Graham Neubig

Join Robert Brennan, CEO of All Hands AI, and Graham Neubig, Co-Founder and Chief Scientist, as they dive into the evolving landscape of AI in software development. They explore how AI tools are reshaping coding workflows, from enhancing developer productivity to managing GitHub issues with open-source agents. The duo discusses trust in AI, coding on the go, and the creative shift in perception around programming. Discover how these innovations are not just about efficiency but transforming coding into a collaborative and accessible craft.

Graham Neubig, a Professor at CMU and chief scientist at All Hands AI, dives into the future of coding agents. He discusses the rise of agents by 2025, highlighting the outstanding achievements of OpenHands in software engineering. The conversation covers the integration of human expertise into agent functionality, the significance of effective prompts, and the advancements in AI agents within the Sweebench repository. Neubig also tackles challenges in AI development, emphasizing the role of accessible technology and innovative benchmarks for improvement.

Expert guests Graham Neubig and Aman Sanger discuss AI topics like Code Edits, Sandboxes, Academia vs Industry. They delve into Benchmarks like SWEBench, Dataset Contamination Detection, and GAIA Benchmark. The conversation also touches on Reasoning - Self-RAG, Let's Verify Step By Step, and developments in multi-agent systems with MetaGPT.

This week features Graham Neubig, a Carnegie Mellon professor and chief scientist at All Hands AI, who dives deep into the Open Hands project, an innovative AI coding agent. He discusses the evolution of coding agents and their role in software development. The episode highlights groundbreaking advancements in open-source AI, including massive new models with impressive context lengths. Neubig also shares insights on community collaboration for AI evaluation, stressing the importance of maintaining code quality in an evolving tech landscape.

Graham Neubig, Associate Professor of Computer Science at Carnegie Mellon University, discusses his research on multilingual natural language processing and machine translation. He compares large language models with special-purpose machine translation models, highlighting GPT-3.5 Turbo's cost advantage. He predicts companies will use general-purpose LLMs and fine-tune them for specific tasks. The podcast also covers speech-to-speech machine translation system releases and Graham's startup, Inspired Cognition, focused on improving AI systems.