What's the Difference Between AI and ML?

Gigster
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September 21, 2023
Machine Learning vs. AI: What's the Difference

Artificial intelligence (AI) and machine learning (ML) are two of today's most talked-about technologies. But what are they, and what are the key differences between them?

AI refers to machines' ability to perform tasks typically associated with human intelligence, such as learning, reasoning, and problem-solving.

ML is a subset of AI that allows machines to learn from data without being explicitly programmed. Both AI and ML are powerful technologies that have the potential to revolutionize many industries. However, they are also different in important ways.

This blog will discuss the differences between AI and ML to help you understand these distinctions to better navigate the tech landscape and harness their unique benefits for innovation, efficiency, and growth.

What is Artificial Intelligence?

AI is a broader concept than ML in that AI encompasses the spectrum of intelligent machines capable of mimicking human cognitive functions.

The objective of any AI-driven tool is to perform tasks that typically require human intelligence. AI should be able to recognize patterns and make choices and judgments. It aims to develop systems capable of replicating human cognitive abilities in order to improve efficiency, accuracy, and automation across various industries and applications.


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Ultimately, AI aims to enhance human capabilities, simplify complex processes, and drive innovation in fields like healthcare, finance, transportation, and more.

Artificial Intelligence vs Machine Learning

Artificial intelligence (AI) and machine learning (ML) are closely related, but there are key differences.

AI refers to machines' ability to perform tasks typically associated with human intelligence, such as learning, reasoning, and problem-solving.

ML is a subset of AI that allows machines to learn from data without being explicitly programmed.

Read More: How AI Shapes the Future of Critical Thinking

Knowing the differences between AI and ML is foundational for effective decision-making, resource management, problem-solving, and responsible technology deployment. A few key differences are outlined in the table below:

AI vs. ML

The Difference Between AI and Machine Learning

The Relationship Between Machine Learning and Artificial Intelligence

Think about it like this: modern-day computer systems leverage AI to not only be able to process information and "think" like a human being but to execute tasks like a human would, too. Machine learning is how that intelligence continues to expand and evolve over time as it is presented with new information.

Machine learning systems, therefore, become a way to not only "train" an AI-driven platform but to ultimately enhance the capabilities of that tool as well.

Read More: Machine Learning Process: A Complete Guide

Real-World Examples of ML and AI

Blockchain can increase transparency, decrease fraud, and lower costs in finance. Below are a few ways that blockchain can offer several benefits in this industry:

Business Automation

AI can be used to analyze the types of large data sets humans would be incapable of. They could pour over years or even decades of sales information to anticipate future trends that a human might miss. They can look at real consumer behavior to more accurately segment audiences, making it easier to successfully up-sell and cross-sell based on what a person has already shown interest in.

Analytical AI tools can look at real-time performance information to make recommendations about how workers and other resources should be allocated to improve collaboration and productivity. Rather than having it take months or even weeks for a human to arrive at similar conclusions, AI can get there in a fraction of the time.

With machine learning, these tools can get more effective the more they're used - all while freeing up the valuable time of human workers to focus on more important matters.

Read More: Integrate AI: How Your Business Can Stay Ahead of the Curve

The Supply Chain

Both artificial intelligence and machine learning can help keep global supply chain networks functioning, even as they grow more complex, with more vendors all the time. Right now, these technologies are employed to do everything from tracking shipments to anticipating delays to problem-solving in real-time, all to avoid the disruption that could cost countless organizations money.

Healthcare-Driven Applications

Artificial intelligence and machine learning are being used to process patient records and medical tests and are the backbone of wearable devices like smartwatches. They're making it easier for humans to diagnose and treat even complex conditions daily, putting access to potentially life-saving care into the hands of people worldwide.

Read More: Machine Learning Integration: A Guide for Business Leaders

AI and ML Gigster Use Cases

eBay

Gigster built an AI model and application that leveraged Computer Vision to classify content with 98.9% accuracy in detecting problems in content and an 80% reduction in time in manual monitoring.

Canon

Gigster implemented an ML-based Photo Community powered by Google’s Computer Vision Engine to enhance the customer experience.

Liberty Mutual

Using drones and ML algorithms to automate the roof damage claims process, Gigster increased the safety of adjusters while saving time and costs by using AI/ML.

Read More: Explore additional client success stories, testimonials, and our tailored services to discover how Gigster can transform your business with innovative solutions.

Benefits of AI and Machine Learning

AI and ML lead to personalized consumer services and reduced business operational costs. Both of these concepts ultimately improve the experience for all involved and provide benefits across various industries. Below are just a few key advantages:

  • Automation and Efficiency
  • Improved Decision-Making
  • Personalization
  • Scalability and Adaptability
  • Data Analysis and Insights
  • Predictive Analytics and Forecasting

Think about your recent online shopping experience. Did you notice the site suggesting similar items they might like? This AI is designed to make your shopping experience more personal and increase the chances of you buying more. The best part is this all happens automatically, without any need for employees to get involved.

The Future of AI and ML

In terms of the future, it's been estimated [1] that the worldwide market for AI will grow from the $136.6 billion value it had in 2022 to an enormous $1.8 trillion by the end of the decade. Everyone is doubling down on both artificial intelligence and machine learning and make no mistake - those that don't will quickly find themselves left behind.

In the End

At Gigster, we can help your business in a variety of different ways by offering both artificial intelligence and machine learning services designed to fit your every need. Through our AI development services, you can speed up your workflows and get more value out of your data by automating as many administrative tasks in particular as possible. Contact the team at Gigster today to find out more information.

Resources:


[1] Grand View Research (2022). Artificial Intelligence Market Size, Share | AI Industry Report, 2025. [online] Grand View Research. Available at: https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-ai-market.

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