Predictive Analytics, Applied Statistics, Machine Learning, Probabilistic or Stochastic Computing
Just two main components – statistics combined with innovative algorithms that use traditional programming constructs and additional advanced math such linear algebra and calculus.
So you start with a need, an application, the time tested business requirement of staying ahead of the curve and use the best available paradigms using the tools above.
Call it machines learning or not having explicitly programming the computations or artificially created intelligence to rival natural or scientifically exploring data, but it is important to understand what is happening under the hoods and whether there a pattern among the widely disparate methods and techniques.
Supervised, Unsupervised, Reinforcement, Representational or all Deep Learning is basically algorithms built on advanced path and made practical by advanced computing.
Now, you look at any application – Classification, Estimation, Recommendation, Anomaly Detection, Sentiment or Style Analysis- you can break them down in terms of what has been said above. Either there were needs or challenges which were intractable that led to development of methods and techniques and then the same were creatively applied in other scenarios.
Doesn’t say much about anything Artificial. Just that there is no limit to the Natural Human Faculties, Intelligence is just one of them.
That also makes me think that there are few separate components
- Advanced Math
- Programming and Technology – data structures, control structures combined with big data, cloud services and other technologies
- Creativity and Ingenuity to adapt solutions to new scenarios or tweaking solutions to create new applications
A practitioner would understand some or more of each of the above but your interest, current skills and /or circumstances may dictate where you are and would be for near future but if you look at benchmarking along these lines, you may chalk out your future path in a more controlled and hopefully, fruitful way.