Xander Dunn
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About
Xander Dunn is an engineer working on deep learning. His work includes implementing large scale pre-training infrastructure in Rust, pre-training distributed Transformer foundation models across 8,000 GPUs and TRNs, and applying these models to LLM self play / self improvement with code generation. He has also worked on fine-tuning GPT and BERT models, applying WaveNets to time series forecasting, and extending GANs for signal-preserving obfuscation. Additional interests include information theory, security, and robotics.
Platform
Task
Features
• deep reinforcement learning for industrial robotics with imitation learning
• extended gans for signal-preserving obfuscation
• applied wavenets to time series forecasting
• secret sharer for characterizing unintended memorization
• fine-tuned gpt and bert models
• llm self play / self improvement with code generation
• pre-trained distributed transformer foundation models
• large scale pre-training infrastructure in rust
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