I was keen to delve into the specifics- we need to know the core of the companies before we can diss their efforts elsewhere; like healthcare.
When you have a hammer, everything looks like a nail. Here, the hammer is the machine learning and the moniker of artificial intelligence.
Are the biggest big tech companies monetizing their big datasets? I think the answer in 2020 is ‘sort of’, and doesn’t involve advanced statistics.
At amazon, even really good product recommendations aren’t (I suspect) driving sales growth more than fast shipping.
For FB & G, my ML questions are:
Does ML improve the quality of their core offering (search for G, feed for FB)
Does it improve the performance of ads? (for any stakeholder)
Does it enable development of new things that diversify their product offering
For me, the answers are no, maybe, and no. G search has gotten worse as they’ve focused on recency in the index, gotten more tolerant of synonyms, and gotten less strict about quoted phrases. And no, they haven’t diversified – their core revenue stream is still ads and in G’s case that income may be drying up.
My contention is that the big ticket acquisitions don’t matter- it is the smaller technology companies that are drying up. The cost of “start up” is almost nil, assuming you have the “talent, ideas and compunction” as one package with a generous help from the backers. However, that alignment only works for the lucky folks. The real cost of the company is in “customer-acquisition”, onboarding and keeping the ship steady.
Machine learning will only get you so far.
Google is “betting” on the next wave of OCR’d textbooks to provide “instant answers”. That’s stealing by any other name.