Artificial Intelligence (AI) is a broad term that can be used to refer to any type of advanced analytical technique – including machine learning, natural language processing (NLP), and deep learning – that is used to extract meaning from unstructured data sources like text documents.
While AI is often used as a catch-all phrase to describe any type of advanced analytics, it is important to note that not all advanced analytics techniques are considered AI. For example, statistical methods like regression analysis are not typically considered AI, even though they can be used to extract meaning from data.
What is the definition of Artificial Intelligence outside of Text Analytics?
The definition of Artificial Intelligence can vary depending on who you ask. Some people might describe AI as any type of computer system that can perform tasks that would normally require human intelligence, such as understanding natural language or recognizing objects.
Others might say that AI is any computer system that can learn and improve its performance over time without being explicitly programmed to do so. This is sometimes referred to as machine learning.
Still, others might define AI as any computer system that can simulate human intelligence. This could include systems that are capable of reasoning, problem-solving, and making decisions.
Applications of Artificial Intelligence?
AI can be used for a variety of different tasks, including:
- Analyzing text documents to extract meaning and insights
- Recognizing spoken words and determining the sentiment of a conversation
- Classifying images or objects
- Making predictions based on data
- Optimizing processes or finding new patterns
These are just a few examples of how AI can be used. In general, AI can be used for any task that requires advanced analytical skills.
AI surpass human intelligence in certain specific tasks
In some cases, AI systems can outperform humans when it comes to analyzing data and making predictions. For example, Google’s AlphaGo system beat the world’s best Go player in a five-game match in 2016.
Similarly, IBM’s Watson system beat human contestants on the game show Jeopardy! in 2011.
What is the difference between Artificial Intelligence and Machine Learning?
Machine learning is a type of AI that focuses on creating algorithms that can learn from data and improve their performance over time without being explicitly programmed to do so.
Machine learning is often used for tasks like image recognition or fraud detection, where it can be difficult or impossible for humans to write explicit rules.