Current Deep Learning architectures grow to learn from complex datasets
Current Deep Learning (DL) architectures are growing larger to learn from complex datasets. Training and tuning astronomical sized models are time and energy consuming and stalls the progress in AI. Industries are increasingly investing in specialized hardware and deep learning accelerators like TPUs and GPUs to scale up the process.
Current Deep Learning (DL) architectures are growing larger to learn from complex datasets. Training and tuning astronomical sized models are time and energy consuming and stalls the progress in AI. Industries are increasingly investing in specialized hardware and deep learning accelerators like TPUs and GPUs to scale up the process.
process, GPUs, TPUs, industries, progress, training, specialized hardware, complex datasets, astronomical sized models, deep learning accelerators, Current Deep Learning (DL) architectures
