Inference by Turing Post

We're no longer in the world of chatbots – we're in the world where AI systems take real-world action. So what does responsible AI even mean when agents write the code, review the code, and act across organizational boundaries? Sarah Bird, Chief Product Officer of Responsible AI at Microsoft, has been in this field since it was a niche. Now it's everywhere. In this episode of Inference, she explai...

GitHub's CPO Mario Rodriguez on how AI agents transformed the platform in December 2025 — record commits, new Copilot direction, and what "agent-native" coding actually means for developers. What happened to GitHub then? Record acceleration across commits, PRs, Actions, and security scans – and a fundamental rethink of what GitHub even is. *In this episode of Inference, we get into:* The December...

What does it really take to put AI-powered building into the hands of millions and even billions – and what happens when everyone becomes a builder? How to do impossible things? Ammaar Reshi leads Product and Design at Google AI Studio (DeepMind). His path is unusual: from writing iPhone app reviews as a teenager, to Palantir, Brex, and ElevenLabs, to now designing how millions of people build app...

Eric Ries, author of The Lean Startup, on why success corrupts companies faster than failure — and how AI will accelerate that collapse if builders don't protect their mission from day one. Eric Ries, entrepreneur and author of The Lean Startup and Incorruptible, argues that the more valuable a company becomes, the more pressure it faces to make money without creating real value. In other words: c...

"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...

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 the...

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 t...

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...

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...

Regarding the question of what matters most – the model or the harness – Michael Bolin is somewhere in the middle. Stronger models clearly pushed Codex to new heights. But without the right harness around them, those models would not be able to operate reliably, and – most importantly – safely on a real developer’s machine. At least, not yet. In this episode of Inference, I talk with Michael Bolin...

In this episode, Ioannis Antonoglou, co-founder and CTO @ReflectionAI (ex-DeepMind, AlphaGo/AlphaZero/MuZero) explains what they are building: a frontier open-weight “general agent model” trained end-to-end with pretraining plus reinforcement learning. And I’ll be honest: I left this conversation more skeptical than I expected. They raised $2 billion last year. But where the results? Reflection’s...

Ioannis Antonoglou helped build AlphaGo, AlphaZero, and MuZero at DeepMind. Now he’s CTO and co-founder of Reflection AI, betting that frontier models should be open weights, not a black box behind an API. In Part 1, we talk about openness as an actual strategy: why open models can move faster, why “sovereignty” matters for enterprises and governments, and why safety might improve when the ecosyst...

Open models are often discussed as if they’re competing head-to-head with frontier systems. Are they catching up? Falling behind? Are they “good enough” yet? Nathan Lambert doesn’t believe open models will ever catch up with closed ones, and he explains clearly why. But he also argues that this is the wrong framing. Nathan is a research scientist at the Allen Institute for AI, the author of the RL...

First Western interview with a senior MiniMax researcher. Olive Song explains how they actually build models that work. When MiniMax's RL training wouldn't converge, they debugged layer by layer until they found it: fp32 precision in the LM head. When their models learned to "hack" during training, exploiting loopholes to maximize rewards, they had to rethink alignment from scratch. When benchmark...

In the first episode of Inference’s quarterly series on Open Source AI, we talk to Raffi Krikorian, CTO of Mozilla, about when open source AI stops being aspirational and becomes an operational choice. We explore why stories like Pinterest saving $10 million by moving to open models are real, but often misunderstood, and why timing matters more than ideology. Raffi lays out his view of a missing “...

Is math the ultimate test for AI reasoning? Or is next-token prediction fundamentally incapable of discovering new truths and discovering conjectures? Carina Hong, co-founder and CEO of Axiom Math, argues that to build true reasoning capabilities, we need to move beyond "chatty" models to systems that can verify their own work using formal logic. In this episode of Inference, we get into: Why curr...

Is security still about patching after the crash? Or do we need to rethink everything when AI can cause failures on its own? Anneka Gupta, Chief Product Officer at Rubrik, argues we're now living in the world before the crash – where autonomous systems can create their own failures. In this episode of Inference, we explore: Why AI agents are "the human problem on steroids" The three pillars of AI...

When robots move into the real world, speed and safety come from simulation! In his first sit-down interview, Spencer Huang – NVIDIA’s product lead for robotics software – talks about his role at NVIDIA, a flat organization where “you have access to everything.” We discuss how open source shapes NVIDIA’s robotics ecosystem, how robots learn physics through simulation, and why neural simulators and...

When thousands of AI agents begin to act on our behalf, who builds the system they all run on? Renen Hallak – founder and CEO of VAST Data – believes we’re witnessing the birth of an *AI Operating System*: a foundational layer that connects data, compute, and policy for the agentic era. In this episode of Inference, we talk about how enterprises are moving from sandboxes and proof-of-concepts to f...

This episode of Inference is dedicated to Breast Cancer Awareness Month. I’m talking with Akash Parvatikar – AI scientist and product leader in digital pathology and computational biology. He leads PathologyMap™ at HistoWiz, a digital pathology platform that turns whole-slide images into searchable, analyzable data with AI tools – streamlining research and accelerating insights for cancer and prec...

Is compute the main roadblock? Or the models are not big enough for AGI? Ulrik Hansen, president and co-founder of Encord, argues that the true bottleneck is data. In this episode of Inference, we get into: Why models are mostly interchangeable, but data orchestration makes or breaks real-world AI Tesla’s compounding advantage from live human feedback vs. Waymo’s cautious rollout Why robotics lags...

What comes after the IDE? In this episode of Inference, I sit down with Zach Lloyd, founder of Warp, to talk about a new category he’s coining: the Agentic Development Environment (ADE). We explore why coding is shifting from keystrokes to prompts, how Warp positions itself against tools like Cursor and Claude Code, and what it means for developers when your “junior dev” is an AI agent that can al...

What limits AI today isn’t imagination – it’s the cost of running it at scale. In this episode of Inference, Ksenia Se sits down with Lin Qiao, co-founder & CEO of Fireworks AI (an inference-first company) and former head of PyTorch at Meta, where she led the rebuild of Meta’s entire AI infrastructure stack. We talk about: Why product-market fit can be the beginning of bankruptcy in GenAI The...

Right now, the biggest leap for AI isn’t a bigger model – it’s giving models and agents a way to act. In this episode of Inference, I sit down with Alex Hancock – Senior Software Engineer at Block, core contributor to Goose (the open-source, multi-purpose AI agent), and a member of the Model Context Protocol (MCP) Steering Committee – to talk about the infrastructure that’s quietly powering the ne...

In this episode of Inference, I sit down with Amr Awadallah – founder & CEO of Vectara, founder of Cloudera, ex-Google Cloud, and the original builder of Yahoo’s data platform – to unpack what’s actually happening with retrieval-augmented generation (RAG) in 2025. We get into why RAG is far from dead, how context windows mislead more than they help, and what it really takes to separate reasoni...