AI: Artificial Intelligence (AI) is usually defined as the science of making computers do things that require intelligence when done by humans. AI has had some success in limited, or simplified, domains (Courtesy of AlanTuring.net).
First, there are different types of artificial intelligence (AI): weak and strong. Weak AI might behave as though a robot or manufacturing line is thinking on its own. However, it’s supervised programming, which means there is a programmed output, or action for given inputs.
Strong AI is a system that might actually change an output based on given goals and input data. A program could do something it wasn’t programmed to if it notices a pattern and determines a more efficient way of accomplishing the goal it was given.
For example, when an AI program was instructed to obtain the highest score it could in the video game Breakout, it was able to learn how to perform better and was able to outperform humans in just 2.5 hours. Researchers let the program run. To their surprise, the program developed a strategy that was not in the software. It would focus on one spot of bricks to poke a hole so the ball would get behind the wall. This minimizes the work, as the computer no longer has to move the bat while the score would increase. This also minimizes the chances of missing the ball and ending the game.
source: https://www.machinedesign.com/automation-iiot/article/21835631/whats-the-difference-between-ai-and-machine-learning?gclid=EAIaIQobChMIns3gkJOn_gIVXfHjBx3OxQ6lEAAYAiAAEgKNqfD_BwE
Machine Learning (ML) is a subset of Artificial Intelligence (AI). AI refers to the ability of machines to exhibit human-like intelligence and cognitive abilities, including learning, reasoning, problem-solving, and decision-making.
Machine learning, on the other hand, is a specific technique that allows machines to learn from data and improve their performance on a specific task without being explicitly programmed. In other words, machine learning is a way of achieving AI.
There are three main types of machine learning:
In summary, AI is a broad field that encompasses a variety of techniques and applications, including machine learning. Machine learning is a specific technique within AI that allows machines to learn from data and improve their performance on a specific task.
Herbert Simon (1916 - 2001)
"AI can have two purposes:
•One is to use the power of computers to augment human thinking, just as we use motors to augment human or horse power. Robotics and expert systems are major branches of that.
•The other is to use a computer's artificial intelligence to understand how humans think. In a humanoid way. If you test your programs not merely by what they can accomplish, but how they accomplish it, they you're really doing cognitive science; you're using AI to understand the human mind. "
ML doesn't solve the second problem...
To solve the second problem, we need to understand and implement "Subjectivity" and "Spirituality" (Soul) in AI... In general, it is clear how to do it... (I describe it in a new book)...
Good luck to all!
Machine learning (ML) and artificial intelligence (AI) are closely related fields, but they are not the same thing. Here are some key differences between the two:
Overall, ML is a subset of AI that focuses specifically on algorithms that can learn from data, while AI is a broader field that encompasses a range of techniques and applications beyond just ML.
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