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Inference by Turing Post

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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.
Top 94.5% by pitch volume (Rank #47258 of 50,000)Data updated Feb 10, 2026

Key Facts

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Episodes
19
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Technology
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Audience: Under 4K / month
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Latest Episodes

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This Is a Fight Worth Having: The Case for Open Source AI | Raffi Krikorian, Mozilla CTO

Tue Jan 27 2026

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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 “LAMP stack for AI” and explains why the hardest problem to solve isn’t models or data, but the connective glue that holds AI systems together. Along the way, he shares how Mozilla is navigating these tradeoffs in practice, why even open-source-first organizations still rely on closed tools during experimentation, and what the browser era taught Mozilla about defaults, user choice, and long-term control. He also shares a few practical recommendations in this episode that apply even if you’re still experimenting. Listen closely. This conversation kicks off our Open Source AI series for 2026, focused on real tradeoffs, real economics, and the decisions companies are making right now. 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:* Raffi Krikorian, CTO at Mozilla LinkedIn: https://www.linkedin.com/in/rkrikorian/ Mozilla AI: https://mozilla.ai/ Mozilla Blog: https://blog.mozilla.org/en/mozilla/mozilla-open-source-ai-strategy/ *Links mentioned:* Raffi's post here about our OSAI strategy: https://blog.mozilla.org/en/mozilla/mozilla-open-source-ai-strategy/ 🌐 #1: Mastering Open Source AI in 2026: Essential Decisions for Builders https://www.turingpost.com/p/opensource1 Mozilla Data Collective: https://data.mozilla.org/ Langchain: https://www.langchain.com/ OpenRouter: https://openrouter.ai/ AI2 (Allen Institute for AI): https://allenai.org/ Flower AI (Federated Learning): https://flower.dev/ Einstein's Dreams by Alan Lightman: https://www.goodreads.com/book/show/14376.Einstein_s_Dreams 📰 The transcript and edited version at https://www.turingpost.com/krikorian *Chapters:* 0:00 Cold Open — Values vs Economics in Open Source AI 0:28 Intro: Why This Season Focuses on Open Source AI 0:54 When Open Source Becomes a Business Decision 1:44 Pinterest Saved $10M + The Shift From Prototyping to Production 2:42 Mozilla’s “Choice Suite” + The Terraform “Exit Door” 5:21 Mozilla’s Mission: Do for AI What Mozilla Did for the Web 7:09 The “LAMP Stack” for AI + Standards Across the Stack 9:52 Small Models, Specialization, and Model Composability 15:45 Data, Privacy, and “I Own My Context” 18:36 “This Is a Fight Worth Having” + The Signal Analogy 21:42 1–2–3 Steps for Companies to Start (Instrument Choice Early) 24:22 Book Pick: Einstein’s Dreams + Closing Turing Post is a newsletter about AI's past, present, and future. Ksenia Se explores how intelligent systems are built – and how they're changing how we think, work, and live. *Follow us →* Turing Post: https://x.com/TheTuringPost Ksenia Se: https://www.linkedin.com/in/ksenia-se https://huggingface.co/Kseniase #OpenSourceAI #LAMPStackForAI #AIEconomics #MozillaAI #AIInfrastructure #DataProvenance #FederatedLearning #OpenModels

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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 “LAMP stack for AI” and explains why the hardest problem to solve isn’t models or data, but the connective glue that holds AI systems together. Along the way, he shares how Mozilla is navigating these tradeoffs in practice, why even open-source-first organizations still rely on closed tools during experimentation, and what the browser era taught Mozilla about defaults, user choice, and long-term control. He also shares a few practical recommendations in this episode that apply even if you’re still experimenting. Listen closely. This conversation kicks off our Open Source AI series for 2026, focused on real tradeoffs, real economics, and the decisions companies are making right now. 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:* Raffi Krikorian, CTO at Mozilla LinkedIn: https://www.linkedin.com/in/rkrikorian/ Mozilla AI: https://mozilla.ai/ Mozilla Blog: https://blog.mozilla.org/en/mozilla/mozilla-open-source-ai-strategy/ *Links mentioned:* Raffi's post here about our OSAI strategy: https://blog.mozilla.org/en/mozilla/mozilla-open-source-ai-strategy/ 🌐 #1: Mastering Open Source AI in 2026: Essential Decisions for Builders https://www.turingpost.com/p/opensource1 Mozilla Data Collective: https://data.mozilla.org/ Langchain: https://www.langchain.com/ OpenRouter: https://openrouter.ai/ AI2 (Allen Institute for AI): https://allenai.org/ Flower AI (Federated Learning): https://flower.dev/ Einstein's Dreams by Alan Lightman: https://www.goodreads.com/book/show/14376.Einstein_s_Dreams 📰 The transcript and edited version at https://www.turingpost.com/krikorian *Chapters:* 0:00 Cold Open — Values vs Economics in Open Source AI 0:28 Intro: Why This Season Focuses on Open Source AI 0:54 When Open Source Becomes a Business Decision 1:44 Pinterest Saved $10M + The Shift From Prototyping to Production 2:42 Mozilla’s “Choice Suite” + The Terraform “Exit Door” 5:21 Mozilla’s Mission: Do for AI What Mozilla Did for the Web 7:09 The “LAMP Stack” for AI + Standards Across the Stack 9:52 Small Models, Specialization, and Model Composability 15:45 Data, Privacy, and “I Own My Context” 18:36 “This Is a Fight Worth Having” + The Signal Analogy 21:42 1–2–3 Steps for Companies to Start (Instrument Choice Early) 24:22 Book Pick: Einstein’s Dreams + Closing Turing Post is a newsletter about AI's past, present, and future. Ksenia Se explores how intelligent systems are built – and how they're changing how we think, work, and live. *Follow us →* Turing Post: https://x.com/TheTuringPost Ksenia Se: https://www.linkedin.com/in/ksenia-se https://huggingface.co/Kseniase #OpenSourceAI #LAMPStackForAI #AIEconomics #MozillaAI #AIInfrastructure #DataProvenance #FederatedLearning #OpenModels

Key Metrics

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From PodPitch users
Rank
#47258
Top 94.5% by pitch volume (Rank #47258 of 50,000)
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Reviews
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Written reviews (when available)
Publish cadence
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Episode count
19
Data updated
Feb 10, 2026
Social followers
82.2K

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Country
United States
Language
English
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Latest episode date
Tue Jan 27 2026

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Under 4K / month
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Social followers
82.2K
Contact available
Yes
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Frequently Asked Questions About Inference by Turing Post

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What is Inference by Turing Post about?

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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