The AI Investor: Understanding Machine Learning

The rise of Artificial Intelligence (AI) is a trend that will have significant implications for your portfolio. Machine Learning (ML) is ground zero for unleashing the potential of AI for businesses, governments, and consumers.

Industries and Institutions vary, but the fundamentals stay the same. We’ll look to the Joint Artificial Intelligence Center (JAIC) publication, “ Understanding AI Technology “ by Greg Allen to get a better understanding of Machine Learning.

“AI is not an elixir. It is an enabler.” Lt Gen John N.T. “Jack” Shanahan.

BASICS

Investors need to understand: What is AI? How does it work? What are the types of Machine Learning, and how do they differ? What are the risks and limitations of AI?

MACHINE LEARNING

Artificial Intelligence is an umbrella term covering a broad swath of technology. When people say “they’re using AI” at work, they usually mean systems that use Machine Learning to automate processes. ML is a few years away from being an autonomous Intelligent machine able to make decisions on its own.

The important point is, while machine learning systems program themselves, human intervention is critical to the learning process. This human intervention includes choosing data and algorithms, setting the learning parameters, and troubleshooting problems.

WHY IS ML IMPORTANT?

The big reason? ML lends itself to automation tasks too complex for human programmers. The number of rules required is impractical, if not impossible, to accomplish with a human coder. ML is well suited for content generation, language translations, pattern recognition, and speech transcription.

WHY NOW?

There are multiple reasons the pause in the Fourth Industrial Revolution is now accelerating. I’ll highlight two of the big ones:

TYPES OF MACHINE LEARNING CONCLUSION

As Greg Allen states in the Guide, organizations should not pursue AI and ML for its own sake. Allen recommends identifying specific metrics for performance and productivity. Adopting AI will require some changes to existing business processes. If companies don’t make those changes, most AI projects will deliver a fraction of the value sought.

Originally published at https://theaiinvestor.substack.com.