OpenAI, on games like Super Mario and Candy Crush.
James Morales is CCN’s blockchain and crypto policy reporter. He has been working in the news media since 2020, writing about topics such as payments, banking and financial technology. These days, he likes to explore the latest blockchain innovations and the evolving landscape of global crypto regulation.
With an educational background in social anthropology and media studies, James uses his platform as a journalist to explore how new technologies work, why they matter and how they might shape our future.
