Explore how AI companies compete and where they can build a lasting advantage.
About This Course
Introduction
A model lab buys compute from a cloud provider that may sell its own model. An app uses a model service while competing with that provider's app. A chip designer depends on manufacturers and memory suppliers while building a software ecosystem of its own. Partners can also be competitors, which makes the relationships worth examining carefully.
We will map roles, dependencies, bargaining power, differentiation, vertical integration, and commoditization. Your project is a market map and an analysis of where a fictional company might sustain value. Revisit the full system, especially Modules 5, 10, 18, 25, and 28.
Planned Lessons
Industry Roles And Value ChainsMap the different businesses involved in creating and delivering AI.
Semiconductor And Infrastructure PositionsIdentify what can make a chip or computing-infrastructure business competitive.
Hyperscalers And Custom SiliconExplore why large cloud providers design their own chips and how that affects suppliers.
Model Labs And Open-Model EcosystemsCompare businesses developing models with communities sharing downloadable models.
Applications And ComplementsSee how useful applications and supporting services create businesses around AI models.
Bargaining Power And AlternativesCompare the alternatives that give buyers and suppliers more negotiating power.
Switching Costs And Lock-InIdentify the time, work and expense involved in changing AI providers.
Proprietary Data And Feedback LoopsExplore when exclusive information and customer feedback help a business improve its position.
Vertical Integration And PartnershipsCompare doing more work within one company with relying on partnerships.
Commoditization And Value CaptureConsider where companies can earn profits as AI capabilities become more widely available.