What is the difference between AI and ML?
AI vs ML simplified, AI side by side comparison and Ohio AI Forum
AI vs MS
Let's simplify the difference between Artificial Intelligence (AI) and Machine Learning (ML).
Analogy:
Think of AI as a big umbrella that covers all the ways we can make machines act intelligently. Machine Learning is one specific approach under that umbrella.
AI: Like teaching a robot to act like a human. You could program it with specific rules or use various techniques to make it intelligent.
ML: Like showing the robot many examples of what to do, and letting it figure out the rules on its own.
Artificial Intelligence (AI): This is a broad concept that refers to machines or software mimicking human-like intelligence. It's about creating algorithms that allow computers to perform tasks that typically require human intelligence, such as understanding speech, recognizing images, or making decisions. AI can include anything from simple rule-based systems to highly complex algorithms.
Machine Learning (ML): This is a subset of AI. It's a specific way of achieving AI by allowing the system to learn from data. Instead of programming specific rules to make decisions, you feed the machine lots of examples (data), and it learns the patterns from that data. Once it's learned these patterns, it can make predictions or decisions without being explicitly programmed to do so.
All Machine Learning is AI, but not all AI uses Machine Learning. ML is a specific technique within the broader field of AI that focuses on learning from data. They are sometimes used as synonyms and easy to get mixed up.
Here are a few common ways you encounter AI and ML in everyday life:
AI Examples:
Voice Assistants: Devices like Amazon's Alexa, Apple's Siri, or Google Assistant use AI to understand and respond to voice commands. You can ask them to play music, tell you the weather, or control smart home devices.
Navigation Systems: GPS apps like Google Maps or Waze use AI to analyze traffic patterns and provide the fastest route to your destination. They take into account real-time traffic data, road closures, and other factors to guide you.
ML Examples:
Recommendation Systems: Platforms like Netflix, Amazon, or Spotify use Machine Learning to analyze your past behavior and preferences to recommend movies, products, or music that you might like. The more you use these services, the better they get at recommending things tailored to your tastes.
Spam Filters in Email: Your email provider likely uses Machine Learning to filter out spam emails. By analyzing the content and sender information of millions of emails, the system learns to recognize what typical spam emails look like and can filter them out of your inbox.
These examples show how AI and ML are integrated into many aspects of life, often working behind the scenes to enhance user experience and efficiency.
Run AI models side by side
Did you know you can run AI models side by side on one screen and see how they stack up with their responses? Give it a try.
Ohio AI Forum in Cincinnati
I was fortunate enough to attend this in person and hear the amazing companies in Cincinnati leveraging AI for good like TQL, Fifth Third (increased loan approvals through AI), Cincinnati Children’s (using AI to help with predictive anxiety in children), Microsoft, KPMG (built internal AI with over 500,000 (chats) conversations and many use cases and only cost them $3000), Kroger, UC and P&G.
“AI is going to be our partner for the rest of our lives, whether we like it or not," said Ali Minai, Ph.D., Professor of Engineering at the University of Cincinnati.
Lt. Gov. Jon Husted said efforts are underway to help classrooms across Ohio embrace technological advances that are happening at lightning speed.
"Rather than worrying about how AI can be used to cheat, let's figure out how to integrate it into education systems so students are turning out of our schools ready to go," Husted said.
If you missed it, here is the replay. https://fb.watch/mgYZuVbZAB/