Open Source in the Age of Cloud AI
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The document discusses the evolution of open source in the context of cloud AI and the changing dynamics of technology companies. It highlights the importance of collaborative development and the philosophy of openness among developers, while cautioning against the shift to zero-sum relationships in profit extraction. Finally, it emphasizes the potential of AI and computational sustainability in creating inclusive and sustainable economies.
Open Source in the Age of Cloud AI
- 1. Open Source in the Age of Cloud AI Tim O’Reilly @timoreilly oreilly.com wtfeconomy.com OSCON July 18, 2018
- 2. My love affair with open source Photo: Esther Dyson
- 3. Losing the way of life, Men rely on goodness. Losing goodness, They rely on laws.
- 4. Generosity
- 5. The Robustness Principle “TCP implementations should follow a general principle of robustness: be conservative in what you do, be liberal in what you accept from others.” Jon Postel, RFC 761 Photo: John Postel in his office, by Carl Malamud
- 6. This goodness flourished in despite of bad licenses (laws) Despite having a proprietary license, and being owned by one company, Unix was developed collaboratively by small teams of independent developers.
- 7. An architecture of participation “The book is perhaps most valuable for its exposition of the Unix philosophy of small cooperating tools with standardized inputs and outputs, a philosophy that also shaped the end-to-end philosophy of the Internet. It is this philosophy, and the architecture based on it, that has allowed open source projects to be assembled into larger systems such as Linux, without explicit coordination between developers.”
- 8. “I couldn’t have built a new kernel for Windows even if I had access to the source code. The architecture just didn’t support it.” Linus Torvalds
- 9. Open source methodologies “won” because they were better adapted to the emerging world of network, protocol-oriented architectures, decentralized software development, and networked software distribution. They were aligned with “the way of life.”
- 11. "The Law of Conservation of Attractive Profits" "When attractive profits disappear at one stage in the value chain because a product becomes modular and commoditized, the opportunity to earn attractive profits with proprietary products will usually emerge at an adjacent stage." -- Clayton Christensen Author of The Innovator's Solution In Harvard Business Review, February 2004
- 12. Breaking Bad “When they hit the top of the S-curve, their relationships with network participants change from positive-sum to zero-sum. The easiest way to continue growing lies in extracting data from users and competing with complements over audiences and profits. Historical examples of this are Microsoft vs Netscape, Google vs Yelp, Facebook vs Zynga, and Twitter vs its 3rd-party clients. Operating systems like iOS and Android have behaved better, although still take a healthy 30% tax, reject apps for seemingly arbitrary reasons, and subsume the functionality of 3rd-party apps at will.” - Chris Dixon, “Why Decentralization Matters”
- 14. Science
- 15. Curiosity, continuous learning by doing Photo by David Fulmer
- 18. Market Design Markets are outcomes. The algorithms decide “who gets what – and why” A better designed marketplace can have better outcomes.
- 20. Generosity turns out to be a robust strategy
- 21. Google forgot that its strength was in the rich ecosystem of the open web, and began to compete with it, on the theory that only benefit to users matters. Conveniently, this also increases Google profits. Amazon too increasingly competes with its supplier ecosystem.
- 22. This looks like a replay of what Microsoft did to the PC
- 23. Divergence of productivity and real median family income in the US
- 24. The same dynamics play out at the national level Inclusive economies prosper. Extractive economies falter. Why do we incentivize extractive behavior?
- 25. What is “the way of life” for networked platforms and economies? “The opportunity for AI is to help humans model and manage complex interacting systems.” Paul R. Cohen
- 26. “Computational Sustainability is a new interdisciplinary research field, with the overarching goal of studying and providing solutions to computational problems for balancing environmental, economic, and societal needs for a sustainable future…. Work in Computational Sustainability integrates in a unique way various areas within computer science and applied mathematics, such as constraint reasoning, optimization, machine learning, and dynamical systems.”Carla Gomes
- 27. The master algorithm asks for growth to go on forever It should be doing a better job of solving for
- 29. “If you want to teach people a new way of thinking, don't bother trying to teach them. Instead, give them a tool, the use of which will lead to new ways of thinking.” Buckminster Fuller