The agencies support responsible innovation by financial institutions that includes identifying and managing risks associated with the use of new technologies. With appropriate governance, risk management, and compliance, the use of innovative technologies by financial institutions, such as those involving artificial intelligence, have the potential to enhance business decision making and improve the services available to consumers and businesses
The massive use of Artificial Intelligence systems is beginning to strongly affect the financial sector. It is no coincidence that a number of organizations that regulate finance in the United States have launched an RFI (request for information), which will expire on June 1st, to indicate the key points to be resolved. The promoters of this initiative, entitled “Request for Information and Comment on Financial Institutions’ Use of Artificial Intelligence, Including Machine Learning ”, are: the CFPB, the Consumer Financial Protection Bureau, the Federal Deposit Insurance Corporation (FDIC) which deals with bank deposits and supervises them, the Office of the Comptroller of the Currency, the Federal Reserve Board, and the National Credit Union Administration, which supervises the US rural banks
This "Deep Learning vs Machine Learning vs AI vs Data Science" video talks about the differences and relationship between Artificial Intelligence, Machine Learning, Deep Learning, and Data Science.
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Artificial Intelligence (AI) vs Machine Learning vs Deep Learning vs Data Science: Artificial intelligence is a field where set of techniques are used to make computers as smart as humans. Machine learning is a sub domain of artificial intelligence where set of statistical and neural network based algorithms are used for training a computer in doing a smart task. Deep learning is all about neural networks. Deep learning is considered to be a sub field of machine learning. Pytorch and Tensorflow are two popular frameworks that can be used in doing deep learning.