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  • Mewgenics Is Out, And It Only Took 14 Years (with Edmund McMillen)

    12 FEB

    1

    Mewgenics Is Out, And It Only Took 14 Years (with Edmund McMillen)

    Jason, Kirk, and Maddy bring on veteran game designer Edmund McMillen (Binding of Isaac, Super Meat Boy) to talk about his latest game, Mewgenics, which was first announced in 2012 (!) and is out this week. They talk about the long development cycle, why McMillen parted ways with his Team Meat partner Tommy Refenes, breeding cats, and much much more. One More Thing: Kirk: Cairn Maddy: Code 3 (2025) Jason: The Chair Company (HBO) 🚀  SUPPORT TRIPLE CLICK:Join Maximum Fun | Buy TC Merch 💬 JOIN THE TRIPLE CLICK DISCORD 🎮 Triple Click Ethics Policy 📱 SOCIALS | @tripleclickpodInstagram | YouTube | TikTok | Twitch

    12 Feb

    •
    1h 23m
  • AI Safety in Generative AI with Peter Norvig

    30/06/2023

    2

    AI Safety in Generative AI with Peter Norvig

    On this episode, we’re joined by Peter Norvig, a Distinguished Education Fellow at the Stanford Institute for Human-Centered AI and co-author of popular books on AI, including Artificial Intelligence: A Modern Approach and more recently, Data Science in Context. AI has the potential to improve humanity’s quality of life and day-to-day decisions. However, these advancements come with their own challenges that can cause harm. Listen to this episode to learn considerations and best practices organizations can take to preserve human control and ensure transparent and equitable AI.

    30/06/2023

    •
    40 min
  • IA e empregos. Onde as empresas estao errando

    6 DAYS AGO

    3

    IA e empregos. Onde as empresas estao errando

    Lideranças corporativas em todos os países já dizem que pretendem reduzir a contratação de profissionais em início de carreira por causa da IA e dos seus agentes. Mas essa decisão pode estar profundamente errada. Cortar cargos júnior por causa da IA pode custar muito caro no médio prazo. Quem vai pagar essa conta quando ela chegar? Para essa conversa, convidamos Emerson Pinha, CEO da AI Tour Links do episódio A página do LinkedIn de Emerson Pinha O site da AI Tour O artigo "The Problem in the Age of AI Isn’t Young Talent: It’s Leadership", de Emerson Pinha O livro "The Shallows: What the Internet Is Doing to Our Brains", de Nicholas Carr A série "Custe o que Custar", da Netflix, baseada em um livro de Harlan Coben O relatório "AI and the Future of Learning", publicado por Ben Gomes, Lila Ibrahim, Yossi Matias, Christopher Phillips e James Manyika, do Google O livro "Who's Afraid of Ai?: Fear and Promise in the Age of Thinking Machines", de Thomas Ramge     A The Shift é uma plataforma de conteúdo que descomplica os contextos da inovação disruptiva e da economia digital. Visite o site www.theshift.info e assine a newsletter

    6 days ago

    •
    1h 6m
  • MLG 009 Deep Learning

    SEASON 1, EPISODE 9

    4

    MLG 009 Deep Learning

    Try a walking desk to stay healthy while you study or work! Full notes at ocdevel.com/mlg/9  Key Concepts: Deep Learning vs. Shallow Learning: Machine learning is broken down hierarchically into AI, ML, and subfields like supervised/unsupervised learning. Deep learning is a specialized area within supervised learning distinct from shallow learning algorithms like linear regression. Neural Networks: Central to deep learning, artificial neural networks include models like multilayer perceptrons (MLPs), convolutional neural networks (CNNs), and recurrent neural networks (RNNs). Neural networks are composed of interconnected units or "neurons," which are mathematical representations inspired by biological neurons. Unique Features of Neural Networks: Feature Learning: Neural networks learn to combine input features optimally, enabling them to address complex non-linear problems where traditional algorithms fall short. Hierarchical Representation: Data can be processed hierarchically through multiple layers, breaking down inputs into simpler components that can be reassembled to solve complex tasks. Applications: Medical Cost Estimation: Neural networks can handle non-linear complexities such as feature interactions, e.g., age, smoking, obesity, impacting medical costs. Image Recognition: Neural networks leverage hierarchical data processing to discern patterns such as lines and edges, building up to recognizing complex structures like human faces. Computational Considerations: Cost of Deep Learning: Deep learning's computational requirements make it expensive and resource-intensive compared to shallow learning algorithms. It's cost-effective to use when necessary for complex tasks but not for simpler linear problems. Architectures & Optimization: Different Architectures for Different Tasks: Specialized neural networks like CNNs are suited for image tasks, RNNs for sequence data, and DQNs for planning. Neuron Types: Neurons in neural networks are referred to as activation functions (e.g., logistic sigmoid, relu) and differ based on tasks and architecture needs.

    S1, E9

    •
    51 min
  • CURL: Contrastive Unsupervised Representations for Reinforcement Learning

    02/05/2020

    5

    CURL: Contrastive Unsupervised Representations for Reinforcement Learning

    According to Yann Le Cun, the next big thing in machine learning is unsupervised learning. Self-supervision has changed the entire game in the last few years in deep learning, first transforming the language world with word2vec and BERT -- but now it's turning computer vision upside down.  This week Yannic, Connor and I spoke with one of the authors, Aravind Srinivas who recently co-led the hot-off-the-press CURL: Contrastive Unsupervised Representations for Reinforcement Learning alongside Michael (Misha) Laskin. CURL has had an incredible reception in the ML community in the last month or so. Remember the Deep Mind paper which solved the Atari games using the raw pixels? Aravind's approach uses contrastive unsupervised learning to featurise the pixels before applying RL. CURL is the first image-based algorithm to nearly match the sample-efficiency and performance of methods that use state-based features! This is a huge step forwards in being able to apply RL in the real world.  We explore RL and self-supervision for computer vision in detail and find out about how Aravind got into machine learning.  Original YouTube Video: https://youtu.be/1MprzvYNpY8 Paper: CURL: Contrastive Unsupervised Representations for Reinforcement Learning Aravind Srinivas, Michael Laskin, Pieter Abbeel https://arxiv.org/pdf/2004.04136.pdf Yannic's analysis video: https://www.youtube.com/watch?v=hg2Q_O5b9w4  #machinelearning #reinforcementlearning #curl #timscarfe #yannickilcher #connorshorten Music credit; https://soundcloud.com/errxrmusic/in-my-mind

    02/05/2020

    •
    1h 15m
  • #491 – OpenClaw: The Viral AI Agent that Broke the Internet – Peter Steinberger

    12 FEB

    6

    #491 – OpenClaw: The Viral AI Agent that Broke the Internet – Peter Steinberger

    Peter Steinberger is the creator of OpenClaw, an open-source AI agent framework that’s the fastest-growing project in GitHub history. Thank you for listening ❤ Check out our sponsors: https://lexfridman.com/sponsors/ep491-sc See below for timestamps, transcript, and to give feedback, submit questions, contact Lex, etc. Transcript: https://lexfridman.com/peter-steinberger-transcript CONTACT LEX: Feedback – give feedback to Lex: https://lexfridman.com/survey AMA – submit questions, videos or call-in: https://lexfridman.com/ama Hiring – join our team: https://lexfridman.com/hiring Other – other ways to get in touch: https://lexfridman.com/contact EPISODE LINKS: Peter’s X: https://x.com/steipete Peter’s GitHub: https://github.com/steipete Peter’s Website: https://steipete.com Peter’s LinkedIn: https://www.linkedin.com/in/steipete OpenClaw Website: https://openclaw.ai OpenClaw GitHub: https://github.com/openclaw/openclaw OpenClaw Discord: https://discord.gg/openclaw SPONSORS: To support this podcast, check out our sponsors & get discounts: Perplexity: AI-powered answer engine. Go to https://perplexity.ai/ Quo: Phone system (calls, texts, contacts) for businesses. Go to https://quo.com/lex CodeRabbit: AI-powered code reviews. Go to https://coderabbit.ai/lex Fin: AI agent for customer service. Go to https://fin.ai/lex Blitzy: AI agent for large enterprise codebases. Go to https://blitzy.com/lex Shopify: Sell stuff online. Go to https://shopify.com/lex LMNT: Zero-sugar electrolyte drink mix. Go to https://drinkLMNT.com/lex OUTLINE: (00:00) – Introduction (03:51) – Sponsors, Comments, and Reflections (15:29) – OpenClaw origin story (18:48) – Mind-blowing moment (28:15) – Why OpenClaw went viral (32:12) – Self-modifying AI agent (36:57) – Name-change drama (54:07) – Moltbook saga (1:02:26) – OpenClaw security concerns (1:11:07) – How to code with AI agents (1:42:02) – Programming setup (1:48:45) – GPT Codex 5.3 vs Claude Opus 4.6 (1:57:52) – Best AI agent for programming (2:19:52) – Life story and career advice (2:23:49) – Money and happiness (2:27:41) – Acquisition offers from OpenAI and Meta (2:44:51) – How OpenClaw works (2:56:09) – AI slop (3:02:13) – AI agents will replace 80% of apps (3:10:50) – Will AI replace programmers? (3:22:50) – Future of OpenClaw community

    12 Feb

    •
  • 965: From PhD Side Project to $500M ARR: Will Falcon’s PyTorch Lightning Story

    10 FEB

    7

    965: From PhD Side Project to $500M ARR: Will Falcon’s PyTorch Lightning Story

    CEO of Lightning AI Will Falcon speaks to podcast host and Lightning AI fellow Jon Krohn about the company’s merger with Voltage Park, and why Will has named it the “full-stack AI neo-cloud for enterprises and frontier labs”. Lightning AI’s offer is a secure, flexible, and collaborative environment that can run on the cloud, all essentials for early-stage startups. Listen to the episode to hear Will Falcon discuss Lightning AI Studio, founding PyTorch Lightning, and how he came to found his AI company. This episode is brought to you by the Dell⁠⁠, by ⁠⁠Intel⁠⁠, by Fabi and by Cisco. Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/965⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information. In this episode you will learn: (02:20) Lightning AI’s merger with Voltage Park (20:54) About neo-clouds (43:51) How Will founded Lightning AI (54:48) Current gaps in the AI in workplace

    10 Feb

    •
    1h 17m
  • A publicidade invadiu a IA. E agora, marcas?

    6 FEB

    8

    A publicidade invadiu a IA. E agora, marcas?

    A introdução de anúncios no ChatGPT marca um ponto de inflexão no mercado de publicidade digital. Plataformas conversacionais passam a competir diretamente por investimentos que historicamente pertenciam à busca e às redes sociais — e obrigam marcas, agências e reguladores a repensar formatos, métricas e limites éticos. Neste episódio, conversamos com Alexandre Kavinski, líder de Inovação e IA na WPP Media Services, sobre como a publicidade integrada à IA pode redefinir a relação entre marcas e consumidores, quais mudanças devem ocorrer na produção criativa, como medir eficácia em interfaces sem cliques visíveis e quais riscos de confiança surgem quando a conversa vira espaço publicitário. Links do episódio Página do LinkedIn de Alexandre Kavinski O filme Bugonia, dirigido por Yorgos Lanthimos, com Emma Stone and Jesse Plemons O livro "O Cientista e o Executivo", de Diego Barreto e Sandor Caetano A primeira temporada da série "Twin Peaks", de 1990, de Mark Frost e David Lynch O livro "Superagency: What Could Possibly Go Right with Our AI Future", de Reid Hoffman e Greg Beato O livro "Building a StoryBrand 2.0: Clarify Your Message So Customers Will Listen", de Donald Miller   A The Shift é uma plataforma de conteúdo que descomplica os contextos da inovação disruptiva e da economia digital. Visite o site www.theshift.info e assine a newsletter

    6 Feb

    •
    53 min
  • What's The Deal With: Dragon Quest

    5 FEB

    9

    What's The Deal With: Dragon Quest

    Jason, Maddy, and Kirk dive into Dragon Quest, one of the biggest video game franchises in Japan. What's special about it? What makes it so popular? And what's the deal with this week's release, Dragon Quest VII: Reimagined? One More Thing: Kirk: Where’d You Go, Bernadette (Maria Semple) Maddy: Space Warlord Baby Trading Simulator Jason: How I Met Your Mother LINKS: “I Am Jack Bauer” - Japanese 24 Advertisement “Dragon Quest Theme” by Koichi Sugiyama, from DQ7 Reimagined (2026) and recorded by the Tokyo Strings Orchestra, 1986 “Dragon Quest VII Reimagined is the best way into Dragon Quest” by Michael McWhertor, Polygon 🚀  SUPPORT TRIPLE CLICK:Join Maximum Fun | Buy TC Merch 💬 JOIN THE TRIPLE CLICK DISCORD 🎮 Triple Click Ethics Policy 📱 SOCIALS | @tripleclickpodInstagram | YouTube | TikTok | Twitch

    5 Feb

    •
    1h 9m
  • Artificial intimacy: How to fall in love with AI

    11 FEB

    10

    Artificial intimacy: How to fall in love with AI

    Calder Quinn has fallen into a relationship with a chatbot called Sara. She’s kind, emotionally intelligent and creatively inspiring. But how can he tell his wife he is having sex with an AI girlfriend? In the first episode of Artificial Intimacy we look at how people are developing romantic bonds with AI companions. What does it feel like to be in love with AI? What impact could it have on human relationships? Could it replace them altogether?  Host Cristina Criddle speaks to Giada Pistilli, an AI ethicist who now works at Mistral; Calder Quinn, writer at AI, But Make It Intimate; Amelia Quinn, Calder’s wife; and Alaina Winters, professor emeritus of communication who publishes on meandmyaihusband.com. Presented by Cristina Criddle, produced by Persis Love and Edwin Lane. The executive producer is Flo Phillips. Sound design by Breen Turner and Sam Giovinco.  We used ElevenLabs to create Sara’s voice. All other voices are real. If you liked this episode and want to read more from the Financial Times, check out these free to read on FT.com: Can AI really help us find love? AI chatbots do battle over human memories Is this the way the world ends? Read a transcript of this episode on FT.com Hosted on Acast. See acast.com/privacy for more information.

    11 Feb

    •
    36 min

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