Mohammad Shoeybi

Mohammad Shoeybi is a senior research scientist and manages the NLP team within the Applied Deep Learning Research group at NVIDIA. His team focuses on language modeling, NLP applications such as question answering and dialogue systems, and large-scale training. He received his PhD. from Stanford University in 2010. Prior to NVIDIA, he worked at DeepMind and Baidu USA leading efforts on bringing deep learning and reinforcement learning to applications.
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Posts by Mohammad Shoeybi

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Conversational AI

Curating Trillion-Token Datasets: Introducing NVIDIA NeMo Data Curator

The latest developments in large language model (LLM) scaling laws have shown that when scaling the number of model parameters, the number of tokens used for... 8 MIN READ
Conversational AI

Scaling Language Model Training to a Trillion Parameters Using Megatron

Natural Language Processing (NLP) has seen rapid progress in recent years as computation at scale has become more available and datasets have become larger. At... 17 MIN READ
Simulation / Modeling / Design

Adding External Knowledge and Controllability to Language Models with Megatron-CNTRL

Large language models such as Megatron and GPT-3 are transforming AI. We are excited about applications that can take advantage of these models to create better... 8 MIN READ
Conversational AI

State-of-the-Art Language Modeling Using Megatron on the NVIDIA A100 GPU

Recent work has demonstrated that larger language models dramatically advance the state of the art in natural language processing (NLP) applications such as... 9 MIN READ