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Inference by Turing Post

Turing Post
Inference by Turing Post
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  • Inference by Turing Post

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

    05.05.2026 | 43 Min.
    "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
  • Inference by Turing Post

    AI Could Change Education Forever – Neeru Khosla Explains Why

    22.04.2026 | 34 Min.
    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
  • Inference by Turing Post

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

    07.04.2026 | 18 Min.
    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
  • Inference by Turing Post

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

    31.03.2026 | 33 Min.
    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/
  • Inference by Turing Post

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

    24.03.2026 | 9 Min.
    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

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Über Inference by Turing Post

Inference is Turing Post’s way of asking the big questions about AI — and refusing easy answers. Each episode starts with a simple prompt: “When will we…?” – and follows it wherever it leads.Host Ksenia Se sits down with the people shaping the future firsthand: researchers, founders, engineers, and entrepreneurs. The conversations are candid, sharp, and sometimes surprising – less about polished visions, more about the real work happening behind the scenes.It’s called Inference for a reason: opinions are great, but we want to connect the dots – between research breakthroughs, business moves, technical hurdles, and shifting ambitions.If you’re tired of vague futurism and ready for real conversations about what’s coming (and what’s not), this is your feed. Join us – and draw your own inference.
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