As for (2), there is likely to be high efficiency in a market between cloud based algorithms and algorithms implemented offline due to extreme low barriers to entry. Basically those first person in with a good method of translating those algorithms offline, surmounting potential legal hazards, and scaling up (no trivial tasks) will make a quick buck. Though, these are problems that I can define. If I can define them, the big names probably already have and are working on solutions for them. You're out of luck, garage entrepreneurs.

People are snapping up data scientists in preparation for the move from Data science as a product to data science as a commodity. Historically, big companies have been awful at making this transition, but once they realize their mistake, eager to make up lost time.. An entrepreneur who looks to be bought up buy one of these market laggards could to really well.

Elon Musk cites first principle thinking in physics as a key to identifying neglected market opportunities. Can someone give me an example of how it may work in that application?

The classic Musk example is taking the cost of raw materials to make a spaceship - he saw that they were many orders of magnitude the actual cost of a spaceship, so he figured there were probably efficiency problems that people simply hadn't solved.