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Girish Kumar

Computer Person

Girish Kumar is a talented professional with a strong background in technology and research, having gained experience from prestigious institutions like Stanford University, Google, and Instabase.

Girish Kumar holds a Bachelor of Science degree in Symbolic Systems from Stanford University, where he honed his skills and knowledge in the field.

Throughout his career, Girish has undertaken various roles, including Applications Engineering Intern at Instabase, Software Engineering Intern at Helia, and Venture Partner at Simple Ventures.

His experience also includes positions such as Data Science Intern at Intapp, Software Engineering Intern at Google AI, and Machine Learning Engineering Intern at companies like PolyAI and Carousell.

Girish Kumar has also contributed to research, having held Internship positions at A*STAR - Agency for Science, Technology and Research, as well as the MIT Media Lab.

His diverse background showcases his versatility and expertise in areas such as software engineering, machine learning, data science, and research.

Highlights

Jul 29 · twitter

To push the open source frontier for RL + LLMs, we need scalable, modular environments with real-world complexity, beyond math benchmarks.

Today, we’re releasing benchmax.

An open-source framework to build, run, & scale useful RL envs for LLM fine-tuning, with integrations to verl & verifiers (more coming soon!).

To push the open source frontier for RL + LLMs, we need scalable, modular environments with real-wor
Jul 8 · twitter

Fine-tuning LLMs typically involves two consecutive steps:

• Supervised Fine-Tuning (SFT) • Reinforcement Fine-Tuning (RFT)

I thought this new paper called Prefix-RFT was really cool! It shows how we can better blend the two. 👇🧵

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Girish Kumar
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Location

Stanford, California