Making a Mind

While we gear up for Season 2, we're sharing a special episode to bridge the seasons. Recorded live at SXSW, this conversation examines how AI agents are moving out of controlled research environments and into real-world consumer applications—and what it takes to make them reliable enough to matter. Cognitive scientist Danielle Perszyk is joined by Amanda Doerr, VP of Core Shopping at Amazon, Mich...

What would it mean to design AI for human flourishing? In the final episode of this season of “Making a Mind,” Cognitive scientist Dr. Danielle Perszyk sits down with Dr. Pat Pataranutaporn, Assistant Professor at the MIT Media Lab and founder of the Cyborg Psychology group, to explore how we move beyond optimizing models—and toward optimizing&nbsp...

Human minds are scaffolded by the tools we create, but what happens when we build tools that can use other tools?    Cognitive scientist Danielle Perszyk sits down with AI researcher Vibhaa Sivaraman to discuss agent tool use and the future of the digital world. They unpack what it really means to build computer-use agents—not just chatbots with function calls—by expl...

Pre-trained language models already contain vast knowledge—the challenge is producing the reasoning needed to handle ambiguous, multi-step tasks. Cognitive scientist Dr. Danielle Perszyk sits down with Amazon AI researcher, Meiqi Sun, to explore the shift from simple action execution to high-reasoning agents.  Drawing parallels to human cognitive development, the...

What if the key to building intelligent agents isn't just better models, but better teachers? Cognitive scientist Dr. Danielle Perszyk sits down with AI researcher Anirudh (Ani) Chakravarthy from Amazon's AGI Lab to explore how agents learn—not through memorization of data sets, but through structured experience.   Drawing parallels to human development...

A system that succeeds once is a demo. A system that succeeds every time is a breakthrough. Dr. Danielle Perszyk sits down with AI researcher Deniz Birlikci from Amazon's AGI Lab to explore how reinforcement learning (RL) is transforming AI agents from impressive demos into dependable tools that work consistently in real-world environments.    Danielle and Deniz discu...

Before an AI agent can reason or plan, it has to see. Dr. Danielle Perszyk and AI researcher Matthew Elkherj explore why user interface (UI) understanding is one of the most underestimated challenges in building autonomous agents—and why it’s foundational to creating reliable AI teammates.  Danielle and Matthew discuss the distinct reliability requireme...

How did we get from language models to AI agents that can take action? Dr. Danielle Perszyk sits down with Kelsey Szot, product lead at Amazon's AGI Lab and one of the original founders of Adept (a startup that helped pioneer modern AI agents) to discuss the technical breakthroughs that transformed AI from pattern recognition to agentic capabilities. Danielle and...

How do you build environments complex enough to train agents that can handle the real web? Dr. Danielle Perszyk sits down with Jason Laster, an engineer leading Amazon's AGI Lab's effort to build reinforcement learning (RL) gyms— simulated web environments where agents learn—to explore how environment development is as critical as models, data, and comp...

Coming soon!