It’s the very first episode of The Big Pitch with Jimmy Carr and our first guest is Phil Wang! And Phil’s subgenre is…This Place is Evil. We’re talking psychological torture, we’re talking gory death scenes, we’re talking Lorraine Kelly?! The Big Pitch with Jimmy Carr is a brand new comedy podcast where each week a different celebrity guest pitches an idea for a film based on one of the SUPER niche sub-genres on Netflix. From ‘Steamy Crime Movies from the 1970s’ to ‘Australian Dysfunctional Family Comedies Starring A Strong Female Lead’, our celebrity guests will pitch their wacky plot, their dream cast, the marketing stunts, and everything in between. By the end of every episode, Jimmy Carr, Comedian by night / “Netflix Executive” by day, will decide whether the pitch is greenlit or condemned to development hell! Listen on all podcast platforms and watch on the Netflix Is A Joke YouTube Channel . The Big Pitch is a co-production by Netflix and BBC Studios Audio. Jimmy Carr is an award-winning stand-up comedian and writer, touring his brand-new show JIMMY CARR: LAUGHS FUNNY throughout the USA from May to November this year, as well as across the UK and Europe, before hitting Australia and New Zealand in early 2026. All info and tickets for the tour are available at JIMMYCARR.COM Production Coordinator: Becky Carewe-Jeffries Production Manager: Mabel Finnegan-Wright Editor: Stuart Reid Producer: Pete Strauss Executive Producer: Richard Morris Executive Producers for Netflix: Kathryn Huyghue, Erica Brady, and David Markowitz Set Design: Helen Coyston Studios: Tower Bridge Studios Make Up: Samantha Coughlan Cameras: Daniel Spencer Sound: Charlie Emery Branding: Tim Lane Photography: James Hole…
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Intro to Generative AI
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Inhalt bereitgestellt von wail. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von wail oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.
This podcast explores the cutting-edge world of generative AI, diving into various models and techniques used to create automated, high-quality content. Each episode will cover topics like natural language processing, voice synthesis, audio editing, and how AI can personalize and enhance the podcasting experience. Join us as we explore the future of podcast production powered by AI.
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Manage series 3601678
Inhalt bereitgestellt von wail. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von wail oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.
This podcast explores the cutting-edge world of generative AI, diving into various models and techniques used to create automated, high-quality content. Each episode will cover topics like natural language processing, voice synthesis, audio editing, and how AI can personalize and enhance the podcasting experience. Join us as we explore the future of podcast production powered by AI.
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In this episode, we dive deep into the world of fine-tuning AI language models, breaking down the processes and techniques behind optimizing models like Llama 2, Code Llama, and OpenHermes. We'll explore the critical role of high-quality instruction datasets and walk you through a step-by-step guide on fine-tuning Llama 2 using Google Colab. Learn about the key libraries, parameters, and how to go beyond notebooks with more advanced scripts. We also take a closer look at the fine-tuning of Code Llama with the Axolotl tool, covering everything from setting up a cloud-based GPU service to merging the trained model and uploading it to Hugging Face. Whether you're just starting with AI models or looking to level up your game, this episode has you covered. Finally, we'll explore Direct Preference Optimization (DPO), a cutting-edge technique that significantly improved the performance of OpenHermes-2.5. DPO, a variation of Reinforcement Learning from Human Feedback (RLHF), shows how preference data can help models generate more accurate and relevant answers. Tune in for practical insights, code snippets, and tips to help you explore and optimize AI models.…
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