Home Latest Insights | News Three Types of Machine Learning and AI companies that exist today

Three Types of Machine Learning and AI companies that exist today

Three Types of Machine Learning and AI companies that exist today

According to Auren Hoffman, SafeGraph CEO, on Quora, there are three different types of Machine Learning and Artificial Intelligence companies: The Superrich, the Servicers, and the Innovators.

  1. Superrich: Companies that do machine learning AND have their own data.
  2. Servicers: Companies that do machine learning on other people’s data.
  3. Innovators: Companies that do machine learning and have to get access to data.

All three of these type of companies can be massively successful and each one has a distinct flavor.

The Superrich are companies like Google, Facebook, Baidu, Tencent, Amazon, Microsoft, and others. There are very few of these companies in the world but they have a massive advantage over everyone else in the machine learning space because they have access to vast amounts of clean, structured data. Engineers that do machine learning can do what they do best … predict the future.

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The Servicers help other firms make use of large amounts of data. These companies comb through data (sometimes unstructured) and develop insights. These companies are essentially service firms because they work directly with the data of their customers. One of the most successful Servicers is Palantir Technologies which made a name of itself helping government organizations make sense of the data. Salesforce.com also is creating initiatives to do this. Many other companies fit into this mold (for instance, a company that helps airlines optimize its pricing). And any consultancy fits in this category too.

The Innovators — are companies that are working on a specific problem but don’t have access to their own data and are not service-oriented companies that help others. These are companies that want to use data to cure cancer, creating self-driving car technology, and predicting the stock market (like hedge funds). Some of these firms, like Two Sigma Investments and Point72 Asset Management, spend hundreds of millions of dollars on data because unlike the Superrich, they do not generate tons of data themselves. Other good example of Innovators are Cruise Automation (self-driving cars and recently acquired by GM) and Flatiron Health (cancer research). Flatiron Health felt it had to acquire a software services company, Altos Solutions, to get access to raw data. Of course, once these Innovators get the data, they still need to stand it up, clean it, merge it, join it, and do a bunch of ETL.

Summation: As access to data becomes more democratized, we will see more and more Innovators starting and being successful. Today, the Superrich have a big advantage but we should see more Innovators that are focused on a specific solution winning in the future.


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