What’s the difference between Artificial Intelligence, Machine Learning and Deep Learning?

Artificial Intelligence (AI), Deep Learning (DL) and Machine Learning (ML) are among the most popular, discussed and evolving fields in the world of technology.

These technologies have a significant impact on many industries, including robotics, where they are used to develop intelligent systems capable of performing complex tasks.

One of the most interesting application areas for artificial intelligence, DL and ML concerns robotic arm projects. In this article, we’ll explore some examples of how AI, DL and ML are being used to develop intelligent arm robots capable of performing a wide range of tasks.

Although the three are often used interchangeably, they are distinct terms that refer to different aspects of computer systems. Artificial intelligence is the broadest term, encompassing all forms of computer systems capable of performing tasks that generally require human intelligence. On the other hand, Machine Learning and Deep Learning are sub-fields of AI that involve training computers to learn from data, recognize patterns and make predictions.

For each of them, we’ll first give a simple but precise definition, then illustrate it with our favorite subject: robotic arm design and engineering.

Artificial intelligence: towards minimal human intervention?

Artificial intelligence or AI refers to the ability of a machine to perform tasks that would normally require human intelligence. In robotics, AI is used to develop intelligent systems capable of performing tasks autonomously or with minimal human intervention. Robotics projects incorporating AI technologies have shown promising results in a variety of applications, such as manufacturing, healthcare and space exploration.

One example of AI in robotic weapons projects is the use of reinforcement learning. (RL) algorithms. RL is a subfield of ML that involves training a system to make decisions based on rewards or penalties. For a robot, RL algorithms can be used to train robots to perform complex tasks, such as grasping and manipulating objects. A study by researchers at Carnegie Mellon University demonstrated the use of RL in robotic arms to perform tasks such as sorting and assembling parts in a manufacturing plant.

Deep learning: algorithms and models for real-life applications

Deep Learning or DL is a sub-field of Machine Learning that uses artificial neural networks to learn patterns in data. Deep Learning algorithms are used in a wide range of applications, including image and speech recognition, natural language processing and robotics. DL algorithms are used in robotic arms to train them to perform tasks requiring visual perception and recognition, such as detecting and tracking the edges of metal components.

You’ve probably heard of using a defined vision on a robotic arm, well, that’s an example of Deep Learning!

The development of vision-based arm robots uses Deep Learning algorithms to process visual data and identify objects, enabling the robot to grasp and manipulate objects autonomously.

At Niryo, we developed a vision-based collaborative robot that could perform selection and placement tasks with 99% accuracy. Thanks to Tensorflow (an open source machine learning tool developed by Google), recognition of multiple objects became possible with Ned2! See the example below.

https://www.youtube.com/watch?v=u3CgVEPYTII

Introducing the Ned2s camera, aka Vision Set

Machine Learning: a supervised way of developing intelligent systems

Machine Learning or ML is also a field of AI that involves training machines to learn from data. ML algorithms are mainly used in robotics to develop intelligent systems capable of performing tasks such as object recognition, path planning and decision-making.

https://www.youtube.com/watch?v=Tef6AHHUtnE

Photo courtesy of Stéphane Bonnevay, Polytech Lyon. Stéphane uses Ned, the predecessor of Ned2.

For example, the use of supervised learning algorithms is an example of machine learning. Supervised learning involves training a system using labeled data to predict the outcome of new data. A study by researchers at the University of Stuttgart demonstrated the use of supervised learning in arm robots to detect and grasp objects in a cluttered environment.

So yes, AI, DL and ML are transforming the way we think about the world. These technologies have shown promising results in a wide range of applications, from manufacturing and healthcare to space exploration. With continued research and development, robot arms will continue to become more intelligent, adaptable and capable of performing complex tasks autonomously, making them an invaluable asset in many industries, as well as in universities and research centers.

As technology continues to advance, we can expect to see even more exciting developments in robotics using AI, DL and ML. which have the potential to revolutionize the way we approach tasks that were once considered too difficult or dangerous for humans to accomplish.