Several cases of children who grew up in extreme social isolation, such as the case of Genie in 1970, suggest that most of our mental capacities, and perhaps even the ability to think, are learned through social interaction.
There have been a number of cases of feral children raised in social isolation with little or no human contact. Few have captured public and scientific attention like that of a young girl called Genie Wiley. She spent almost her entire childhood locked in a bedroom, isolated and abused for over a decade.
Genie's case was one of the first to put the critical period theory to the test. Could a child reared in utter deprivation and isolation develop language? Could a nurturing environment make up for a horrifying past?
This article discusses Genie's life, her treatment, and the impact that abuse and deprivation had on her language development. It also covers the ethical problems with her case.
Discovery and Study (1970-1975)
Genie's story came to light on November 4, 1970, in Los Angeles, California. A social worker discovered the 13-year old girl after her mother sought out services for her own health. The social worker soon discovered that the girl had been confined to a small room, and an investigation by authorities quickly revealed that the child had spent most of her life in this room, often tied to a potty chair.
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Historically, enslaved people have resisted slavery through escaping, fighting back with physical violence, and fighting back through words (such as petitions, articles, speeches, etc.)
Because they didn't know what else to do they were poor.
A multi-task learning-based framework that utilizes a combination of self-supervised and supervised pre-training tasks to learn a generic document representation. They design the network architecture and the pre-training tasks to incorporate the multi-modal document information across text, layout, and image dimensions and allow the network to work with multi-page documents.
What do you mean by multi-task learning?
Multi-task learning, on the other hand, is a machine learning approach in which we try to learn multiple tasks simultaneously, optimizing multiple loss functions at once. Rather than training independent models for each task, we allow a single model to learn to complete all of the tasks at once.
How does multi-task learning work?
Multi-task learning is a sub field of machine learning in which multiple tasks are simultaneously learned by a shared model. Such approaches offer advantages like improved data efficiency, reduced overfitting through shared representations, and fast learning by leveraging auxiliary information
What is a multi modal?
Multi modal machine learning aims to build models that can process and relate information from multiple modalities. It is a vibrant multi-disciplinary field of increasing importance and with extraordinary potential.
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