Scaling Transformer to Output Over 2 Million Words With RMT

Recurrent Memory Transformer retains information across up to 2 million tokens (words). Applying Transformers to long texts does not necessarily require large

Related Keywords

Rowan Cheung , Robert Jordan , Brian Wang , Victor Hugo , Harry Potter , Elon Musk , Head Of Research , Singularity University , Recurrent Memory Transformer , Applying Transformers , Large Language Models , Memory Transformer , Futurist Thought Leader , Artificial Intelligence , Anti Aging Biotechnology , Angel Investor ,