Breaking Math is a podcast that aims to make math accessible to everyone, and make it enjoyable. Every other week, topics such as chaos theory, forbidden formulas, and more will be covered in detail. If you have 45 or so minutes to spare, you're...
Summary: The episode discusses the 10,000 year dilemma, which is a thought experiment on how to deal with nuclear waste in the future. Today's episode is hosted by guest host David Gibson, who is the founder of the Ray Kitty Creation Workshop. (Find out more about the Ray Kitty Creation Workshop by clicking here).
Gabriel and Autumn are out this week, but will be returning in short order with 3 separate interviews with authors of some fantastic popular science and math books including:
An interview with Prof. Marcus du Sautoy about his book Around the Wold in Eighty Games . . . .a Mathematician Unlocks the Secrets of the World's Greatest Games.
Topics covered in Today's Episode:
1. Introduction to Professor Marcus du Sautoy and the Role of Games
- Impact of games on culture, strategy, and learning
- The educational importance of games throughout history
2. Differences in gaming cultures across regions like India and China
3. Creative Aspects of Mathematics
4. The surprising historical elements and banned games by Buddha
5. Historical and geographical narratives of games rather than rules
6. Game Theory and Education
7. Unknowable questions like thermodynamics and universe's infinity
8. Professor du Sautoy's Former Books and Collections
9. A preview of his previous books and their themes
10. Gaming Cultures and NFTs in Blockchain
11. Gamification in Education
12. The Role of AI in Gaming
13. Testing machine learning in mastering games like Go
14. Alphago's surprising move and its impact on Go strategies
15 . The future of AI in developing video game characters, plots, and environments
16. Conclusion and Giveaway Announcement
*Free Book Giveaway of Around The World in 88 Games . . . by Professor Marcus Du Sautory! Follow us on our socials for details:
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Summary
Brain Organelles, A.I. and Defining Intelligence in Nature-
In this episode, we continue our fascinating interview with GT, a science content creator on TikTok and YouTube known for their captivating - and sometimes disturbing science content.
GT can be found on the handle ‘@bearBaitOfficial’ on most social media channels.
In this episode, we resume our discussion on Brain Organelles - which are grown from human stem cells - how they are being used to learn about disease, how they may be integrated in A.I. as well as eithical concerns with them.
We also ponder what constitutes intelligence in nature, and even touch on the potential risks of AI behaving nefariously.
You won't want to miss this thought-provoking and engaging discussion.
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This episode is inspired by a correspondence the Breaking Math Podcast had with the editors of Digital Discovery, a journal by the Royal Society of Chemistry. In this episode the hosts review a paper about how the Lean Interactive Theorem Prover, which is usually used as a tool in creating mathemtics proofs, can be used to create rigorous and robust models in physics and chemistry.
Also - we have a brand new member of the Breaking Math Team! This episode is the debut episode for Autumn, CEO of Cosmo Labs, occasional co-host / host of the Breaking Math Podcast, and overall contributor who has been working behind the scenes on the podcast on branding and content for the last several months. Welcome Autumn!
Autumn and Gabe discuss how the paper explores the use of interactive theorem provers to ensure the accuracy of scientific theories and make them machine-readable. The episode discusses the limitations and potential of interactive theorem provers and highlights the themes of precision and formal verification in scientific knowledge. This episode also provide resources (listed below) for listeners interested in learning more about working with the LEAN interactive theorem prover.
Takeaways
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This conversation explores the topic of brain organoids and their integration with robots. The discussion covers the development and capabilities of brain organoids, the ethical implications of their use, and the differences between sentience and consciousness. The conversation also delves into the efficiency of human neural networks compared to artificial neural networks, the presence of sleep in brain organoids, and the potential for genetic memories in these structures. The episode concludes with an invitation to part two of the interview and a mention of the podcast's Patreon offering a commercial-free version of the episode.
Takeaways
Chapters
References:
Muotri Labs (Brain Organelle piloting Spider Robot)
Cortical Labs (Brain Organelle's trained to play Pong)
*For a copy of the episode transcript, email us at [email protected]
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Summary:
This is a follow up on our previous episode on OpenAi's SORA. We attempt to answer the question, "Can OpenAi's SORA model real-world physics?"
We go over the details of the technical report, we discuss some controversial opinoins by experts in the field at Nvdia and Google's Deep Mind.
The transcript for episode is avialable below upon request.
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OpenAI's Sora, a text-to-video model, has the ability to generate realistic and imaginative scenes based on text prompts. This conversation explores the capabilities, limitations, and safety concerns of Sora. It showcases various examples of videos generated by Sora, including pirate ships battling in a cup of coffee, woolly mammoths in a snowy meadow, and golden retriever puppies playing in the snow. The conversation also discusses the technical details of Sora, such as its use of diffusion and transformer models. Additionally, it highlights the potential risks of AI fraud and impersonation. The episode concludes with a look at the future of physics-informed modeling and a call to action for listeners to engage with Breaking Math content.
Takeaways
Chapters
00:00 Introduction to OpenAI's Sora
04:22 Overview of Sora's Capabilities
07:08 Exploring Prompts and Generated Videos
12:20 Technical Details of Sora
16:33 Limitations and Safety Concerns
23:10 Examples of Glitches in Generated Videos
26:04 Impressive Videos Generated by Sora
29:09 AI Fraud and Impersonation
35:41 Future of Physics-Informed Modeling
36:25 Conclusion and Call to Action
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Contact us at [email protected]
Summary
#OpenAiSora #
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Transcripts are available upon request. Email us at [email protected]
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Visit our guest Levi McClain's Pages:
Summary
Levi McClean discusses various topics related to music, sound, and artificial intelligence. He explores what makes a sound scary, the intersection of art and technology, sonifying data, microtonal tuning, and the impact of using 31 notes per octave. Levi also talks about creating instruments for microtonal music and using unconventional techniques to make music. The conversation concludes with a discussion on understanding consonance and dissonance and the challenges of programming artificial intelligence to perceive sound like humans do.
Takeaways:
Chapters
00:00 What Makes a Sound Scary
03:00 Approaching Art and Music with a Technical Mind
05:19 Sonifying Data and Turning it into Sound
08:39 Exploring Music with Microtonal Tuning
15:44 The Impact of Using 31 Notes per Octave
17:37 Why 31 Notes Instead of Any Other Arbitrary Number
19:53 Creating Instruments for Microtonal Music
21:25 Using Unconventional Techniques to Make Music
23:06 Closing Remarks and Questions
24:03 Understanding Consonance and Dissonance
25:25 Programming Artificial Intelligence to Understand Consonance and Dissonance
We are joined today by content creator Levi McClain to discuss the mathematics behind music theory, neuroscience, and human experiences such as fear as they relate to audio processing.
For a copy of the episode transcript, email us at [email protected].
For more in depth discussions on these topics and more, check out Levi's channels at:
Instagram.com/levimcclainmusic
Help Support The Podcast by clicking on the links below:
Help Support The Podcast by clicking on the links below:
Part 2/2 of the interview with Brit Cruise, creator of the YouTube channel "Art of the Problem," about interesting mathematics,, electrical and computer engineering problems.
In Part 1, we explored what 'intelligence' may be defined as by looking for examples of brains and proto-brains found in nature (including mold, bacteria, fungus, insects, fish, reptiles, and mammals).
In Part 2, we discuss aritifical neural nets and how they are both similar different from human brains, as well as the ever decreasing gap between the two.
Brit's YoutTube Channel can be found here: Art of the Problem - Brit Cruise
Transcript will be made available soon! Stay tuned. You may receive a transcript by emailing us at [email protected].
Become a supporter of this podcast: https://www.spreaker.com/podcast/breaking-math-podcast--5545277/support.
In this episode (part 1 of 2), I interview Brit Cruise, creator of the YouTube channel 'Art of the Problem.' On his channel, he recently released the video "ChatGPT: 30 Year History | How AI learned to talk." We discuss examples of intelligence in nature and what is required in order for a brain to evolve at the most basic level. We use these concepts to discuss what artificial intelligence - such as Chat GPT - both is and is not.
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