Images in the wild may not come with labels, but they often include metadata. A new training method takes advantage of this information to improve contrastive learning.
Images in the wild may not come with labels, but they often include metadata. A new training method takes advantage of this information to improve contrastive learning.
I believe that natural language processing in 2022 will re-embrace symbolic reasoning, harmonizing it with the statistical operation of modern neural networks. Let me explain what I mean by this.
I believe that natural language processing in 2022 will re-embrace symbolic reasoning, harmonizing it with the statistical operation of modern neural networks. Let me explain what I mean by this.
Until recently, big data processing has been dominated by batch systems like MapReduce and Spark, which allow us to periodically process a large amount of data very efficiently.
Until recently, big data processing has been dominated by batch systems like MapReduce and Spark, which allow us to periodically process a large amount of data very efficiently.
From language to vision models, deep neural networks are marked by improved performance, higher efficiency, and better generalizations. Yet, these systems are also marked by perpetuation of bias and injustice.
From language to vision models, deep neural networks are marked by improved performance, higher efficiency, and better generalizations. Yet, these systems are also marked by perpetuation of bias and injustice.
Is AI becoming inbred? The fear: The best models increasingly are fine-tuned versions of a small number of so-called foundation models that were pretrained on immense quantities of data scraped from the web.
Is AI becoming inbred? The fear: The best models increasingly are fine-tuned versions of a small number of so-called foundation models that were pretrained on immense quantities of data scraped from the web.
The emerging generation of trillion-parameter models needs datasets of billions of examples, but the most readily available source of examples on that scale — the web — is polluted with bias and antisocial expressions. A new study examines the issue.
The emerging generation of trillion-parameter models needs datasets of billions of examples, but the most readily available source of examples on that scale — the web — is polluted with bias and antisocial expressions. A new study examines the issue.
DeepMind opened access to AlphaFold, a model that finds the shapes of proteins, and to its output so far — a potential cornucopia for biomedical research. The research lab, a division of Google’s parent company Alphabet, made AlphaFold freely available.
DeepMind opened access to AlphaFold, a model that finds the shapes of proteins, and to its output so far — a potential cornucopia for biomedical research. The research lab, a division of Google’s parent company Alphabet, made AlphaFold freely available.
Researchers found serious flaws in an influential language dataset, highlighting the need for better documentation of data used in machine learning.
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