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03 - The AI That Predicted Dreams

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Manage episode 500444972 series 3683328
Content provided by Steve Atwal. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Steve Atwal or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

What if artificial intelligence could tap into your subconscious and anticipate your dreams before you even fell asleep? In this episode of AI Freaky Facts, host Steve explores a groundbreaking experiment that blurs the line between science fiction and reality. Tune in for a surreal journey into the strange intersection of sleep, neuroscience, and machine learning.

References:

1. Amano & Nakayama Lab – University of Tokyo Brain Decoding Research

https://www.brain.ipc.i.u-tokyo.ac.jp/en/

Explore their cutting-edge work on fMRI-based decoding and neural representation of visual imagery.

2. Nature Neuroscience – Decoding the Visual and Subjective Contents of the Human Brain

https://www.nature.com/articles/nn1444.pdf

This foundational study by Yukiyasu Kamitani and Frank Tong explores how fMRI data can be used to decode visual perception and subjective mental imagery — a key concept behind dream prediction AI.

3. MIT Technology Review – AI and Dream Interpretation

https://www.technologyreview.com (search “dream decoding”)

Articles exploring how AI is being used to interpret dreams and emotions.

4. Stanford University – NeuroAI Research

https://neuroscience.stanford.edu

Includes studies on emotional pattern recognition and brain-computer interfaces.

5. Neuralink – Brain-Machine Interface Projects

https://neuralink.com

Relevant to real-time dream prediction and brain interfaces.

7. IEEE Spectrum – Ethics of Brain Data and AI

https://spectrum.ieee.org (search “brain data ethics”)

Explores the risks and responsibilities of using neural data in AI systems.

8. Frontiers in Neuroscience – Dream Research & fMRI Studies

https://www.frontiersin.org/journals/neuroscience

Peer-reviewed articles on sleep, dreams, and brain imaging.

9. YouTube – DreamNet Visual Reconstructions (if available) (Search “DreamNet AI dream decoding”). Some research teams have posted visual recreations of dreams using generative AI.

Additional References:

10. Neuroba – Using AI to Decode Dreams: A Look Into the Future

https://www.neuroba.com/post/using-ai-to-decode-dreams-a-look-into-the-future-neuroba

11. AI-Driven “Smart Dreams”: Can AI Influence What We Dream About?

https://www.oxaam.com/articles/ai-driven-smart-dreams-influence/

Music Credits:

1. Tension Rising by Aylex | https://freetouse.com/music/aylex

2. 'Meanwhile' by Scott Buckley - released under CC-BY 4.0. www.scottbuckley.com.au

3. Tech Live Kevin MacLeod (incompetech.com)

Licensed under Creative Commons: By Attribution 3.0 License

http://creativecommons.org/licenses/by/3.0/

This podcast is narrated by the host's own voice, powered by AI.

  continue reading

7 episodes

Artwork
iconShare
 
Manage episode 500444972 series 3683328
Content provided by Steve Atwal. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Steve Atwal or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

What if artificial intelligence could tap into your subconscious and anticipate your dreams before you even fell asleep? In this episode of AI Freaky Facts, host Steve explores a groundbreaking experiment that blurs the line between science fiction and reality. Tune in for a surreal journey into the strange intersection of sleep, neuroscience, and machine learning.

References:

1. Amano & Nakayama Lab – University of Tokyo Brain Decoding Research

https://www.brain.ipc.i.u-tokyo.ac.jp/en/

Explore their cutting-edge work on fMRI-based decoding and neural representation of visual imagery.

2. Nature Neuroscience – Decoding the Visual and Subjective Contents of the Human Brain

https://www.nature.com/articles/nn1444.pdf

This foundational study by Yukiyasu Kamitani and Frank Tong explores how fMRI data can be used to decode visual perception and subjective mental imagery — a key concept behind dream prediction AI.

3. MIT Technology Review – AI and Dream Interpretation

https://www.technologyreview.com (search “dream decoding”)

Articles exploring how AI is being used to interpret dreams and emotions.

4. Stanford University – NeuroAI Research

https://neuroscience.stanford.edu

Includes studies on emotional pattern recognition and brain-computer interfaces.

5. Neuralink – Brain-Machine Interface Projects

https://neuralink.com

Relevant to real-time dream prediction and brain interfaces.

7. IEEE Spectrum – Ethics of Brain Data and AI

https://spectrum.ieee.org (search “brain data ethics”)

Explores the risks and responsibilities of using neural data in AI systems.

8. Frontiers in Neuroscience – Dream Research & fMRI Studies

https://www.frontiersin.org/journals/neuroscience

Peer-reviewed articles on sleep, dreams, and brain imaging.

9. YouTube – DreamNet Visual Reconstructions (if available) (Search “DreamNet AI dream decoding”). Some research teams have posted visual recreations of dreams using generative AI.

Additional References:

10. Neuroba – Using AI to Decode Dreams: A Look Into the Future

https://www.neuroba.com/post/using-ai-to-decode-dreams-a-look-into-the-future-neuroba

11. AI-Driven “Smart Dreams”: Can AI Influence What We Dream About?

https://www.oxaam.com/articles/ai-driven-smart-dreams-influence/

Music Credits:

1. Tension Rising by Aylex | https://freetouse.com/music/aylex

2. 'Meanwhile' by Scott Buckley - released under CC-BY 4.0. www.scottbuckley.com.au

3. Tech Live Kevin MacLeod (incompetech.com)

Licensed under Creative Commons: By Attribution 3.0 License

http://creativecommons.org/licenses/by/3.0/

This podcast is narrated by the host's own voice, powered by AI.

  continue reading

7 episodes

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