Artificial Intelligence and Machine Learning are two terms that you would often hear in the technological field. People often get confused by AI and ML.
Even people who are mastering these skills are landing a high-paying job. Artificial Intelligence and Machine learning are often termed with abbreviations as AI and ML.
These days so many startups have been started that are based on artificial intelligence e.g., Gemini AI, OpenAI etc. So, it becomes very important to understand what these terms are exactly and how it’s shaping our lives from virtual assistance to many more.
What is Artificial Intelligence?
Artificial Intelligence refers to the intelligence that are created in machines and computers by humans. AI can replicate human works, reasoning, language, and problem-solving etc. AI is generally used to automate things that requires human intelligence.
There are several types of Artificial Intelligence, and some are:
i) Weak AI: It is also known as Narrow AI. These AIs can perform their duty within a defined domain and not allowed to perform tasks beyond their boundary. It can perform operations like setting reminders, suggestion theoretical solutions of problems etc. Some weak AI examples are Siri & Alexa etc.
ii) Strong AI: It is also known as General AI. It is a theoretical concept of AI because it is assumed that it can understand, learn, and apply knowledge similar to human intelligence. It can reach up to the level of human intelligence through continuous training like ChatGPT.
iii) Superintelligent AI: This is hypothetical concepts in which it is assumed that AI will surpass the human intelligence in every fields. This type of AI is considered as dangerous as it has the ability to dominate human and can cause potential risks if comes in existence.
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What is Machine Learning?
ML has emerged from AI and therefore ML is known as subset of AI. Machine Learning focuses on the algorithms development that allows computers to predict, analyze, and taking decisions on their own.
Unlike simple programmed codes that are designed to perform tasks, Machine Learning is developed by feeding enormous data to identify patterns and improve their decision-making performance.
Terms that you should know in Machine Learning are:
i) Supervised Learning: In this category, models are trained on the basis of labeled data. You give models data with correct answers.
For example, you give pictures of bike and car and on this basis, it predicts different picture whether it is car or bike. Hence, you provide data and allows models to predict other data with similar properties.
ii) Unsupervised Learning: In this category, models are trained with unlabeled data. It predicts pattern from finding similarity among data.
For example, you provide picture of groups of bikes and cars, and it predicts which one is car and bike just because of similarity of shapes.
iii) Reinforcement Learning: It this category, you provide feedback to ML models to make it more predictable.
Suppose your model, give wrong answer then you make it correct. After doing it continuously it becomes better and better.
How are Artificial Intelligence and Machine Learning related?
AI main objective is to enhance machine intelligence so that it can be capable of human-like tasks whereas, ML main goal is to provide AI datasets to improve its abilities and intelligence.
Hence, we can say that ML gives the AI skills allowing it to be better at recognizing patterns and intelligence.
Conclusion: Artificial Intelligence Vs Machine Learning
In short, AI main aim is to make machines smarter while ML main goal is to make AI better. AI and ML together making the potential to drive innovations and tackle complex problems across various fields.
This is how Artificial Intelligence and Machine Learning together making innovations are reshaping technology and our lives.
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