Bricks and Mortar:
Strategic Positioning of a Long-Term, Human-Level AI Project
Bricks and Mortar
Précis
- Any 10 year project needs to have a robust strategy for dealing with change during its lifetime
- This is particularly true for a human-level AI project, as all key aspects of the field are changing dramatically
- To date, all previous AI projects have been narrowly-focused and highly specialized: designed to achieve one goal (diagnose a disease, play chess, decide when to sell a stock, etc.)
- Any human-level AI project, by contrast, will be orders of magnitude more complex, integrating sub-systems that will need to work together to achieve many sub-goals simultaneously, so…
- Any human-level AI project will end up being a cooperative affair, involving many manufacturers/labs producing many specialist components. It is useful to think of these components as bricks, and the larger project as an edifice to be built
- This heterogeneous nature will lead to novel constructs not seen in previous AI projects. Most notably, a human-level AI project will be a distributed system, not a monolithic program. Some data and third-party AI sub-systems will be called as services, not bolt-on components
- To carry the “bricks” metaphor to its logical conclusion, a kind of highly dynamic “mortar” will also be required to bind any human-level AI project together: a mechanism that will allow the bricks to discover one another; to coordinate and sequence their activities; to recover gracefully when a component fails, gets upgraded or goes off-line; to communicate with outside sensors, AI services and data
- The best business strategy involves developing the mortar, not the bricks