Neural networks (connectionist AI) are powerful learning algorithms, but training them comes with several key challenges. Below are explanations of four major challenges in training neural networks.
https://www.v7labs.com/blog/overfitting
https://www.ibm.com/think/topics/catastrophic-forgetting#:~:text=Catastrophic forgetting occurs when neural,in a sequential learning process
https://jelvix.com/blog/catastrophic-forgetting#:~:text=Catastrophic interference%2C also referred to,previously learned as soon as
https://www.rapidinnovation.io/post/best-practices-ai-data-privacy#:~:text=At Rapid Innovation%2C we understand,our data privacy compliance software
https://www.nist.gov/blogs/cybersecurity-insights/privacy-attacks-federated-learning#:~:text=memorize their training data in,Recent work by Haim et
https://superagi.com/mastering-ai-powered-crm-security-in-2025-a-beginners-guide-to-data-protection-and-compliance/#:~:text=Protecting training data is a,access and potential data breaches
https://www.arbor.eco/blog/ai-environmental-impact#:~:text=Is AI increasing carbon emissions%3F
https://marmelab.com/blog/2025/03/19/ai-carbon-footprint.html#:~:text=Modern AI tools offer impressive,leading to substantial CO2 emissions