Breaking Math Podcast

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 OpenAI's Sora is a groundbreaking text-to-video model that can generate realistic and imaginative scenes based on text prompts. Sora has the potential to revolutionize various industries, including entertainment, advertising, and education. While Sora's capabilities are impressive, there are limitations and safety concerns, such as the potential for misuse and the need for robust verification methods. The conversation highlights the importance of understanding the ethical implications of AI and the need for ongoing research and development in the field.Chapters00:00 Introduction to OpenAI's Sora04:22 Overview of Sora's Capabilities07:08 Exploring Prompts and Generated Videos12:20 Technical Details of Sora16:33 Limitations and Safety Concerns23:10 Examples of Glitches in Generated Videos26:04 Impressive Videos Generated by Sora29:09 AI Fraud and Impersonation35:41 Future of Physics-Informed Modeling36:25 Conclusion and Call to ActionHelp Support The Podcast by clicking on the links below: Start YOUR podcast on ZenCastr!    Use my special link  ZenCastr Discount to save 30% off your first month of any Zencastr paid plan Visit our PatreonContact us at breakingmathpodcast@gmail.comSummary#OpenAiSora #

Help Support The Podcast by clicking on the links below: Try out ZenCastr w/ 30% Discount   Use my special link to save 30% off your first month of any Zencastr paid plan Patreon YouTubeTranscripts are available upon request. Email us at BreakingMathPodcast@gmail.comFollow us on X (Twitter)Follow us on Social Media Pages (Linktree)Visit our guest Levi McClain's Pages: youtube.com/@LeviMcClainlevimcclain.com/SummaryLevi 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: The perception of scary sounds can be analyzed from different perspectives, including composition techniques, acoustic properties, neuroscience, and psychology. Approaching art and music with a technical mind can lead to unique and innovative creations. Sonifying data allows for the exploration of different ways to express information through sound. Microtonal tuning expands the possibilities of harmony and offers new avenues for musical expression. Creating instruments and using unconventional techniques can push the boundaries of traditional music-making. Understanding consonance and dissonance is a complex topic that varies across cultures and musical traditions. Programming artificial intelligence to understand consonance and dissonance requires a deeper understanding of human perception and cultural context.Chapters00:00 What Makes a Sound Scary03:00 Approaching Art and Music with a Technical Mind05:19 Sonifying Data and Turning it into Sound08:39 Exploring Music with Microtonal Tuning15:44 The Impact of Using 31 Notes per Octave17:37 Why 31 Notes Instead of Any Other Arbitrary Number19:53 Creating Instruments for Microtonal Music21:25 Using Unconventional Techniques to Make Music23:06 Closing Remarks and Questions24:03 Understanding Consonance and Dissonance25:25 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 BreakingMathPodcast@gmail.com.  For more in depth discussions on these topics and more, check out Levi's channels at: Patreon.com/LeviMcClainyoutube.com/@LeviMcClainTiktok.com/@levimcclainInstagram.com/levimcclainmusicHelp Support The Podcast by clicking on the links below: Start YOUR podcast on ZenCastr!   Use my special link  ZenCastr Discount to save 30% off your first month of any Zencastr paid plan Visit our Patreon

Help Support The Podcast by clicking on the links below: Start YOUR podcast on ZenCastr!   Use my special link  ZenCastr Discount to save 30% off your first month of any Zencastr paid plan Visit our PatreonPart 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 CruiseTranscript will be made available soon! Stay tuned. You may receive a transcript by emailing us at breakingmathpodcast@gmail.com.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.Help Support The Podcast by clicking on the links below: Start YOUR podcast on ZenCastr!   Use my special link  ZenCastr Discount to save 30% off your first month of any Zencastr paid plan Visit our Patreon

Transcripts of this episode are avialable upon request.  Email us at BreakingMathPodcast@gmail.com. In this episode Gabriel Hesch interviews Taylor Sparks, a professor of material science and engineering, about his recent paper on the use of generative modeling a.i. for material disovery.  The paper is published in the journal Digital Discovery and is titled 'Generative Adversarial Networks and Diffusion MOdels in Material Discovery. They discuss the purpose of the call, the process of generative modeling, creating a representation for materials, using image-based generative models, and a comparison with Google's approach. They also touch on the concept of conditional generation of materials, the importance of open-source resources and collaboration, and the exciting developments in materials and AI. The conversation concludes with a discussion on future collaboration opportunities.Takeaways Generative modeling is an exciting approach in materials science that allows for the prediction and creation of new materials. Creating a representation for materials, such as using the crystallographic information file, enables the application of image-based generative models. Google's approach to generative modeling received attention but also criticism for its lack of novelty and unconditioned generation of materials. Open-source resources and collaboration are crucial in advancing materials informatics and machine learning in the field of materials science.Help Support The Podcast by clicking on the links below: Start YOUR podcast on ZenCastr!   Use my special link  ZenCastr Discount to save 30% off your first month of any Zencastr paid plan Visit our PatreonHow is Machine Learning being used to further original scientific discoveries?  

In October of 2023, Sofia Baca passed away unexpectedly from natural causes. Sofia was one of the founders and cohosts of the Breaking Math Podcast. In this episode, host Gabriel Hesch interviews Diane Baca, mother of Sofia Baca as we talk about her passions for creativity, mathematics, science, and discovering what it means to be human. Sofia lived an exceptional life with explosive creativity, a voracious passion for mathematics, physics, computer science, and creativity. Sofia also struggled immensely with mental health issues which included substance abuse as well as struggling for a very long time understand the source of their discontent. Sofia found great happiness in connecting with other people through teaching, tutoring, and creative expression. The podcast will continue in honor of Sofia. There are many folders of ideas that Sofia left with ideas for the show or for other projects. We will continue this show with sharing some of these ideas, but also with sharing stories of Sofia - including her ideas and her struggles in hopes that others may find solace in that they are not alone in their struggles. But also in hopes that others may find inspiration in what Sofia had to offer. We miss you dearly, Sofia.

Join Sofía Baca and her guests, the host and co-host of the Nerd Forensics podcast, Millicent Oriana and Jacob Urban, as they explore what it means to be able to solve one problem in multiple ways.This episode is distributed under a Creative Commons Attribution-ShareAlike 4.0 International License. For full text, visit: https://creativecommons.org/licenses/by-sa/4.0/[Featuring: Sofía Baca; Millicent Oriana, Jacob Urban[Help Support The Podcast by clicking on the links below: Try out ZenCastr w/ 30% DiscountUse my special link to save 30% off your first month of any Zencastr paid plan Patreon YouTube Breaking Math WebsiteEmail us for copies of the transcript!

The podcast explores the concept of units, dimensions, and variables in mathematics, discussing their use for counting and measuring tangible and abstract things. It also delves into the conversion between units of measurement and the manipulation of numbers, the evolution of measurement systems, the contamination of Biscayne Bay, the application of the Buckingham Pi theorem, and the utility of dimensional analysis in simplifying complex physical problems.

Help Support The Podcast by clicking on the links below: Try out ZenCastr w/ 30% DiscountUse my special link to save 30% off your first month of any Zencastr paid plan Patreon YouTube Breaking Math WebsiteEmail us for copies of the transcript!Join Sofia Baca and Nerd Forensics co-host Jacob Urban as they discuss all things counting!Counting is the first arithmetic concept we learn, and we typically learn to do so during early childhood. Counting is the basis of arithmetic. Before people could manipulate numbers, numbers had to exist. Counting was first done on the body, before it was done on apparatuses outside the body such as clay tablets and hard drives. However, counting has become an invaluable tool in mathematics itself, as became apparent when counting started to be examined analytically. How did counting begin? What is the study of combinatorics? And what can be counted? All of this and more, on this episode of Breaking Math.This episode is distributed under a Creative Commons Attribution-ShareAlike 4.0 International License (full text: https://creativecommons.org/licenses/by-sa/4.0/)[Featuring: Sofia Baca; Jacob Urban]