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Inference by Turing Post
Turing Post
13 episodes
1 week ago
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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Technology
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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.
Show more...
Technology
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When Will We Train Once and Learn Forever? Insights from Dev Rishi, CEO and co-founder ⁨@Predibase ​
Inference by Turing Post
28 minutes
5 months ago
When Will We Train Once and Learn Forever? Insights from Dev Rishi, CEO and co-founder ⁨@Predibase ​
What it actually takes to build models that improve over time. In this episode, I sit down with Devvret Rishi, CEO and co-founder of Predibase, to talk about the shift from static models to continuous learning loops, the rise of reinforcement fine-tuning (RFT), and why the real future of enterprise AI isn’t chatty generalists – it’s focused, specialized agents that get the job done. We cover: The real meaning behind "train once, learn forever" How RFT works (and why it might replace traditional fine-tuning) What makes inference so hard in production Open-source model gaps—and why evaluation is still mostly vibes Dev’s take on agentic workflows, intelligent inference, and the road ahead If you're building with LLMs, this conversation is packed with hard-earned insights from someone who's doing the work – and shipping real systems. Dev is super structural! I really enjoyed this conversation. Did you like the video? You know what to do: 📌 Subscribe for more deep dives with the minds shaping AI. Leave a comment if you have something to say. Like it if you liked it. That’s it. Oh yeap, one more thing: Thank you for watching and sharing this video. We truly appreciate you. Guest: Devvret Rishi, co-founder and CEO at Predibase https://predibase.com/ If you don’t see a transcript, subscribe to receive our edited conversation as a newsletter: https://www.turingpost.com/subscribe Chapters: 00:00 - Intro 00:07 - When Will We Train Once and Learn Forever? 01:04 - Reinforcement Fine-Tuning (RFT): What It Is and Why It Matters 03:37 - Continuous Feedback Loops in Production 04:38 - What's Blocking Companies From Adopting Feedback Loops? 05:40 - Upcoming Features at Predibase 06:11 - Agentic Workflows: Definition and Challenges 08:08 - Lessons From Google Assistant and Agent Design 08:27 - Balancing Product and Research in a Fast-Moving Space 10:18 - Pivoting After the ChatGPT Moment 12:53 - The Rise of Narrow AI Use Cases 14:53 - Strategic Planning in a Shifting Landscape 16:51 - Why Inference Gets Hard at Scale 20:06 - Intelligent Inference: The Next Evolution 20:41 - Gaps in the Open Source AI Stack 22:06 - How Companies Actually Evaluate LLMs 23:48 - Open Source vs. Closed Source Reasoning 25:03 - Dev’s Perspective on AGI 26:55 - Hype vs. Real Value in AI 30:25 - How Startups Are Redefining AI Development 30:39 - Book That Shaped Dev’s Thinking 31:53 - Is Predibase a Happy Organization? 32:25 - Closing Thoughts Turing Post is a newsletter about AI's past, present, and future. Publisher Ksenia Semenova explores how intelligent systems are built – and how they’re changing how we think, work, and live. Sign up: Turing Post: https://www.turingpost.com FOLLOW US Devvret and Predibase: https://devinthedetail.substack.com/ https://www.linkedin.com/company/predibase/ Ksenia and Turing Post: https://x.com/TheTuringPost https://www.linkedin.com/in/ksenia-se https://huggingface.co/Kseniase
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.