Sewon Min: The Science of Natural LanguageOn developing practical natural language processing systems, benchmarks in NLP, text retrieval, and the limitations and promise of language models.
Richard Socher: Re-Imagining SearchOn neural networks for language, leading Salesforce Research, research and management in AI, and taking on the only game in town with a new search…
Joe Edelman: Meaning-Aligned AIHow technology sometimes fails us, and how we can make it more human.
Ed Grefenstette: Language, Semantics, CohereOn distributional semantics, pragmatics and communication, grounding and consciousness, and leading ML at Cohere.

February 2023

Ken Liu: What Science Fiction Can Teach UsOn fiction's value, critical reflection on technology, LLMs for creativity, and looking toward the future.
Hattie Zhou: Lottery Tickets and Algorithmic Reasoning in LLMsOn lottery tickets and forgetting in neural networks, endowing LLMs with algorithmic reasoning, and ML research culture.
Kyunghyun Cho: Neural Machine Translation, Language, and Doing Good ScienceOn decades of NLP research, becoming a good researcher, and finding peace and balance.
Steve Miller: Will AI Take Your Job? It's Not So Simple.On human-AI collaboration, automation vs. augmentation, AI adoption, and what this all means for workers and companies.

January 2023

Blair Attard-Frost: Canada’s AI strategy and the ethics of AI business practicesOn AI Governance in general and in Canada in particular, and a review of 47 AI business ethics guidelines
Linus Lee: At the Boundary of Machine and MindOn language, notation, better tools and mediums for thought
Suresh Venkatasubramanian: An AI Bill of RightsOn the algorithmic lens, legislating AI, and making policy as a technologist
Pete Florence: Dense Visual Representations, NeRFs, and LLMs for RoboticsOn how robotics can benefit from dense visual representations, neural radiance fields, and large language models