According to Mattermark, No.
This editorial presents an interesting look at the ecosystem of machine learning startups, across all industries. Some choice quotes:
2013’s Big Data is 2016’s Machine Learning (ML) and Artificial Intelligence (AI).
AI and ML are the latest buzzwords, but unlike most corporate cliches, there’s a robust market for AI tech–both in the form of internal R&D and big corporate interest–in the realm of startup work and venture funding.
Mattermark notes on a few significant exits that have happened recently, including DeepMind (Google) and Turi (Apple). Thus far most exits have been of companies that focus on the core technology. I think machine learning companies are going to continue to get acquired, and going forward it will be more-focused companies within specific verticals. This could be GE acquiring industrial-focused companies or Pfizer acquiring a company working with genetic data to predict new drugs.
One of the big differentiators between machine learning and previous technology fads is that there are actual, value-adding, results in the work being done. Mattermark address this as such
We spoke with Matt Ocko, cofounder and co-Managing Partner of [VC firm Data Collective] ... “We think there is both technology push and market pull,” Ocko suggested. The presence of both forces is rare in emerging technologies and creates significant demand.
Ocko explained that Data Collective “[likes] companies that substitute compute for capex and opex, both in their own operations (longer run-way, higher margins) and in how their product is transformative for customers’ business.”
Machine learning is already generating results for companies throughout the economy and will continue to do so.