Artificial intelligence
Machine learning
Deep learning
Generative artificial intelligence
Reproduced with the permission of Les bibliothèques de l’Université de Montréal – Source : “ Intelligence artificielle générative - Différencier IA et IAg”, par les bibliothèques UdeM, sous licence CC BY 4.0 À savoir - Intelligence artificielle générative - La boîte à outils at Université de Montréal
Machine learning
Machine learning uses algorithms to extract information, detect patterns, and make automated decisions. The data is provided by humans.
Examples:
- Content platforms analyze your viewing habits to suggest movies, music, and products that match what you watch.
- Shopping sites make personalized suggestions for products that complement your purchase.
- Search engines use predictive search to respond to your queries.
Generative artificial intelligence
For text, for example, the system—called a large language model—predicts the probability that a given word will be followed by a certain word or used in a certain sentence. Artificial intelligence has evolved considerably and very quickly in recent years, especially since the launch of ChatGPT in November 2022. Artificial intelligence now enables “conversation” in natural language through chatbots like ChatGPT.
Generative artificial intelligence is a subcategory of deep learning. A massive amount of data is used to train the neural network, which then becomes capable of generating new content (images, videos, audio, text). This content generation is actually based on a statistical prediction system: the neural network creates a model of the type of content requested (text in a given language, a certain type of image) and predicts the probability that one form will appear after another to provide the most plausible result possible.
Examples:
- Text generators (e.g., ChatGPT and Microsoft Copilot)
- Multimedia content generators (e.g., images and videos)
- For more examples of tools, see the Explore Tools page.
Deep learning
Deep learning is based on artificial neural networks inspired by the human brain. The system learns and adapts, becoming capable of performing specific tasks such as visual recognition.
Examples:
- Images: Deep learning is achieved by feeding the system thousands of images of an object so that it can recognize it on its own. For example, to detect certain diseases in medical imaging, the machine has ingested thousands of images of brain tumors to identify them on new X-rays.
- Voice assistant applications: Siri, Alexa, Google Home.
- Other examples include object detection by autonomous vehicles, facial recognition, car navigation assistance, and machine translation.
Artificial intelligence (1950)
Artificial intelligence has been present in our lives since its inception in 1950.
Examples:
- It can be found in online maps.
- We challenge it in video games when we play “against the computer.”
- It retouches photos (for example, by recognizing red eyes).
- It detects credit card fraud.
- In smart watches, it detects falls and sorts spam.
Not all artificial intelligence is the same. Different types include machine learning, deep learning, and as a subcategory of deep learning, generative artificial intelligence.
EN-Différencier l’IA et l’IAg
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Transcript
Artificial intelligence
Machine learning
Deep learning
Generative artificial intelligence
Reproduced with the permission of Les bibliothèques de l’Université de Montréal – Source : “ Intelligence artificielle générative - Différencier IA et IAg”, par les bibliothèques UdeM, sous licence CC BY 4.0 À savoir - Intelligence artificielle générative - La boîte à outils at Université de Montréal
Machine learning
Machine learning uses algorithms to extract information, detect patterns, and make automated decisions. The data is provided by humans.
Examples:
Generative artificial intelligence
For text, for example, the system—called a large language model—predicts the probability that a given word will be followed by a certain word or used in a certain sentence. Artificial intelligence has evolved considerably and very quickly in recent years, especially since the launch of ChatGPT in November 2022. Artificial intelligence now enables “conversation” in natural language through chatbots like ChatGPT.
Generative artificial intelligence is a subcategory of deep learning. A massive amount of data is used to train the neural network, which then becomes capable of generating new content (images, videos, audio, text). This content generation is actually based on a statistical prediction system: the neural network creates a model of the type of content requested (text in a given language, a certain type of image) and predicts the probability that one form will appear after another to provide the most plausible result possible.
Examples:
Deep learning
Deep learning is based on artificial neural networks inspired by the human brain. The system learns and adapts, becoming capable of performing specific tasks such as visual recognition.
Examples:
Artificial intelligence (1950)
Artificial intelligence has been present in our lives since its inception in 1950.
Examples:
Not all artificial intelligence is the same. Different types include machine learning, deep learning, and as a subcategory of deep learning, generative artificial intelligence.