Charles Foster
Member Of Policy Staff at METR
Oakland, California, United States
Summary
🤩
Rockstar🎓
Top SchoolCharles Foster is a policy-focused technologist and applied AI scientist with a decade of experience at the intersection of research, product, and public-facing commentary. After earning advanced degrees from Stanford, he progressed from multimedia and VR audio research roles into R&D and AI leadership at Accenture and Finetune, later translating that expertise into independent AI commentary before joining METR's policy staff. He blends deep technical understanding of machine learning with a keen eye for design and user experience, driven by an interest in how aesthetics and technology shape everyday life. Based in Oakland, he brings practical research experience, startup agility, and a habit of communicating complex AI issues to diverse audiences.
10 years of coding experience
5 years of employment as a software developer
Master's Degree, Master's Degree at Stanford University
Github Skills (105)
language-model10
python10
radiance10
deep-learning10
transformer10
evaluation-framework10
nlp10
natural-language-processing10
pytorch10
evaluation10
machine-learning10
large-language-models10
neural-rendering9
stream9
transformers9
Programming languages (11)
Github contributions (5)
cfoster0/CLAP
Apr 2021 - Mar 2022
Contrastive Language-Audio Pretraining
Contributions:32 commits, 21 PRs, 62 pushes in 10 months
contrastivepretrainingaudio
cfoster0/simple-parallel-transformer
Jun 2021 - Mar 2022
As it says on the tin, this repo has a simple implementation of a transformer model, with some borrowed efficiency improvements. The purpose is mainly pedagogical.
Contributions:59 commits, 4 PRs, 111 pushes in 9 months
pytorchnlptransformersbertdeep-learning
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