95. Francesca Rossi - Thinking, fast and slow: AI edition

95. Francesca Rossi - Thinking, fast and slow: AI edition

Author: The TDS team September 22, 2021 Duration: 46:42

The recent success of large transformer models in AI raises new questions about the limits of current strategies: can we expect deep learning, reinforcement learning and other prosaic AI techniques to get us all the way to humanlike systems with general reasoning abilities?

Some think so, and others disagree. One dissenting voice belongs to Francesca Rossi, a former professor of computer science, and now AI Ethics Global Leader at IBM. Much of Francesca’s research is focused on deriving insights from human cognition that might help AI systems generalize better. Francesca joined me for this episode of the podcast to discuss her research, her thinking, and her thinking about thinking.


While the active production of Towards Data Science has concluded, its archive remains a vital resource. Created by The TDS team, this collection captures a specific moment in the rapid evolution of data science and artificial intelligence. Each conversation pulls you directly into the room with leading researchers and practitioners who were shaping the tools and theories of their time. The discussions are not abstract lectures; they are grounded explorations of real-world problems, ethical dilemmas, and technical challenges that defined the field's trajectory. You'll hear experts dissect the implications of their work, from algorithmic fairness to the practicalities of deploying models at scale. This podcast served as a forum for nuanced debate, where complex ideas were unpacked with clarity and depth. Listening now offers a unique historical perspective, a chance to understand the foundational conversations that continue to influence where technology is headed next. The archive of Towards Data Science stands as a substantive record of insight, preserving the voices and questions from the forefront of a digital revolution.
Author: Language: en-us Episodes: 50

Towards Data Science
Podcast Episodes
127. Matthew Stewart - The emerging world of ML sensors [not-audio_url] [/not-audio_url]

Duration: 41:34
Today, we live in the era of AI scaling. It seems like everywhere you look people are pushing to make large language models larger, or more multi-modal and leveraging ungodly amounts of processing power to do it. But alt…
126. JR King - Does the brain run on deep learning? [not-audio_url] [/not-audio_url]

Duration: 55:43
Deep learning models — transformers in particular — are defining the cutting edge of AI today. They’re based on an architecture called an artificial neural network, as you probably already know if you’re a regular Toward…
125. Ryan Fedasiuk - Can the U.S. and China collaborate on AI safety? [not-audio_url] [/not-audio_url]

Duration: 48:19
It’s no secret that the US and China are geopolitical rivals. And it’s also no secret that that rivalry extends into AI — an area both countries consider to be strategically critical. But in a context where potentially t…
124. Alex Watson - Synthetic data could change everything [not-audio_url] [/not-audio_url]

Duration: 51:47
There’s a website called thispersondoesnotexist.com. When you visit it, you’re confronted by a high-resolution, photorealistic AI-generated picture of a human face. As the website’s name suggests, there’s no human being…
122. Sadie St. Lawrence - Trends in data science [not-audio_url] [/not-audio_url]

Duration: 43:02
As you might know if you follow the podcast, we usually talk about the world of cutting-edge AI capabilities, and some of the emerging safety risks and other challenges that the future of AI might bring. But I thought th…
121. Alexei Baevski - data2vec and the future of multimodal learning [not-audio_url] [/not-audio_url]

Duration: 49:31
If the name data2vec sounds familiar, that’s probably because it made quite a splash on social and even traditional media when it came out, about two months ago. It’s an important entry in what is now a growing list of s…