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2. Machine learning - Wikipedia

   en.wikipedia.org/wiki/Machine_learning

   Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]

3. The key differences between rule-based AI and machine learning

   www.aol.com/key-differences-between-rule-based...

   Companies across industries are exploring and implementing artificial intelligence (AI) projects, from big data to robotics, to automate business processes, improve customer experience, and ...

4. Machine learning in bioinformatics - Wikipedia

   en.wikipedia.org/wiki/Machine_learning_in...

   Methods to achieve this task are varied and span many disciplines; most well known among them are machine learning and statistics. Classification and prediction tasks aim at building models that describe and distinguish classes or concepts for future prediction. The differences between them are the following:

5. Artificial general intelligence - Wikipedia

   en.wikipedia.org/wiki/Artificial_general...

   Weak AI hypothesis: An artificial intelligence system can (only) act like it thinks and has a mind and consciousness. The first one he called "strong" because it makes a stronger statement: it assumes something special has happened to the machine that goes beyond those abilities that we can test.

6. A beginner’s guide to AI: The difference between human and ...

   www.aol.com/beginner-guide-ai-difference-between...

   The guide contains articles on (in order published) neural networks, computer vision, natural language processing, algorithms, artificial general intelligence, and the difference between video ...

7. Precision and recall - Wikipedia

   en.wikipedia.org/wiki/Precision_and_recall

   In a classification task, the precision for a class is the number of true positives (i.e. the number of items correctly labelled as belonging to the positive class) divided by the total number of elements labelled as belonging to the positive class (i.e. the sum of true positives and false positives, which are items incorrectly labelled as belonging to the class).

8. Neural network (machine learning) - Wikipedia

   en.wikipedia.org/wiki/Neural_network_(machine...

   This model paved the way for research to split into two approaches. One approach focused on biological processes while the other focused on the application of neural networks to artificial intelligence. In the late 1940s, D. O. Hebb [14] proposed a learning hypothesis based on the mechanism of neural plasticity that became known as Hebbian ...

9. The Gap Between Open and Closed AI Models Might Be ... - AOL

   www.aol.com/gap-between-open-closed-ai-141710282...

   “A key difference between Meta and closed model providers is that selling access to AI models isn’t our business model,” Meta CEO Mark Zuckerberg wrote in an open letter in July. “We ...