Why Did Google DeepMind Opt to Not Publish the Source Code for AlphaGo Zero and AlphaZero?

Introduction
Google DeepMind is renowned for its groundbreaking contributions to artificial intelligence. When it comes to the development and success of programs like AlphaGo Zero and AlphaZero, the company faced a crucial question: should the source code be published or kept proprietary? In this article, we will explore the reasons behind DeepMind's decision to withhold the source code and examine the implications of such a choice.

AlphaGo Zero and AlphaZero

AlphaGo Zero and AlphaZero are both artificial intelligence systems developed by Google DeepMind. AlphaGo Zero, first unveiled in 2017, marked a significant milestone in the field of AI, as it achieved the crucial ability to learn through self-play without relying on historical data from older programs like AlphaGo. This led to a major breakthrough in the field of reinforcement learning and adaptive algorithms.

The AlphaZero variant, released in 2017, further advanced the capabilities of AlphaGo Zero, demonstrating its proficiency in playing multiple games, including chess and shogi. Unlike its predecessor, AlphaZero did not require prior knowledge of the games and was able to outperform earlier versions by learning from scratch.

The Decision to Keep the Source Code Private

One of the most significant decisions made by Google DeepMind regarding these programs was the choice to withhold the source code from public access. Many in the AI community and academia question why DeepMind opted for this strategy. It is often suggested that DeepMind's decision stems from the company's competitive edge and the need to protect its intellectual property.

Competitive Edge and Intellectual Property

As a subsidiary of Alphabet Inc., Google’s overarching parent company, Google DeepMind has an obligation to protect its proprietary technology and maintain a competitive advantage. Publishing source code would mean making their algorithms, techniques, and strategies publicly available, which could potentially lead to imitation or reverse engineering by competitors. This, in turn, could undermine the very foundation upon which DeepMind built its success.

Core Competition Considerations

Many speculate that DeepMind also views the source code as a part of its core intellectual property (IP). In the world of AI, algorithms are not just tools but are the heart and soul of the technology. For an AI company, the source code represents a precious asset that contributes to its innovation and research capabilities. It is similar to how a cookbook is a vital asset for a chef; removing this asset could severely limit further advancements by competitors.

Alternatives to Open Sourcing

Despite the challenges, there are alternatives to open sourcing code that can still foster collaboration and innovation without the risk of losing competitive advantage. One such approach is to release a simplified version of the code that includes enough details to understand the main logic but excludes critical aspects that would enable full replication of the AI system. This middle ground can help in advancing the field while preserving proprietary elements.

Collaborative Research and Academic Engagement

Another strategy is to engage in collaborative research through partnerships and academic collaborations. By working closely with universities and research institutions, DeepMind can disseminate knowledge and foster innovation without releasing the full source code. This approach has been successfully adopted by companies like IBM in the field of AI.

Community Contributions and Improvements

By focusing on community contributions and improvements, Google DeepMind can leverage the collective intelligence of the AI research community. Making the source code partially open or providing a platform for researchers to build upon existing works can lead to valuable enhancements and new discoveries, while still maintaining some level of proprietary control.

Conclusion

The decision by Google DeepMind to not publish the source code for AlphaGo Zero and AlphaZero is a complex one that reflects the company's strategic goals and competitive edge. While this choice may provoke dissatisfaction among some researchers and enthusiasts, it also fosters an environment where DeepMind can continue to innovate and lead the field of artificial intelligence. The key takeaway is that the battle for intellectual property and competitive advantage is ongoing, and the strategies employed by tech giants like Google can significantly influence the trajectory of technological advancements.

Keywords:

AlphaGo Zero AlphaZero DeepMind Open Source