Let’s say you have a pretrained language model and a small amount of data to fine-tune it to answer yes-or-no questions. Should you fine-tune it to classify yes/no or to fill in missing words — both viable approaches that are likely to yield different results?
Let’s say you have a pretrained language model and a small amount of data to fine-tune it to answer yes-or-no questions. Should you fine-tune it to classify yes/no or to fill in missing words — both viable approaches that are likely to yield different results?
Programming is hard. Programming competitions are harder. Yet transformers proved themselves up to the task.
Facebook’s parent company is staking its future on a new compute cluster. Meta unveiled AI Research SuperCluster (RSC), which is designed to accelerate training of large models for applications like computer vision, natural language processing, and speech recognition.
Programming is hard. Programming competitions are harder. Yet transformers proved themselves up to the task.
Facebook’s parent company is staking its future on a new compute cluster. Meta unveiled AI Research SuperCluster (RSC), which is designed to accelerate training of large models for applications like computer vision, natural language processing, and speech recognition.
OpenAI unveiled a more reliable successor to its GPT-3 natural language model. InstructGPT is a version of GPT-3 fine-tuned to minimize harmful, untruthful, and biased output. It's available via an application programming interface.
OpenAI unveiled a more reliable successor to its GPT-3 natural language model. InstructGPT is a version of GPT-3 fine-tuned to minimize harmful, untruthful, and biased output. It's available via an application programming interface.
Researchers discovered a new way to reduce memory requirements when training large machine learning models. Tim Dettmers and colleagues at University of Washington released 8-bit optimizers that store gradient statistics as 8-bit values, while maintaining the same accuracy.
Amazon reported long-term success using machine learning to shrink its environmental footprint. The online retailer developed a system that fuses product descriptions, images, and structured data to decide how an item should be packed for shipping.
Researchers discovered a new way to reduce memory requirements when training large machine learning models. Tim Dettmers and colleagues at University of Washington released 8-bit optimizers that store gradient statistics as 8-bit values, while maintaining the same accuracy.
Amazon reported long-term success using machine learning to shrink its environmental footprint. The online retailer developed a system that fuses product descriptions, images, and structured data to decide how an item should be packed for shipping.
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.
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.
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