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Inference by Turing Post
Turing Post
18 episodes
1 month 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 Give AI True Memory? A conversation with Edo Liberty, CEO and founder @ Pinecone
Inference by Turing Post
31 minutes
7 months ago
When Will We Give AI True Memory? A conversation with Edo Liberty, CEO and founder @ Pinecone
What happens when one of the architects of modern vector search asks whether AI can remember like a seasoned engineer, not a gold‑fish savant? In this episode, Edo Liberty – founder & CEO of Pinecone and one‑time Amazon scientist – joins me to discuss true memory in LLMs. We unpack the gap between raw cognitive skill and workable knowledge, why RAG still feels pre‑ChatGPT, and the breakthroughs needed to move from demo‑ware to dependable memory stacks. Edo explains why a vector database needs to be built from the ground (and then rebuilt many times), that storage – not compute – has become the next hardware frontier, and predicts a near‑term future where ingesting a million documents is table stakes for any serious agent. We also touch the thorny issues of truth, contested data, and whether knowledgeable AI is an inevitable waypoint on the road to AGI. Whether you wrangle embeddings for a living, scout the next infrastructure wave, or simply wonder how machines will keep their facts straight, this conversation will sharpen your view of “memory” in the age of autonomous agents. Let’s find out when tomorrow’s AI will finally remember what matters. (CORRECTION: the opening slide introduces Edo Liberty as a co-founder. We apologize for this error: Edo Liberty is the Founder and CEO of Pinecone.) Did you like the video? You know what to do: Subscribe to the channel. Leave a comment if you have something to say. Like it if you liked it. That’s all. Thanks. Guest: Edo Liberty, CEO and founder at Pinecone Website: https://www.pinecone.io/ Additional Reading: https://www.turingpost.com/ Chapters 00:00 Intro & The Big Question – When will we give AI true memory? 01:20 Defining AI Memory and Knowledge 02:50 The Current State of Memory Systems in AI 04:35 What’s Missing for “True Memory”? 06:00 Hardware and Software Scaling Challenges 07:45 Contextual Models and Memory-Aware Retrieval 08:55 Query Understanding as a Task, Not a String 10:00 Pinecone’s Full Stack Approach 11:00 Commoditization of Vector Databases? 13:00 When Scale Breaks Your Architecture 15:00 The Rise of Multi-Tenant & Micro-Indexing 17:25 Dynamically Choosing the Right Indexing Method 19:05 Infrastructure for Agentic Workflows 20:15 The Hard Questions: What is Knowledge? 21:55 Truth vs Frequency in AI 22:45 What is “Knowledgeable AI”? 23:35 Is Memory a Path to AGI? 24:40 A Book That Shaped a CEO – *Endurance* by Shackleton 26:45 What Excites or Worries You About AI’s Future? 29:10 Final Thoughts: Sea Change is Here In Turing Post we love machine learning and AI so deeply that we cover it extensively from all perspectives: past of it, its present, and our joint-future. We explain what happens the way you will understand. Sign up: Turing Post: https://www.turingpost.com FOLLOW US Edo Liberty: https://www.linkedin.com/in/edo-liberty-4380164/ Pinecone: https://x.com/pinecone Ksenia and Turing Post: Hugging Face: https://huggingface.co/Kseniase Turing Post: https://x.com/TheTuringPost Ksenia: https://x.com/Kseniase_ Linkedin: TuringPost: https://www.linkedin.com/company/theturingpost Ksenia: https://www.linkedin.com/in/ksenia-se
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.