313 subscribers
התחל במצב לא מקוון עם האפליקציה Player FM !
126. JR King - Does the brain run on deep learning?
Manage episode 341145775 series 2546508
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 Towards Data Science reader. And if you are, then you might also already know that as their name suggests, artificial neural networks were inspired by the structure and function of biological neural networks, like those that handle information processing in our brains.
So it’s a natural question to ask: how far does that analogy go? Today, deep neural networks can master an increasingly wide range of skills that were historically unique to humans — skills like creating images, or using language, planning, playing video games, and so on. Could that mean that these systems are processing information like the human brain, too?
To explore that question, we’ll be talking to JR King, a CNRS researcher at the Ecole Normale Supérieure, affiliated with Meta AI, where he leads the Brain & AI group. There, he works on identifying the computational basis of human intelligence, with a focus on language. JR is a remarkably insightful thinker, who’s spent a lot of time studying biological intelligence, where it comes from, and how it maps onto artificial intelligence. And he joined me to explore the fascinating intersection of biological and artificial information processing on this episode of the TDS podcast.
***
Intro music:
- Artist: Ron Gelinas
- Track Title: Daybreak Chill Blend (original mix)
- Link to Track: https://youtu.be/d8Y2sKIgFWc
***
Chapters:
- 2:30 What is JR’s day-to-day?
- 5:00 AI and neuroscience
- 12:15 Quality of signals within the research
- 21:30 Universality of structures
- 28:45 What makes up a brain?
- 37:00 Scaling AI systems
- 43:30 Growth of the human brain
- 48:45 Observing certain overlaps
- 55:30 Wrap-up
132 פרקים
Manage episode 341145775 series 2546508
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 Towards Data Science reader. And if you are, then you might also already know that as their name suggests, artificial neural networks were inspired by the structure and function of biological neural networks, like those that handle information processing in our brains.
So it’s a natural question to ask: how far does that analogy go? Today, deep neural networks can master an increasingly wide range of skills that were historically unique to humans — skills like creating images, or using language, planning, playing video games, and so on. Could that mean that these systems are processing information like the human brain, too?
To explore that question, we’ll be talking to JR King, a CNRS researcher at the Ecole Normale Supérieure, affiliated with Meta AI, where he leads the Brain & AI group. There, he works on identifying the computational basis of human intelligence, with a focus on language. JR is a remarkably insightful thinker, who’s spent a lot of time studying biological intelligence, where it comes from, and how it maps onto artificial intelligence. And he joined me to explore the fascinating intersection of biological and artificial information processing on this episode of the TDS podcast.
***
Intro music:
- Artist: Ron Gelinas
- Track Title: Daybreak Chill Blend (original mix)
- Link to Track: https://youtu.be/d8Y2sKIgFWc
***
Chapters:
- 2:30 What is JR’s day-to-day?
- 5:00 AI and neuroscience
- 12:15 Quality of signals within the research
- 21:30 Universality of structures
- 28:45 What makes up a brain?
- 37:00 Scaling AI systems
- 43:30 Growth of the human brain
- 48:45 Observing certain overlaps
- 55:30 Wrap-up
132 פרקים
כל הפרקים
×
1 130. Edouard Harris - New Research: Advanced AI may tend to seek power *by default* 58:22

1 129. Amber Teng - Building apps with a new generation of language models 51:21

1 128. David Hirko - AI observability and data as a cybersecurity weakness 49:02

1 127. Matthew Stewart - The emerging world of ML sensors 41:34

1 126. JR King - Does the brain run on deep learning? 55:43

1 125. Ryan Fedasiuk - Can the U.S. and China collaborate on AI safety? 48:19

1 124. Alex Watson - Synthetic data could change everything 51:47

1 123. Ala Shaabana and Jacob Steeves - AI on the blockchain (it actually might just make sense) 54:43

1 122. Sadie St. Lawrence - Trends in data science 43:02

1 121. Alexei Baevski - data2vec and the future of multimodal learning 49:31

1 120. Liam Fedus and Barrett Zoph - AI scaling with mixture of expert models 40:47

1 119. Jaime Sevilla - Projecting AI progress from compute trends 48:34

1 118. Angela Fan - Generating Wikipedia articles with AI 51:44

1 117. Beena Ammanath - Defining trustworthy AI 46:46

1 116. Katya Sedova - AI-powered disinformation, present and future 54:24
ברוכים הבאים אל Player FM!
Player FM סורק את האינטרנט עבור פודקאסטים באיכות גבוהה בשבילכם כדי שתהנו מהם כרגע. זה יישום הפודקאסט הטוב ביותר והוא עובד על אנדרואיד, iPhone ואינטרנט. הירשמו לסנכרון מנויים במכשירים שונים.