Machine Learning and the Physical World

Neil D. Lawrence

Data Centric Engineering

Emergent Behaviour

Loneliness
loneliness

Crowding
overcrowding

Birth
birth

Glider

Glider (1969)

Loafer

Loafer (2013)

Figure: Science on Holborn Viaduct, cradling the Centrifugal Governor.

On Governors, James Clerk Maxwell 1868

The Gap

  • There is a gap between the world of data science and AI.
  • The mapping of the virtual onto the physical world.
  • E.g. Causal understanding.

Prime Air

Gur Kimchi Paul Viola David Moro

Buying System

Monolithic System

Service Oriented Architecture

Intellectual Debt

Technical Debt

  • Compare with technical debt.
  • Highlighted by Sculley et al. (2015).

Separation of Concerns

Intellectual Debt

  • Technical debt is the inability to maintain your complex software system.

  • Intellectual debt is the inability to explain your software system.

Statistical Emulation

Emulation

Emulation

Emulation

Emulation

Emulation

Auto AI

  • Auto ML is great but not sufficient
  • Interacting components in an ML system
  • Identify problems, and automatically deploy solutions

Deep Emulation

Deep Emulation

Deep Emulation

Deep Emulation

The Accelerate Programme

  • Research
  • Teaching and learning
    • Ramp or Bridge model
  • Engagement

ML and the Physical World Course

Thanks!

References

Sculley, D., Holt, G., Golovin, D., Davydov, E., Phillips, T., Ebner, D., Chaudhary, V., Young, M., Crespo, J.-F., Dennison, D., 2015. Hidden technical debt in machine learning systems, in: Cortes, C., Lawrence, N.D., Lee, D.D., Sugiyama, M., Garnett, R. (Eds.), Advances in Neural Information Processing Systems 28. Curran Associates, Inc., pp. 2503–2511.