Data Science at Home

Francesco Gadaleta

Cutting through AI bullsh*t. Come join the discussion on Discord! https://discord.gg/4UNKGf3

  1. 6 MARS

    Programmable Money: The Cage They'll Call Convenience (Ep. 300)

    Money has always been yours to spend freely. That's about to change. This episode breaks down programmable money, the technology that turns your wallet into a permission system.   ✨ Connect with us! Personal newsletter: https://defragzone.substack.com 📩 Newsletter: https://datascienceathome.substack.com 🎙 Podcast: Available on Spotify, Apple Podcasts, and more. 🐦 Twitter: @DataScienceAtHome 📘LinkedIn: https://www.linkedin.com/in/fragadaleta/ Instagram: https://www.instagram.com/datascienceathome/ Facebook: https://www.facebook.com/datascienceAH LinkedIn: https://www.linkedin.com/company/data-science-at-home-podcast Discord Channel: https://discord.gg/4UNKGf3   NEW TO DATA SCIENCE AT HOME? Welcome! Data Science at Home explores the latest in AI, data science, and machine learning. Whether you’re a data professional, tech enthusiast, or just curious about the field, our podcast delivers insights, interviews, and discussions. Learn more at https://datascienceathome.com   SEND US MAIL! We love hearing from you! Send us mail at: hello@datascienceathome.com Don’t forget to like, subscribe, and hit the 🔔 for updates on the latest in AI and data science!

    25 min

  2. 3 MARS

    There Is No AI. There's a Stateless Function on 10,000 GPUs Pretending to Know You (Ep. 299)

    Right now, millions of people are simultaneously chatting with a system that remembers nothing, knows nothing, and resets after every message. The engineering keeping that illusion alive is actually the impressive part.   ✨ Connect with us! Personal newsletter: https://defragzone.substack.com 📩 Newsletter: https://datascienceathome.substack.com 🎙 Podcast: Available on Spotify, Apple Podcasts, and more. 🐦 Twitter: @DataScienceAtHome 📘 LinkedIn: https://www.linkedin.com/in/fragadaleta/ Instagram: https://www.instagram.com/datascienceathome/ Facebook: https://www.facebook.com/datascienceAH LinkedIn: https://www.linkedin.com/company/data-science-at-home-podcast Discord Channel: https://discord.gg/4UNKGf3   NEW TO DATA SCIENCE AT HOME? Welcome! Data Science at Home explores the latest in AI, data science, and machine learning. Whether you’re a data professional, tech enthusiast, or just curious about the field, our podcast delivers insights, interviews, and discussions. Learn more at https://datascienceathome.com   SEND US MAIL! We love hearing from you! Send us mail at: hello@datascienceathome.com Don’t forget to like, subscribe, and hit the 🔔 for updates on the latest in AI and data science!

    39 min

  3. 10 JANV.

    AGI: The Dream We Should Never Reach (Ep. 296)

    Also on YouTube   Two AI experts who actually love the technology explain why chasing AGI might be the worst thing for AI's future—and why the current hype cycle could kill the field we're trying to save. Want to dive deeper? Head to datascienceathome.com for detailed show notes, code examples, and exclusive deep-dives into the papers we discuss.   Subscribe to our newsletter for weekly breakdowns of cutting-edge research delivered straight to your inbox—no fluff, just science! 📧 Join the conversation! Our Discord community is full of ML engineers, researchers, and AI enthusiasts discussing papers, sharing projects, and helping each other level up. Whether you're debugging your first neural net or training your tenth transformer, there's a place for you. Link in the show notes! 💬 Newsletter https://datascienceathome.substack.com/subscribe Website https://datascienceathome.com     References CEO is obsolete AI is the new blockchain Dr Eliseo Ferrante NYU https://nyuad.nyu.edu/en/academics/divisions/science/faculty/eliseo-ferrante.html

    46 min

  4. 22/12/2025

    When Data Stops Being Code and Starts Being Conversation (Ep. 297)

    Mark Brocato built Mockaroo—the tool that taught millions of developers how to fake data. Now, as Head of Engineering at Tonic.ai, he's building the AI agent that's making his own creation obsolete. In this episode, we explore why static test data can't survive the AI era, what it means to "negotiate" datasets with an agent instead of scripting them, and whether we're heading toward a future where sandbox environments vanish entirely. From the hidden failures of legacy mocks to the security implications of agent-driven synthesis, Mark reveals what happens when data generation becomes a conversation—not a pipeline.   Sponsors   Tonic.ai Synthetic data solutions for software and AI development. Accelerate engineering velocity and ensure compliance with AI-powered data synthesis   This episode is brought to you by Statistical Horizons  At Statistical Horizons, you can stay ahead with expert-led livestream seminars that make data analytics and AI methods practical and accessible. Join thousands of researchers and professionals who’ve advanced their careers with Statistical Horizons. Get $200 off any seminar with code DATA25 at https://statisticalhorizons.com

    34 min

  5. 25/11/2025

    Your AI Strategy is Burning Money: Here's How to Fix It (Ep.295)

    Most companies don't have an AI problem. They have a decision-making problem. Matt Lea, founder of Schematical and CloudWarGames, has spent nearly 20 years helping tech leaders ship smarter. In this conversation, he breaks down when AI actually makes sense, where AWS costs spiral out of control, and why your "cool demo" keeps dying before launch. If you're tired of AI hype and ready for straight answers, hit play. Join the conversation! Our Discord community is full of ML engineers, researchers, and AI enthusiasts discussing papers, sharing projects, and helping each other level up. Whether you're debugging your first neural net or training your tenth transformer, there's a place for you.      Newsletter https://datascienceathome.substack.com/subscribe Website https://datascienceathome.com   References http://schematical.com https://cloudwargames.com https://schematical.com/posts/we-need-ai_20241028

    32 min

  6. 11/11/2025

    From Tokens to Vectors: The Efficiency Hack That Could Save AI (Ep. 294)

    LLMs generate text painfully slow, one low-info token at a time. Researchers just figured out how to compress 4 tokens into smart vectors & cut costs by 44%—with full code & proofs! Meanwhile OpenAI drops product ads, not papers. We explore CALM & why open science matters. 🔥📊   Sponsors This episode is brought to you by Statistical Horizons  At Statistical Horizons, you can stay ahead with expert-led livestream seminars that make data analytics and AI methods practical and accessible. Join thousands of researchers and professionals who’ve advanced their careers with Statistical Horizons. Get $200 off any seminar with code DATA25 at https://statisticalhorizons.com

    47 min

  7. 30/10/2025

    Why AI Researchers Are Suddenly Obsessed With Whirlpools (Ep. 293)

    VortexNet uses actual whirlpools to build neural networks. Seriously. By borrowing equations from fluid dynamics, this new architecture might solve deep learning's toughest problems—from vanishing gradients to long-range dependencies. Today we explain how vortex shedding, the Strouhal number, and turbulent flows might change everything in AI.   Sponsors This episode is brought to you by Statistical Horizons  At Statistical Horizons, you can stay ahead with expert-led livestream seminars that make data analytics and AI methods practical and accessible. Join thousands of researchers and professionals who’ve advanced their careers with Statistical Horizons. Get $200 off any seminar with code DATA25 at https://statisticalhorizons.com     References https://samim.io/p/2025-01-18-vortextnet/

    33 min

  8. 16/10/2025

    The Scientists Growing Living Computers in Swiss Labs (Ep. 292)

    Fred Jordan, Co-CEO of FinalSpark, takes us inside the radical world of biological computing, where real neurons extracted from human tissue are being trained to solve problems that would require 10 megawatts in silicon. We explore the life support systems keeping these "wetware" processors alive, the ethical quandaries of computation performed by living cells, and why the messiness of biology might be exactly what AI needs next. From training cycles and reproducibility challenges to the surprising behaviors these neural networks display, Jordan paints a picture of 2030 where your devices might be powered by something closer to a brain than a chip.   Sponsors   This episode is proudly sponsored by Amethix Technologies. At the intersection of ethics and engineering, Amethix creates AI systems that don’t just function—they adapt, learn, and serve. With a focus on dual-use innovation, Amethix is shaping a future where intelligent machines extend human capability, not replace it. Discover more at https://amethix.com This episode is brought to you by Intrepid AI. From drones to satellites, Intrepid AI gives engineers and defense innovators the tools to prototype, simulate, and deploy autonomous systems with confidence. Whether it's in the sky, on the ground, or in orbit—if it's intelligent and mobile, Intrepid helps you build it. Learn more at intrepid.ai   References Website: finalspark.com Discord account:   / discord   Newsletter: https://finalspark.com/#newsletter   Topics: Biological computing • Neural engineering • Energy-efficient AI • Wetware vs hardware • The future of computation

    38 min
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Notes et avis

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3 notes

À propos

Cutting through AI bullsh*t. Come join the discussion on Discord! https://discord.gg/4UNKGf3

Informations

  • Création
    Francesco Gadaleta
  • Années d’activité
    2015 - 2026
  • Épisodes
    294
  • Classification
    Contenu explicite
  • Copyright
    © Copyright 2026 datascienceathome.com All rights reserved.
  • Site web de l’émission
    Data Science at Home

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