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Causality, LLMs & Abstractions || Matej Zečević || Causal Bandits Ep. 000 (2023)
Manage episode 382491663 series 3526805
Support the show
Video version of this episode available on YouTube
Recorded on Aug 14, 2023 in Frankfurt, Germany
Are Large Language Models (LLMs) causal?
Some researchers have shown that advanced models like GPT-4 can perform very well on certain causal benchmarks.
At the same time, from the theoretical point of view it's highly unlikely that these models can learn causal structures. Is it possible that large language models are not causal, but talk causality?
In our conversation we explore this question from the point of view of the formalism proposed by Matej and his colleagues in their "Causal Parrots" paper.
We also discuss Matej's journey from the dream of becoming a hacker to a successful AI and then causality researcher. Ready to dive in?
Links
- Events
- Causality Discussion Group (https://discuss.causality.link/)
- Eastern European Machine Learning Summer School (https://www.eeml.eu/home)
- Videos
- Prof. Moritz Helmstaedter on connectomics
- Books
- Molak (2023) - Causal Inference & Discovery in Python
- Pearl & Mackenzie (2019) - The Book of Why
- Papers
- For full list of papers see the episode's description here.
Causal Bandits Podcast
Causal AI || Causal Machine Learning || Causal Inference & Discovery
Web: https://causalbanditspodcast.com
Connect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/
Join Causal Python Weekly: https://causalpython.io
The Causal Book: https://amzn.to/3QhsRz4
Chapter
1. Causality, LLMs & Abstractions || Matej Zečević || Causal Bandits Ep. 000 (2023) (00:00:00)
2. [Ad] Rumi.ai (00:28:54)
3. (Cont.) Causality, LLMs & Abstractions || Matej Zečević || Causal Bandits Ep. 000 (2023) (00:29:43)
28 episode
Manage episode 382491663 series 3526805
Support the show
Video version of this episode available on YouTube
Recorded on Aug 14, 2023 in Frankfurt, Germany
Are Large Language Models (LLMs) causal?
Some researchers have shown that advanced models like GPT-4 can perform very well on certain causal benchmarks.
At the same time, from the theoretical point of view it's highly unlikely that these models can learn causal structures. Is it possible that large language models are not causal, but talk causality?
In our conversation we explore this question from the point of view of the formalism proposed by Matej and his colleagues in their "Causal Parrots" paper.
We also discuss Matej's journey from the dream of becoming a hacker to a successful AI and then causality researcher. Ready to dive in?
Links
- Events
- Causality Discussion Group (https://discuss.causality.link/)
- Eastern European Machine Learning Summer School (https://www.eeml.eu/home)
- Videos
- Prof. Moritz Helmstaedter on connectomics
- Books
- Molak (2023) - Causal Inference & Discovery in Python
- Pearl & Mackenzie (2019) - The Book of Why
- Papers
- For full list of papers see the episode's description here.
Causal Bandits Podcast
Causal AI || Causal Machine Learning || Causal Inference & Discovery
Web: https://causalbanditspodcast.com
Connect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/
Join Causal Python Weekly: https://causalpython.io
The Causal Book: https://amzn.to/3QhsRz4
Chapter
1. Causality, LLMs & Abstractions || Matej Zečević || Causal Bandits Ep. 000 (2023) (00:00:00)
2. [Ad] Rumi.ai (00:28:54)
3. (Cont.) Causality, LLMs & Abstractions || Matej Zečević || Causal Bandits Ep. 000 (2023) (00:29:43)
28 episode
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