If you’ve been keeping an eye on the tech landscape, you might be familiar with all tech giants rolling out opensource AI models, one after the another. What they are doing here is essentially commoditize your complement”. But what does it really mean?
Imagine you’re selling razors. The razors are your main product, but the blades are the complements. If you can make those blades affordable and widely available, guess what? More people will buy your razors. Simple, right? Now, translate that to the tech world. Here, the “razor” is your core product—say, a proprietary AI platform—and the “blades” are the tools, models, or data that enhance its value. By making these complements cheap or even free, companies can drive demand for their primary offerings and lock users into their ecosystem.
Think of the AI ecosystem as a layered cake:
- Hardware: GPUs, TPUs, and other specialized chips.
- Infrastructure: Cloud platforms like AWS, Google Cloud, and Azure.
- Models: Open-source and proprietary AI models (e.g., GPT, BERT, LLaMA).
- Applications: End-user tools like chatbots, image generators, and coding assistants.
Each layer supports and enhances the others. Powerful hardware makes training models easier, better models make applications more useful, and so on. Companies are strategically commoditizing certain layers to strengthen their dominance in others.
Google: Open-Sourcing Models to Drive Cloud Adoption
Google brought us groundbreaking models like BERT and Transformer. By open-sourcing these models, Google has effectively commoditized the AI model layer.
Think of Google as a car manufacturer that gives away free engines. More people build cars using those engines, and naturally, they’ll buy other layers (like tires and batteries) from Google.
Open source is the unsung hero in the commoditization game. By making software or models freely available, companies can:
- Lower Entry Barriers: Developers can easily start building without hefty upfront costs.
- Ecosystem Growth: A vibrant community forms around the core products, fostering innovation and collaboration.
- Industry Standards: Open-source offerings often become the de facto standards, ensuring widespread adoption.
Take Google’s TensorFlow, for example. It’s become an industry standard, ensuring that developers are more inclined to use Google Cloud's Vertex platform for their AI projects.
Open-source software models are like free recipes— the more people use them, the more they’ll buy the ingredients (cloud services, hardware) from the same store.
While commoditizing complements is a powerful strategy, it’s not without its pitfalls:
- Over-Commoditization: If the complement becomes too cheap or ubiquitous, it might devalue the core product.
- Intense Competition: Other companies can also commoditize their complements, sparking a race to the bottom.
- Ecosystem Dependence: Relying heavily on open-source models can make a company vulnerable to shifts in the ecosystem.
As AI continues to evolve, more companies are likely to adopt this strategy. Emerging trends to watch include:
- Specialized Models: Commoditizing general-purpose models while keeping specialized ones proprietary.
- Data as a Complement: High-quality datasets becoming the next layer to be commoditized.
- Edge AI: Hardware manufacturers commoditizing software to sell more chips as AI moves to edge devices.
Commoditizing the complement has been a game-changer for the tech industry for decades.
Be it IBM standardizing hardware components to create a reliable foundation for diverse software applications, Red Hat transforming open-source software into enterprise-ready solutions with predictable support and services, or Acquia streamlining Drupal hosting to provide scalable and secure environments for web applications, these companies have exemplified the power of commoditizing complementary products and services.
So next time you see a for-profit corporation announcing an open-source initiative, don’t assume it is just a charitable contribution—it is a strategic move to commoditize complementary products, enhance their ecosystem, and drive long-term growth.