Inference by Turing Post

Will Everyone Become an AI Builder? Clem Delangue on Hugging Face, Agents, Local AI & Robotics

"The numbers of people who are going to be able to become AI builders is going to explode. It's gonna go from maybe a few hundred thousands or low millions… to maybe tens of millions, fifties of millions, maybe a hundred million at some point." Clément Delangue, co-founder and CEO of Hugging Face, believes we are entering a new phase of AI – one where building models, fine-tuning systems, running local AI, and even experimenting with robotics may no longer be limited to a small technical elite. His passion for open source is very contagious! I enjoyed chatting with him about: Why the next wave of AI builders won't be traditional engineers – and how that could push the field beyond slop toward biology, medicine, and climate What open source actually solves in cybersecurity – and why "safety" is often a cover story for business strategy Why lobbying against open source in the US would be a strategic mistake that could cost the country its AI leadership Why comparing open weights to closed APIs is irrelevant and why benchmarks miss what really matters What Hugging Face is learning as agents become a new kind of user How LeRobot and Reachy Mini are turning AI into something people lile Why training, fine-tuning, and post-training on your own data are becoming the real differentiators as building apps gets trivial What three months of paternity leave taught Clem We also talk about fear-based AI marketing, how public perception shifts the moment people build with AI, what's missing in robotics datasets, and why Clem keeps coming back to Camus' Sisyphus as a metaphor for being a founder right now A conversation about agency, openness, and what it means to democratize AI before it gets locked down. Watch it. *Chapters:* 00:00 AI Builders Are About to Explode 00:35 Why Coding Agents Still Struggle with AI 02:23 100 Million AI Builders 03:30 Non-Technical People Entering AI 05:15 How Building AI Can Change Public Perception 06:22 Who Can Make AI More Open? 08:02 Fear-Based Marketing in AI 09:33 Open Source, Cybersecurity, and Risk 12:31 Why Companies Don’t Open Source 14:30 Lobbying Against Open Source 17:24 What Changed During Paternity Leave 19:11 Making Hugging Face Agent-Native 21:00 Hugging Face Robotics and LeRobot 23:01 Local AI, Open Models, and the Future *Did you like the episode? Do the following:* 📌 Subscribe here and here (https://www.turingpost.com/subscribe) for more conversations with the builders shaping real-world AI. 💬 Leave a comment 👍 Like it 🫶 Thank you for watching and sharing! *Guest:* Clément Delangue, co-founder & CEO of Hugging Face https://x.com/ClementDelangue https://www.linkedin.com/in/clementdelangue https://huggingface.co/clem https://huggingface.co/ *Projects discussed:* ML Intern LeRobot SO-101 / LeRobot docs 📰 Want the transcript and edited version? Subscribe to Turing Post: https://www.turingpost.com/subscribe Turing Post is a newsletter about AI’s past, present, and future. Publisher Ksenia Se explores how intelligent systems are built – and how they’re changing how we think, work, and live. Follow us - Ksenia and Turing Post: https://x.com/TheTuringPost https://www.linkedin.com/in/ksenia-se https://huggingface.co/Kseniase #HuggingFace #ClemDelangue #OpenSourceAI #LocalAI #AIAgents #RoboticsAI #LeRobot #MLIntern #AIBuilders #FutureOfAI

AI Could Change Education Forever – Neeru Khosla Explains Why

Can AI actually help children learn better – or are schools still too slow, too scared, and too locked into the old system? Neeru Khosla, co-founder of CK-12 Foundation, believes this moment could become a turning point for education. After nearly two decades building free learning tools for students and teachers, she argues that AI is our chance to finally understand how students think, where they get stuck, and how to help each child learn in a way that works for them. *In this episode of Inference, we get into:* - Why prompting is not cheating, but a real learning skill - Why textbooks alone were never enough for deep understanding - What C means in CK-12 (it’s important!) - What Neeru learned from launching Flexi, CK-12’s AI tutor, now used by millions of students - Why standardized testing misses the most important part of learning - Why teachers need support, visibility, and confidence – not fear - Why AI literacy may become as fundamental as reading, writing, and math - How curiosity, mentorship, and community shape better learning outcomes - Why “attention is all you need” is no longer enough – and what we need now We also talk about public school inertia, philanthropy, core values when raising kids, and why Neeru believes AI should be used as augmented intelligence – not something to fear, but something to help humans grow. This is a conversation about education, equity, curiosity, and what it would really take to build a learning system that works for every child. Watch it. I’m really passionate about this topic and think that everyone should think and talk more about it. *Did you like the episode? You know the drill:* 📌 Subscribe for more conversations with the people rethinking how AI will shape society 💬 Leave a comment if this resonated with you 👍 Like it if you liked it 🫶 Thank you for watching and sharing *Guest:* Neeru Khosla, co-founder and executive director of CK-12 Foundation https://info.ck12.org/neeru-khosla https://www.ck12.org/flexi/ *📰 Want the transcript and edited version?* Subscribe to Turing Post: https://www.turingpost.com/subscribe *Chapters* 0:00 Why Education Is the Greatest Gift to Society 0:27 Meet Neeru Khosla & the Mission of CK-12 1:32 How Technology Changed Learning Over the Years 3:20 Why AI Became a Turning Point in Education 5:52 Flexi: CK-12’s AI Tutor Used by Millions 8:26 Does AI Require Rethinking the Education System? 11:12 What Teachers Need From AI Right Now 12:56 Essential Skills for Kids and Teachers in the AI Era 18:13 From Molecular Biology to Building CK-12 23:27 Why Education Is a Human Right — and What Comes Next Turing Post is a newsletter about AI’s past, present, and future. Publisher Ksenia Se explores how intelligent systems are built – and how they’re changing how we think, work, and live. *Follow us* Ksenia and Turing Post: https://x.com/TheTuringPost https://www.linkedin.com/in/ksenia-se https://huggingface.co/Kseniase #AIinEducation #EducationAI #NeeruKhosla #CK12 #Flexi #AILiteracy #FutureOfEducation #EdTech #PersonalizedLearning #TuringPost

Transformers Are Not the End Game | World Models, Physical AI, and AI’s Next Frontier

At NVIDIA GTC, we sat down with Sanja Fidler, VP of AI Research at NVIDIA and one of the leading voices in spatial intelligence and physical AI. We dive into world models, robotics, autonomous driving, and the hard problems AI still hasn’t solved. If you want to understand where AI goes next and what occupies the minds of the best researchers, you need to watch this video. *In this episode:* Why transformers and world models are not competing ideas Why physical AI is still a major frontier The evolution of simulation Why 3D matters for robotics and real-world intelligence What’s still missing in multimodal AI Whether autonomous driving could have a “ChatGPT moment” before robotics does If you enjoy conversations at the edge of AI research, *subscribe to Turing Post* for more interviews with the people building the future https://www.turingpost.com/ *Chapters:* 0:00 Physical AI vs Transformers — The Big Question 0:19 Introduction: NVIDIA & Spatial Intelligence Lab 0:38 Transformers vs World Models — Not a Competition 1:45 World Models as Simulators of Reality 3:20 Are New Architectures Replacing Transformers? 4:17 “Alpa Dreams” — Real-Time Interactive AI Worlds 6:22 The Evolution of Simulation in Self-Driving 7:44 From 3D Reconstruction to True World Modeling 10:26 Multimodal AI: Audio, Radar, and Physical Interaction 13:29 AGI, Robotics & the Future of Physical AI *Did you like the episode? You know the drill:* 📌 Subscribe here and here (https://www.turingpost.com/subscribe) for more conversations with the builders shaping real-world AI. 💬 Leave a comment 👍 Like it 🫶 Thank you for watching and sharing! *Guest:* Sanja Fidler – NVIDIA Research https://research.nvidia.com/person/sanja-fidler University of Toronto https://www.cs.toronto.edu/~fidler/ Spatial Intelligence Lab https://research.nvidia.com/labs/sil/ Google Scholar https://scholar.google.com/citations?user=CUlqK5EAAAAJ&hl=en X https://x.com/FidlerSanja LinkedIn https://ca.linkedin.com/in/sanja-fidler-2846a1a #AI #NVIDIA #SanjaFidler #WorldModels #PhysicalAI #SpatialIntelligence #Robotics #AutonomousDriving #Transformers #GTC

Inside NVIDIA’s Plan to Bring Self-Driving to Every Car | Ali Kani explains

What if the future of self-driving isn’t one perfect robotaxi – but a stack that can turn almost any car into a self-driving car? In this episode of Inference, we ride through San Francisco – as one of the first to do this test drive – and talk about what’s changing in autonomous driving: cheaper hardware, better models, synthetic data, and a whole new approach to building the software behind the wheel. Ali Kani has been at NVIDIA Automotive for almost 8 years – he’s been through all the ups and downs, and he’s eager to share. *We talk about:* Why Level 2 is already possible with a surprisingly cheap sensor setup What is still missing for Level 4 Why next year could matter for Level 4 How NVIDIA combines an end-to-end driving model with a classical safety stack Why open source matters for the future of autonomous driving Why synthetic data and simulation may matter as much as real-world driving data How different cities, laws, and driving cultures change the way autonomous systems behave Why the goal is bigger than one self-driving car – it’s making many cars autonomous by open sourcing the whole stack (it’s HUGE) We also experience live what still makes urban driving hard: construction, cyclists, congestion, weird negotiations at stop signs, and all the messy little moments humans barely notice but cars have to handle perfectly. What I liked about this conversation is that it makes the shift feel very real. *We’re moving from self-driving built inside closed labs to self-driving becoming a shared capability that can spread across the whole car industry.* This is a conversation about a future that starts tomorrow. It’s open and very exciting. Chapters: 0:00 The Future of Self-Driving Starts Now 0:19 Open Autonomous Driving Beyond Tesla and Waymo 1:07 Inside NVIDIA’s Low-Cost Level 2 Self-Driving Stack 1:48 From Level 2 to Level 4: Hyperion, Thor, and Redundancy 2:43 How NVIDIA Combines End-to-End AI with Safety Guardrails 3:56 What Changed in AlphaMaio Since GTC 5:12 The Key Technologies Needed to Solve Self-Driving 7:22 Real Data vs Synthetic Data in Autonomous Driving 9:21 Driving Through Real San Francisco Traffic 18:55 AlphaDream and the Next Generation of Simulation *Follow on*: https://www.turingpost.com/ https://www.turingpost.com/p/av *Did you like the episode? You know the drill:* 📌 Subscribe here and here (https://www.turingpost.com/subscribe) for more conversations with the builders shaping real-world AI. 💬 Leave a comment 👍 Like it 🫶 Thank you for watching and sharing! *Guest:* Ali Kani, Vice President and General Manager of Automotive, NVIDIA https://www.linkedin.com/in/ali-kani-b22198 https://blogs.nvidia.com/blog/author/alikani/ Read more: https://www.turingpost.com/p/selfdriving https://thefocus.ai/posts/the-car-wash-test/

OpenAI’s Michael Bolin: What Engineers Still Matter For in the Age of Coding Agents

In this second part of my conversation with Michael Bolin, lead for open-source Codex at OpenAI, we move from harness engineering to the human side of the story. What does it mean to be a programmer when you are no longer typing most of the code? Which skills become more important in an agent-driven workflow? Will coding agents eventually take over most software implementation? And if that happens, what is left for the human engineer besides pushing prompts around like a confused project manager with Wi-Fi? All of it and more in this part – watch it. *Follow on*: https://www.turingpost.com/ *Did you like the episode? You know the drill:* 📌 Subscribe for more conversations with the builders shaping real-world AI. 💬 Leave a comment if this resonated. 👍 Like it if you liked it. 🫶 Thank you for watching and sharing! *Guest:* Michael Bolin, tech lead on Codex, OpenAI https://www.linkedin.com/in/michael-bolin-7632712/ https://x.com/bolinfest https://github.com/openai/codex Chapters: 0:00 — Do You Still Need to Learn Coding? 0:18 — From Systems to Humans: The Future of Programming 0:39 — Switching Mindset: Building for Agents vs Developers 1:13 — What Happens When Agents Consume the Web? 1:27 — Programmer Identity in the Age of AI 2:15 — Are Engineers Building More Than Ever? 2:37 — Key Skills for Engineers Working with AI Agents 3:59 — Will Agents Take Over Coding? 4:57 — Engineering Taste vs AI Decisions 5:10 — From Idea to Product Faster Than Ever 6:01 — Risks: Losing Human Judgment Too Early 6:42 — Do We Still Need Humans in the Loop? 8:06 — Book That Shaped a Builder’s Mindset 📰 Transcript:https://www.turingpost.com/p/bolincodex https://x.com/TheTuringPost https://www.linkedin.com/in/ksenia-se #AI #OpenAI #Codex #MichaelBolin #SoftwareEngineering #Programming #CodingAgents #AIAgents #DeveloperTools #HarnessEngineering #FutureOfWork #Engineering #TuringPost