All Work Published on Machine Learning
A Stanford team has developed Sophia, a new way to optimize the pretraining of large language models that’s twice as fast as current approaches.
A Stanford team has developed Sophia, a new way to optimize the pretraining of large language models that’s twice as fast as current approaches.
Scholars outline the best possible uses for these tools and the path to deployment.
Scholars outline the best possible uses for these tools and the path to deployment.
The Multi-VALUE framework achieves consistent performance across dozens of English dialects.
The Multi-VALUE framework achieves consistent performance across dozens of English dialects.
Generative AI claims to produce new language and images, but when those ideas are based on copyrighted material, who gets the credit? A new paper from Stanford University looks for answers.
Generative AI claims to produce new language and images, but when those ideas are based on copyrighted material, who gets the credit? A new paper from Stanford University looks for answers.
Could Self-Supervised Learning Be a Game-Changer for Medical Image Classification?
Supervised methods for training medical image models aren’t scalable. A new review highlights the potential of self-supervised learning.
Supervised methods for training medical image models aren’t scalable. A new review highlights the potential of self-supervised learning.
Researchers develop a new tool to measure how well popular large language models align with public opinion to evaluate bias in chatbots.
Researchers develop a new tool to measure how well popular large language models align with public opinion to evaluate bias in chatbots.
