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Localizing and Editing Knowledge in LLMs with Peter Hase - #679
Manage episode 411383461 series 2355587
Contenuto fornito da TWIML and Sam Charrington. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da TWIML and Sam Charrington o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.
Today we're joined by Peter Hase, a fifth-year PhD student at the University of North Carolina NLP lab. We discuss "scalable oversight", and the importance of developing a deeper understanding of how large neural networks make decisions. We learn how matrices are probed by interpretability researchers, and explore the two schools of thought regarding how LLMs store knowledge. Finally, we discuss the importance of deleting sensitive information from model weights, and how "easy-to-hard generalization" could increase the risk of releasing open-source foundation models.
The complete show notes for this episode can be found at twimlai.com/go/679.
778 episodi
Localizing and Editing Knowledge in LLMs with Peter Hase - #679
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Condividi
Manage episode 411383461 series 2355587
Contenuto fornito da TWIML and Sam Charrington. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da TWIML and Sam Charrington o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.
Today we're joined by Peter Hase, a fifth-year PhD student at the University of North Carolina NLP lab. We discuss "scalable oversight", and the importance of developing a deeper understanding of how large neural networks make decisions. We learn how matrices are probed by interpretability researchers, and explore the two schools of thought regarding how LLMs store knowledge. Finally, we discuss the importance of deleting sensitive information from model weights, and how "easy-to-hard generalization" could increase the risk of releasing open-source foundation models.
The complete show notes for this episode can be found at twimlai.com/go/679.
778 episodi
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Simile a The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
The Everyday AI podcast is a daily livestream, podcast and free newsletter where we help everyday people grow their careers with AI. The Everyday AI podcast is hosted by Jordan Wilson, a former journalist who's now the owner of a boutique digital strategy company with 20 years of martech experience. Our main focus is to help you keep up with AI trends to make your job easier. Get your work done faster. Increase your output. - Sign up for our free Prime Prompt Polish ChatGPT course: https://p ...
…
continue reading
Android Backstage, a podcast by and for Android developers. Hosted by developers from the Android engineering team, this show covers topics of interest to Android programmers, with in-depth discussions and interviews with engineers on the Android team at Google. Subscribe to Android Developers YouTube → https://goo.gle/AndroidDevs
…
continue reading
Redefining AI is a Three-Time Award-Winning Tech Podcast that cuts through the noise! Join Lauren Hawker Zafer, Chief Operating Officer at Squirro and Stevie Silver Award–winning creator, for a bold, thought-provoking exploration of artificial intelligence. Celebrated as intellectually rigorous, globally relevant, and truly unique, the show examines how AI shapes us socially, psychologically, and even physiologically. Each episode brings together leading academics, authors, executives, and i ...
…
continue reading
The Data Skeptic Podcast features interviews and discussion of topics related to data science, statistics, machine learning, artificial intelligence and the like, all from the perspective of applying critical thinking and the scientific method to evaluate the veracity of claims and efficacy of approaches.
…
continue reading
Every Friday and Sunday, Slate’s popular daily news podcast What Next brings you TBD, a clear-eyed look into the future. From fake news to fake meat, algorithms to augmented reality, Lizzie O’Leary is your guide to the tech industry and the world it’s creating for us to live in.
…
continue reading
Hanselminutes is Fresh Air for Developers. A weekly commute-time podcast that promotes fresh technology and fresh voices. Talk and Tech for Developers, Life-long Learners, and Technologists.
…
continue reading
TechStuff is getting a system update. Everything you love about Tech Stuff now twice the bandwidth with new hosts, Oz Woloshyn (Sleepwalkers) and Karah Preiss (Sleepwalkers). Oz and Karah bring humour and wit to the table as they break down what's happening in tech...and what it says about us. TechStuff is the podcast where technology meets culture. We speak to the folks building the future to understand what tomorrow will look like and how our technology is changing us: how we live, how we ...
…
continue reading
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continue reading
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…
continue reading
Discover what separates AI success from AI hype. In this series from MIT Sloan Management Review, AI winners share their secrets and success stories from the front lines. Explore the future of artificial intelligence with leaders from companies like YouTube, Cisco, and Hugging Face who are turning AI's potential into measurable business value.
…
continue reading
Player FM - App Podcast
Vai offline con l'app Player FM !
Vai offline con l'app Player FM !
