From search results to your chatbot, you interact with AI in some form. But is machine learning and AI the same? We delved a bit deeper to help you understand what the difference is and the most common examples of AI and machine learning in our lives.
Artificial intelligence (AI) and machine learning are often used interchangeably. One of popular Google search requests is “are artificial intelligence and machine learning the same thing?” There are subtle differences but the most important one is that machine learning is based on machines learning and evolving (similar to what some scientists refer to as deep learning) while AI refers to a broader idea where machines can execute tasks "smartly." It can include machine learning, deep learning and other techniques to solve actual problems.
AI is a science like mathematics or biology that studies ways to build intelligent programs and machines that can creatively solve problems, traditionally considered a human prerogative. AI systems are powered by algorithms, using techniques such as machine learning, deep learning and rules. Machine learning algorithms feed computer data to AI systems, using statistical techniques to enable AI systems to learn. Through machine learning, AI systems get progressively better at tasks, without having to be specifically programmed to do so.
AI can encompass anything from Google's search algorithms to IBM's Watson, to autonomous weapons. AI technologies have transformed the capabilities of businesses globally, enabling humans to automate previously time-consuming tasks and gain untapped insights into their data through rapid pattern recognition.
Machine learning is a subset of AI that provides systems with the ability to automatically learn and improve from experience without being explicitly programmed. This also includes deep learning which uses the neural networks to analyze different factors within a structure that is similar to the human neural system.
Some of the most common use of AI using machine learning to deliver some services that have quickly become ubiquitous in our lives include:
- Virtual Personal Assistants: Virtual assistants like Google Assistant, Siri or Alexa use machine learning as they collect and refine the information on the basis of your previous interaction to render results that are tailored to your preferences.
- Maps and traffic Predictions: When using GPS navigation services, our current locations and velocities are being saved at a central server for managing traffic. This data is used to build a map of the current traffic. While this helps in preventing the traffic and does congestion analysis, the underlying problem is that there are fewer cars equipped with GPS. AI and machine learning in such scenarios help to estimate the regions where congestion can be found on the basis of daily experiences.
- Social media: We all have been recommended people to connect to or what we should watch or what might be of interest to us. It is an annoying or useful tool depending on the platform. From personalizing your news feed to better ads targeting you, social media platforms are utilizing machine learning for their own and user benefits.
- Online customer support: A number of websites today offer the option to chat with a customer support representative. In most of the cases, you talk to a chatbot. These bots tend to extract information from the website and present it to the customers. Some of the better chatbots tend to understand the user queries better and serve them with better answers, which is possible due to its machine learning algorithms.
- Search engines: Google and other search engines use machine learning to improve the search results for you. Every time you execute a search, the algorithms at the backend keep a watch at how you respond to the results and improve every time you search. If you open the top results and stay on the web page for long, the search engine assumes that the results it displayed were in accordance with the query. Similarly, if you reach the second or third page of the search results but do not open any of the results, the search engine estimates that the results served did not match requirement.
- Product Recommendations: Most shopping websites like Amazon or Souq (and some of the more sophisticated websites and apps) usually recommend items that somehow matches your taste. Machine learning is responsible for analysing your behaviour and interaction with the website/app based on past purchases, items liked or added to cart, brand preferences etc, to make these product recommendations.
Our lives are all online in some form or the other. And AI/machine learning touches us on a lot of different levels. As we learn to leverage these technologies better, the hope is that some aspects of our lives (business and personal) will be easier.