Amer Sinha is a software engineer at Google Research working on machine learning.
How media typically covers Amer Sinha
Amer Sinha as author
Scaling laws for differentially private language model training accurately model compute-privacy-utility tradeoffs and identify optimal training configurations for privacy-preserving LLM development.
“Author of "Tool-space interference in the MCP era: Designing for agent compatibility at sca" on arXiv”
Referenced in coverage
Google released VaultGemma, the largest open-weight language model (1B parameters) trained from scratch with differential privacy, alongside new scaling laws quantifying compute-privacy-utility trade-offs.
“Co-introduced VaultGemma, the most capable language model trained from scratch with differential privacy.”