Machine Learning – Horizontal vs. Vertical Platforms

Cleantech Forum – Insightful Answers to Insightful QuestionsCategory: artificial intelligenceMachine Learning – Horizontal vs. Vertical Platforms
proton Staff asked 4 months ago

Horizontal or Vertical machine learning platform? Which one is better and where should you invest time and money?

1 Answers
proton Staff answered 4 months ago

Machine Learning - From Fundamental Capabilities to Features to Solutions


Machine Learning use cases in Energy



Machine Learning use cases in Industry



A few points to consider:

  • The Big Data analytics space is noisy. Artificial Neural Networks, Machine Learning, Deep Learning, Artificial Intelligence, etc., terms are being used loosely/interchangeably. Research is headed towards building a system with human brain like capabilities but most businesses do not need such capabilities right away to extract value out of their data.

  • You only need 2 data points to describe a line. You can store a million data points about the line and use excessive compute power to find the slope because memory and compute are cheap. But you only need 2 data points. Machine Learning is a means to an end goal of solving business problems. Enterprise customers should spend time on asking the right questions and prioritize those that have business value. Enterprises should avoid wasting time and effort on combining data sets and implementing a big data project merely for the sake of it.

  • There are 3 main stages in any Data Science project. Data Preparation (includes Collection, Integration, & Preparation), Model Building (includes Visualization and other data exploration and analysis tools), and Model Deployment.

  • Data is the most valuable asset and is the only sustainable competitive advantage. Models are not useful if not tested on real enterprise data. The second most valuable asset is the talent to use this data.

Another question frequently encountered by enterprises thinking about using ML technologies: Should we buy horizontal technology platforms or should we buy a product/application that solves pain points in my industry (and related industries)?

To answer this question we should look at ML/AI market maturity and how sophisticated the buyer is (do they have a solid data science team, have they executed big data projects previously and so on....)





To simplify the challenge, let's take a look at Solar module value chain: