Why is machine learning [ML] important for your business? If you work at Nokia, your Chairman can explain it to you in a one hour presentation he developed over six months of research. Risto Siilasmaa helped make his network smarter. Everyone needs to know if ML can help with their business problems, but first they have to understand the basics, says Siilasmaa.
- Digitization has created an explosion of information
- ML is based on models like logistic regression, which can be fairly easy to understand
- ML is fitting the model to the data
- ML is neural networks learning from data sets
- The more high quality data, and computing power, the fewer mistakes ML will make
- In a large neural network you can have 100 million parameters in a single layer
- Flawed outputs can happen if human oversight confirms incorrect ML conclusions (human oversight becomes very important)
- A neural network first learns from a data set (time consuming) and then can be tested against other data sets
- The important work is done by systems of ML systems
- Machines are still getting faster and more tools are being developed
- The data we are helping create (e.g. through use of speech recognition) is feeding AI corporations
- ML can be tricked if you know the underlying algorithms
- Remember: Garbage-in, Garbage-out
- Big question: What data will we need in the future to make better decisions?
- Business and human work is moving to — Low Predictability + High Complexity
- ML can help to experiment faster and better in order to deal with Low Predictability + High Complexity
- The future of work: First experiment … then develop a strategy