In 2018, a total of 466 AI companies raised $9.3B in funding, up from $5.4B in 2017, an increase of 72%, according to a PWC Moneytree report.
The AI industry is evolving rapidly and it’s much bigger than any single player or technology including Google TensorFlow. As the number of AI startups entering the industry surges, the technology they’re bringing to market is maturing. The focus nowadays is to simplify the process of building and incorporating ML models into existing technology stacks. Startups like DataRobot and H2O.ai have created platforms that abstract away the complexity of building, deploying, and running ML programs.
A new category in the field of AI has emerged called Automated Machine Learning (AutoML). The AutoML tools simplify and automate the process of working with datasets, processing datasets, figuring out which algorithms and model works best, training models, and much more. DataRobot has made it easy to work with its platform. All users need to do is provide a dataset, even a low quality one, and they’ll take care of the rest. It’s a little more complicated than that, but that’s the aim which is likely to be achieved sometime in the future.
Today, DataRobot and H2O.ai work extensively with the data science community. However, we all know that the road to riches is in serving the non-data scientist, or what the industry calls the citizen data scientist. DataRobot has been the more aggressive startup, in that they have acquired several startups, including a competitor, a highly specialized startup, and a couple of others.
- ParallelM: Created MLOps category. Helped companies scale and deploy ML models on Kubernetes, Spark, public and private cloud.
- Cursor: Developed a data collaboration platform and catalog that helps companies find and make better use of their data.
- Nexosis: Automated machine learning platform. A competitor to DataRobot.
- Nutonian: Developed an engine for time series analytical modeling that powers predictive analytics at major companies like Audi and NASA.
In regards to the CDN industry, we expect some vendors to start working with AI in 2020, to help modernize their global technology stacks, beyond cloud security.