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Stable Diffusion Podcasts

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Machine learning audio course, teaching the fundamentals of machine learning and artificial intelligence. It covers intuition, models (shallow and deep), math, languages, frameworks, etc. Where your other ML resources provide the trees, I provide the forest. Consider MLG your syllabus, with highly-curated resources for each episode's details at ocdevel.com. Audio is a great supplement during exercise, commute, chores, etc.
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Join us as we embark on a captivating journey through the ever-evolving intersection of AI, data, and architecture. In this podcast, we dive deep into the vast potential of AI for architecture and design, examining the remarkable possibilities it offers, while also acknowledging the challenges it presents. Our mission is to expand the conversation, engaging with leaders, thinkers, and doers in the ecosystem. We invite them to share their profound insights, groundbreaking ideas, and innovativ ...
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Learn to write effective prompts for ChatGPT, Bard, Midjourney, DALLE, and other AI systems. Also hosting bi-weekly prompt engineering masterminds, where you bring a prompt and we all colaborate to improve it. Each episode we explore prompting techniques, interviews with experts and newbies, and tips on selling your prompts. Released weekly! Let me know who you'd like me to interview at PromptEngineeringPodcast.com Keep in touch: - https://www.linkedin.com/groups/14231334/ - https://t.me/Pro ...
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Become a Paid Subscriber: https://podcasters.spotify.com/pod/show/rebeltech/subscribe Welcome to my Rebel Rant Series podcast! Join me as I dive into topics that matter, and share my unfiltered thoughts and opinions. This podcast is a different side of me, separate from my YouTube videos that I upload. It's raw, it's real, and it's here to inspire and motivate. In this podcast, I'll be sharing never-before-seen footage and insights into my life, as well as discussing topics ranging from busi ...
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Knowledge Distillation is the podcast that brings together a mixture of experts from across the Artificial Intelligence community. We talk to the world’s leading researchers about their experiences developing cutting-edge models as well as the technologists taking AI tools out of the lab and turning them into commercial products and services. Knowledge Distillation also takes a critical look at the impact of artificial intelligence on society – opting for expert analysis instead of hysterica ...
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Google Veo leads the generative video market with superior 4K photorealism and integrated audio, an advantage derived from its YouTube training data. OpenAI Sora is the top tool for narrative storytelling, while Kuaishou Kling excels at animating static images with realistic, high-speed motion. Links Notes and resources at ocdevel.com/mlg/mla-26 Tr…
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The AI image market has split: Midjourney creates the highest quality artistic images but fails at text and precision. For business use, OpenAI's GPT-4o offers the best conversational control, while Adobe Firefly provides the strongest commercial safety from its exclusively licensed training data. Links Notes and resources at ocdevel.com/mlg/mla-25…
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Luc Izri — architect, theorist, and co-founder of Inflexion Dynamics — joins us to explore the evolving relationship between computation and design thinking. With a deep background in algorithmic and topological design education, Luc brings a fresh perspective on how AI is transforming not only architectural practice, but the way we teach and learn…
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 It's been a while since I've released an episode. I'm heading to the AI Engineer World's Fair tomorrowv If you're going to be there, I am going to be wearing a Superman shirt, so come say hi! I would love to talk to listeners and hear how your prompting journey has been going. I'm also planning on restarting the podcast, with one of a couple diffe…
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Auto encoders are neural networks that compress data into a smaller "code," enabling dimensionality reduction, data cleaning, and lossy compression by reconstructing original inputs from this code. Advanced auto encoder types, such as denoising, sparse, and variational auto encoders, extend these concepts for applications in generative modeling, in…
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🔍 In this TL;DR episode, Anna and Nate unpack why calling AI outputs “hallucinations” misses the mark—and introduce “AI Mirage” as a sharper, more accurate metaphor. From scoring alternative terms to sparking social media debates, they show how language shapes our assumptions, trust, and agency in the age of generative AI. The takeaway: choosing th…
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🔍 In this TL;DR episode, Emmie Hine (Yale Digital Ethics Center) makes the case for Europe’s leadership in open-source AI—thanks to strong infrastructure, multilingual data, and regulatory clarity. With six key policy recommendations, the message is clear: trust and transparency can make EU models globally competitive. 📌 TL;DR Highlights ⏲️[00:00] …
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At inference, large language models use in-context learning with zero-, one-, or few-shot examples to perform new tasks without weight updates, and can be grounded with Retrieval Augmented Generation (RAG) by embedding documents into vector databases for real-time factual lookup using cosine similarity. LLM agents autonomously plan, act, and use ex…
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Explains language models (LLMs) advancements. Scaling laws - the relationships among model size, data size, and compute - and how emergent abilities such as in-context learning, multi-step reasoning, and instruction following arise once certain scaling thresholds are crossed. The evolution of the transformer architecture with Mixture of Experts (Mo…
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In this episode, we’re joined by Roey Granot, co-founder of QBIQ, a trailblazing company using artificial intelligence to transform how we design and plan spaces. QBIQ’s platform allows brokers, landlords, architects, and tenants to generate instant, customized layout plans and immersive 3D tours—redefining workflows across real estate and architec…
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🔍 In this TL;DR episode, Milton Mueller (the Georgia Institute of Technology School of Public Policy) argues that what we call “AI” is really just part of a broader digital ecosystem. Instead of vague, top-down AI regulation, he calls for context-specific rules that address actual uses—like facial recognition or medical diagnostics—rather than the …
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Tool use in code AI agents allows for both in-editor code completion and agent-driven file and command actions, while the Model Context Protocol (MCP) standardizes how these agents communicate with external and internal tools. MCP integration broadens the automation capabilities for developers and machine learning engineers by enabling access to a …
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Gemini 2.5 Pro currently leads in both accuracy and cost-effectiveness among code-focused large language models, with Claude 3.7 and a DeepSeek R1/Claude 3.5 combination also performing well in specific modes. Using local open source models via tools like Ollama offers enhanced privacy but trades off model performance, and advanced workflows like c…
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🔍 In this TL;DR episode, Kevin Frazier (University of Texas at Austin school of Law) outlines a proposal to realign U.S. copyright law with its original goal of spreading knowledge. The discussion introduces three key reforms—an AI training presumption, research safe harbors, and data commons—to help innovators access data more easily. By reducing …
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🔍 In this TL;DR episode, Paul Keller (The Open Future Foundation) outlines a proposal for a common opt-out vocabulary to improve how EU copyright rules apply to AI training. The discussion introduces three clear use cases—TDM, AI training, and generative AI training—to help rights holders express their preferences more precisely. By standardizing t…
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🔍 In this TL;DR episode, João Quintais (Institute for Information Law) explains the interaction between the AI Act and EU copyright law, focusing on text and data mining (TDM). He unpacks key issues like lawful access, opt-out mechanisms, and transparency obligations for AI developers. João explores challenges such as extraterritoriality and trade …
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🔍 In this TL;DR episode, Anna Tumadóttir (Creative Commons) discusses how the evolution of creator consent and AI has reshaped perspectives on openness, highlighting the challenges of balancing creator choice with the risks of misuse. Examines the limitations of blunt opt-out mechanisms like those in the EU AI Act, the implications for marginalized…
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Vibe coding is using large language models within IDEs or plugins to generate, edit, and review code, and has recently become a prominent and evolving technique in software and machine learning engineering. The episode outlines a comparison of current code AI tools - such as Cursor, Copilot, Windsurf, Cline, Roo Code, and Aider - explaining their a…
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Links: Notes and resources at ocdevel.com/mlg/33 3Blue1Brown videos: https://3blue1brown.com/ Try a walking desk stay healthy & sharp while you learn & code Try Descript audio/video editing with AI power-tools Background & Motivation RNN Limitations: Sequential processing prevents full parallelization—even with attention tweaks—making them ineffici…
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🔍 In this TL;DR episode, Carys J Craig (Osgoode Professional Development) explains the "copyright trap" in AI regulation, where relying on copyright favors corporate interests over creativity. She challenges misconceptions about copying and property rights, showing how this approach harms innovation and access. Carys offers alternative ways to prot…
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🔍 In this TL;DR episode, Ariadna Matas (Europeana Foundation) discusses how the 2019 Copyright Directive has influenced text and data mining practices in cultural heritage institutions, highlighting the tension between public interest missions and restrictive approaches, and explores the broader implications of opt-outs on access, research, and the…
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🔍 In this TL;DR episode, Martin Senftleben (Institute for Information Law (IViR) & University of Amsterdam) discusses how EU regulations, including the AI Act and copyright frameworks, impose heavy burdens on AI training and development. The discussion highlights concerns about bias, quality, and fairness due to opt-outs and complex rights manageme…
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🔍 In this TL;DR episode, Mark Lemley (Stanford Law School) discusses how generative AI challenges traditional copyright doctrines, such as the idea-expression dichotomy and substantial similarity test, and explores the evolving role of human creativity in the age of AI. 📌 TL;DR Highlights ⏲️[00:00] Intro ⏲️[00:54] Q1-How does genAI challenge tradit…
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🔍 In this TL;DR episode, Jacob Mchangama (The Future of Free Speech & Vanderbilt University) discusses the high rate of AI chatbot refusals to generate content for controversial prompts, examining how this may conflict with the principles of free speech and access to diverse information. 📌 TL;DR Highlights ⏲️[00:00] Intro ⏲️[00:51] Q1-How does the …
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In the rapidly evolving world of AI, one of the most pressing questions is: Can AI models truly unlearn? As AI becomes more integrated into our daily lives, ensuring healthier, bias-free models is crucial. In this episode, we dive deep into a groundbreaking approach—machine unlearning—with Ben Louria, founder of Hirundo. His platform tackles one of…
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🔍 In this TL;DR episode, Jurgen Gravestein (Conversation Design Institute) discusses his Substack blog post delving into the ‘Intelligence Paradox’ with the AI lab 📌 TL;DR Highlights ⏲️[00:00] Intro ⏲️[01:08] Q1-The ‘Intelligence Paradox’: How does the language used to describe AI lead to misconceptions and the so-called ‘Intelligence Paradox’? ⏲️[…
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🔍 In this TL;DR episode, Dr. Stefaan G. Verhulst (The GovLab & The Data Tank) discusses his Frontiers Policy Labs contribution on the urgent need to preserve data access for the public interest with the AI lab 📌 TL;DR Highlights ⏲️[00:00] Intro ⏲️[01:13] Q1-‘Data Winter’: Can you provide a brief overview of your concept of 'Data Winter' and why you…
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Let’s talk about AI tokenization in this third episode of our AI in Action series. Tokenization is actually pretty interesting, especially if you ever wondered how these fancy AI machines understand the stuff we type and say and produce things when we give them prompts. Next time you're marvelling at an AI-generated text, remember it's all about th…
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In this episode, we’re joined by Husain Al Asfoor, founder of Ebinaa, a platform dedicated to streamlining relationships throughout the real-estate journey. Husain has been at the forefront of digitizing the design and construction industry, with a deep focus on enhancing the flow of information across the real estate sector. His insights on how da…
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🔍 In this TL;DR episode, Dr. Bertin Martens (Bruegel) discusses his working paper for the Brussels-based economic think tank on the economic arguments in favour of reducing copyright protection for generative AI inputs and outputs with the AI lab * 9:44: Mr Martens intended to say "humans" instead of machines 📌 TL;DR Highlights ⏲️[00:00] Intro ⏲️[0…
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In this experimental episode of the Rebel Rant Series, I sit down with the renowned Silicon Valley realtor and entrepreneur, Charlie Giang, for a candid and unfiltered conversation. We dive deep into the world of AI, explore the future of real estate and content creation, and share some hilarious stories along the way.This isn't your typical podcas…
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Get ready for a raw, uncensored and real conversation! We're kicking off Season 2 of the Rebel Rant Series with a bang! Our first guest is none other than Richard, the Global Marketing Director of @enyamusicglobal Dive deep into the world of music, tech, and entrepreneurship as we explore ENYA Music's journey, their innovative products like the Nov…
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🔍 In this TL;DR episode, Prof. Dr. Alexander Peukert (Goethe University Frankfurt am Main) discusses his primer on copyright in the EU AI Act with the AI lab 📌 TL;DR Highlights ⏲️[00:00] Intro ⏲️[01:26] Q1-Merging copyright & AI regulation: What challenges arise from merging copyright law and AI regulation? How might this impact legislation, compli…
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🔍 In this TL;DR episode, Professor Thomas Margoni (CiTiP - Centre for IT & IP Law, KU Leuven) discusses copyright law and the lifecycle of machine learning models with the AI lab. The starting point is an article co-authored with Professor Martin Kretschmer (CREATe, University of Glasgow) and Dr Pinar Oruç (University of Manchester), and published …
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Let’s talk about AI terminology in the second episode in our AI in Action series. The AI term gets thrown around more than a beach ball at a summer picnic, and it’s not always clear what people are talking about. “AI” is to tech what “food” is to a grocery store – sure, it covers a lot, but a hot dog and a filet mignon are pretty darn different whe…
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🔍 In this TL;DR episode, Dr Elisa Giomi, Associate Professor at the Roma Tre University and Commissioner of the Italian Communications Regulatory Authority (AGCOM), discusses her recent contribution on Intermedia, the journal of the International Institute of Communications (IIC), titled “The (almost) unacknowledged revolution of AI in the media an…
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We are delighted to present another thought-provoking episode exploring the critical topics of accountability and responsibility in Artificial Intelligence within the creative industries. In this episode, we are honored to welcome Vered Horesh from Bria AI, a visionary in the field of AI. Vered shares the journey and mission of Bria AI, emphasizing…
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🔍 In this TL;DR episode, Derek Slater (Proteus Strategies) discusses his recent blog post on the Tech Policy Press website, titled “What the Copyright Case Against Ed Sheeran Can Teach Us About AI”, with the AI lab 📌 TL;DR Highlights ⏲️[00:00] Intro ⏲️[01:11] Q1 - Legal boundaries & creativity: How to define the boundary between protectable express…
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We are kickstarting our AI in Action series by diving headfirst into the key milestones that led to the gradual deployment of Artificial Intelligence, or AI for short. You might think it's some shiny new invention, looking at all the recent media coverage about robots taking over your jobs and writing bad poetry. But hold on to your Roomba, because…
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We are thrilled to bring you an insightful episode that dives deep into the pressing issues of accountability and responsibility in the realm of Artificial Intelligence within the creative industries. Introduction by Dyann Heward-Mills: The EU AI Act To set the framework, we have the honor of welcoming Dyann Heward-Mills:, an esteemed expert in AI …
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🔍 In this TL;DR episode, Professor Žiga Turk (University of Ljubljana, Slovenia) discusses his recent contribution for the Wilfried Martens Centre for European Studies on how “Brussels is About to Protect Citizens from Intelligence” with the AI lab 📌 TL;DR Highlights ⏲️[00:00] Intro ⏲️[01:55] Q1 - Why do you think AI regulation prioritises limiting…
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Emily Mackevicius is a co-founder and director of Basis, a nonprofit applied research organization focused on understanding and building intelligence while advancing society’s ability to solve intractable problems. Emily is a member of the Simons Society of Fellows, and a postdoc in the Aronov lab and the Center for Theoretical Neuroscience at Colu…
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Stability AI’s Stable Diffusion model is one of the best known and most widely used text-to-image systems. The decision to open-source both the model weights and code has ensured its mass adoption, with the company claiming more than 330 million downloads. Details of the latest version - Stable Diffusion 3 - were revealed in a paper, published by t…
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🔥 In this 'Hot Item', MEP Axel Voss (Germany, EPP) & the AI lab discuss his intentions to bring the creative industry and AI developers around the table in mid-April for a first exchange to gain a better understanding of the issues perceived on both sides 📌 Hot Item Highlights ⏲️[00:00] Intro ⏲️[00:53] MEP Axel Voss (Germany, EPP) ⏲️[09:51] Wrap-up…
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In this episode, we're joined by Florian Schneider, a prominent figure navigating the intersections of art, technology, and documentary practices. As a filmmaker, writer, curator, and esteemed Professor at NTNU, Florian has spearheaded groundbreaking discussions on the role of artificial intelligence (AI) in reshaping creativity and ownership acros…
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🔍 In this TL;DR episode, Assistant Professor Nuno Sousa e Silva (Universidade Católica Portuguesa) discusses his recent Kluwer Copyright Blog contribution, “Are AI Models’ Weights Protected Databases?”, with the AI lab. 📌 TL;DR Highlights ⏲️[00:00] Intro ⏲️[01:41] Q1 - What are weights in an AI model? ⏲️[05:14] Q2 - Why could the EU Database Direct…
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No organisation in the AI world is under more intense scrutiny than OpenAI. The maker of Dall-E, GPT4, ChatGPT and Sora is constantly pushing the boundaries of artificial intelligence and has supercharged the enthusiasm of the general public for AI technologies. With that elevated position come questions about how OpenAI can ensure its models are n…
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Jeff and Seymour kick off 2024 with a discussion of the three phases of generative AI. Phase 1: The launch of ChatGPT in November, 2022. Phase 2: The rise and fall of AI wrapper companies during early- to mid-2023. Phase 3: The current emergence of AI Agents that can automatically chain together multiple steps that drastically change the kinds of p…
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In this episode, we welcome Mohammed Almahmood to explore the intersection of artificial intelligence (AI) and urbanism. With over 15 years of experience and a passion for creating human-centric public spaces, Mohammed provides a critical insight into how AI is transforming urban design. We discuss the impact of AI on data collection, simulation mo…
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Nina Schick is a leading commentator on Artificial Intelligence and its impact on business, geopolitics and humanity. Her book ‘Deepfakes and the Infocalypse’ charts the early use of gen AI to create deepfake pornography and the technology’s subsequent use as a tool of political manipulation. With over two decades of geopolitical experience, Nina h…
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