Fine-tuning a neural network typically involves retraining every layer on new data. But research shows that networks may perform better when fine-tuning modifies only a subset of layers.
Amid rising questions about the fairness and legality of using publicly available information to train AI models, Japan affirmed that machine learning engineers can use any data they find.
Amid rising questions about the fairness and legality of using publicly available information to train AI models, Japan affirmed that machine learning engineers can use any data they find.
The largest dataset for training text-to-image generators was assembled by volunteers for roughly $10,000. Now it’s implicated in fights over whether copyrighted works can be used for training.
The largest dataset for training text-to-image generators was assembled by volunteers for roughly $10,000. Now it’s implicated in fights over whether copyrighted works can be used for training.
Developers of language models will have to pay for access to troves of text data that they previously got for free. The discussion platform Reddit and question-and-answer site Stack Overflow announced plans to protect their data from being used to train large language models.
Developers of language models will have to pay for access to troves of text data that they previously got for free. The discussion platform Reddit and question-and-answer site Stack Overflow announced plans to protect their data from being used to train large language models.
Principal component analysis is a key machine learning technique for reducing the number of dimensions in a dataset, but new research shows that its output can be inconsistent and unreliable.
Principal component analysis is a key machine learning technique for reducing the number of dimensions in a dataset, but new research shows that its output can be inconsistent and unreliable.
Large datasets often contain overly similar examples that consume training cycles without contributing to learning. A new paper identifies similar training examples, even if they’re not labeled.
Large datasets often contain overly similar examples that consume training cycles without contributing to learning. A new paper identifies similar training examples, even if they’re not labeled.
Who would disagree that, if all people are mortal and Socrates is a person, Socrates must be mortal? GPT-3, for one. Recent work shows that bigger language models are not necessarily better when it comes to logical reasoning.
Who would disagree that, if all people are mortal and Socrates is a person, Socrates must be mortal? GPT-3, for one. Recent work shows that bigger language models are not necessarily better when it comes to logical reasoning.
The world’s supply of data soon may fail to meet the demands of increasingly hungry machine learning models. Researchers at Epoch AI found that a shortage of text data could cause trouble as early as this year. Vision data may fall short within a decade.
The world’s supply of data soon may fail to meet the demands of increasingly hungry machine learning models. Researchers at Epoch AI found that a shortage of text data could cause trouble as early as this year. Vision data may fall short within a decade.
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