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What's the difference between artificial intelligence and machine learning in LogTech?

Artificial intelligence (AI) and machine learning are both technical buzz words in LogTech. Both of these terms are technologies that are used to make systems smarter. Although many people think they are interchangeable, this is not the case.


Let's discuss what these terms are, their differences, and how it ties into technology in the logistics industry.



What is artificial intelligence (AI)?

Artificial intelligence technology mimics human intelligence. In other words, it makes a computer think in the way a human might and is used to make systems life-like.


Commonly recognized forms of AI include:

  • Self-driving cars and trucks

  • Facial recognition systems that unlock tablets and smartphones



What is machine learning (ML)?

Machine learning is a subset of artificial intelligence. In machine learning, machines learn from data inputs and make certain decisions without being explicitly programmed.


Machine learning is a self-learning process where the machine needs to be trained through different data sets and models. As a result, machines can then make accurate decisions and learn from experience using the stored data.


A common example of machine learning is a product recommendation system for an online retailer. Retailers gather data on purchase behavior, search history, and product information. The system then learns and makes recommendations to individual shoppers after synthesizing the data.



What are the differences between artificial intelligence and machine learning?

Some of the primary differences of these technologies are specified below.


Goal

The purpose of AI is to build more intelligent systems that can solve numerous complex problems. Because of this, it is meant to solve problems more quickly and efficiently than a human could.


As a subset of AI, ML allows machines to solve specific tasks related to data sets. Furthermore, it increases the accuracy of the results by making data-driven predictions. Also, ML identifies patterns in the data.

Behavior

AI mimics human intelligence, however, ML does not mimic human intelligence. ML relies on the data that is inputted into the system.

Practicality

Artificial systems are difficult to make. Comparatively, training a machine is less complex. Think about it this way: Teaching a machine is more achievable than creating an artificial human mind.

Reasoning

AI involves explicit reasoning. Meanwhile, ML does not involve any reasoning.



Machine learning and artificial intelligence in LogTech

What are ways we are seeing AI or machine learning in the logistics industry?


Autonomous trucks and vehicles are a major trend in AI technology. As technology and regulation improve, we can expect to see this come to reality, possibly in the next five to 10 years. We especially expect to see this in the middle mile.


Truckload procurement technologies like FreightFriend use machine learning to provide recommendations to shippers, brokers, and asset carriers. For example, FreightFriend uses machine learning to provide better ranked freight matches to its users. The software combines data like load history, posted trucks, and carrier behavior and feedback. The data helps reveal carrier preferences and drive their engagement.


Schedule a demo to learn more about how FreightFriend uses machine learning to offer the most sophisticated freight matching and dynamic routing engine on the market today.


* "Versus" icon in image made by Good Ware.