Technology

The Difference Between AI and Machine Learning, According to ClearObject

As data increases and advances in specialized chip design make computing more efficient, artificial intelligence (AI) and machine learning are becoming more accessible and advancing tremendously as a result. Industry-leading cloud companies like Google, Amazon, and Microsoft can now deliver this technology to startups and companies from a variety of industries, making it easier to leverage data into innovative AI and machine learning solutions. 

While the terms “AI” and “machine learning” are often used interchangeably, they actually have different technical definitions. Here’s a look at what precisely artificial intelligence and machine learning are.

What is Artificial Intelligence?

Artificial intelligence (AI) is the broader of the two categories, and its name captures the goal of this field. AI encompasses the concept that computers (or machines) could imitate human abilities, especially human intellectual abilities. Just as people effortlessly evaluate their environment and past experiences to make informed decisions, so too can AI-empowered computers.

Artificial intelligence as we know it in the real world is known as Artificial Narrow Intelligence (ANI). ANI enables computers to perform specific tasks that a computer is programmed to do. This is the only form of AI that’s actually been achieved in the real world thus far. The other forms (Artificial General Intelligence and Artificial Superintelligence) are still theoretical or found only in science fiction.

ClearObject offers a variety of advanced technology services, including AI and IoT integration. Other examples of ANI include self-driving cars, smartphones’ digital assistants, and facial recognition technology.

What is Machine Learning?

Machine Learning (ML) is a subset of artificial intelligence, referring to the processes by which computers (or machines) learn from past outcomes. On a broad level, AI can be thought of as computers mimicking human behavior and ML can be thought of as computers learning from data.

ML uses various models to analyze data, looking for patterns that create meaningful insights. There are four distinct types of ML:

  • Supervised Learning: Algorithms check large amounts of labeled data for pre-defined correlations.
  • Unsupervised Learning: Algorithms check unlabeled data for patterns and correlations without a specific end goal.
  • Semi-Supervised Learning: Algorithms check mostly labeled data, but they’re able to explore their own understanding of the data.
  • Reinforcement Learning: Algorithms complete multi-step processes with defined rules, and make their own decisions throughout the processes.

Some of the services that ClearObject offers fall under machine learning.

AI and ML Have Important Roles

Both artificial intelligence and machine learning have important roles to play now and in the future. Both types of computer-run operations will also become more advanced as they’re developed further.

About ClearObject

ClearObject specializes in AI and ML solutions for the automotive and engineering sectors. The Midwestern company has clients around the world in these industries. Follow ClearObject on Facebook and Twitter to learn more.

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