Women in AI Research (WiAIR)
Women in AI Research (WiAIR)
Podcast Description
Women in AI Research (WiAIR) is a podcast dedicated to celebrating the remarkable contributions of female AI researchers from around the globe. Our mission is to challenge the prevailing perception that AI research is predominantly male-driven. Our goal is to empower early career researchers, especially women, to pursue their passion for AI and make an impact in this rapidly growing field. You will learn from women at different career stages, stay updated on the latest research and advancements, and hear powerful stories of overcoming obstacles and breaking stereotypes.
Podcast Insights
Content Themes
The podcast focuses on topics such as bias in AI, the limitations of transformer models, and the personal journeys of women in AI research. Episodes include discussions on the social implications of AI, technical challenges in language models, and the overall impact of diverse voices in the AI field.
Women in AI Research (WiAIR) is a podcast dedicated to celebrating the remarkable contributions of female AI researchers from around the globe. Our mission is to challenge the prevailing perception that AI research is predominantly male-driven. Our goal is to empower early career researchers, especially women, to pursue their passion for AI and make an impact in this rapidly growing field. You will learn from women at different career stages, stay updated on the latest research and advancements, and hear powerful stories of overcoming obstacles and breaking stereotypes.
Do large language models truly understand language—or are they sophisticated pattern matchers?
In this conversation, Dr. Anna Ivanova (Asst. Prof. at Georgia Tech) explores one of the important questions in AI: the relationship between language, thought, and intelligence. Drawing from neuroscience, cognitive science, and AI research, Anna explains why language understanding is harder to define than most people realize, why reasoning and language are not the same thing, and what today's LLMs can and cannot tell us about human cognition.
Key Topics:
- Do LLMs understand language or merely generate convincing text?
- The difference between formal and functional linguistic competence
- What LLMs can learn from language alone—and what they cannot
- Why human cognition and AI cognition may be fundamentally different
- Theory of mind, reasoning, and common misconceptions about AI capabilities
- How cognitive scientists evaluate the ”thinking” abilities of LLMs
- What neuroscience can teach AI researchers about interpretability
- Why understanding AI requires studying both behavior and internal representations
- The future of multimodal models and AI cognition
Resources & Links:
- What does it mean to understand language?
- Dissociating language and thought in large language models
- How to evaluate the cognitive abilities of LLMs
- How Do LLMs Use Their Depth?
- True Lens
Connect with Dr. Anna Ivanova:
https://bsky.app/profile/neuranna.bsky.social
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