Machine's Learning is a daily podcast produced entirely by AI — two AI hosts in conversation about one fresh paper from machine learning and AI research, translated for thoughtful listeners who don't need a PhD to be curious about where the field is going. One paper per episode, no math required, every cross-domain connection drawn to a universally accessible field (history, biology, medicine, environment) so anyone can follow. By AI, about AI, for humans.
Machine's Learning
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41 episodes
Updated Daily
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Podcast Overview
Machine's Learning is a daily podcast produced entirely by AI — two AI hosts in conversation about one fresh paper from machine learning and AI research, translated for thoughtful listeners who don't need a PhD to be curious about where the field is going. One paper per episode, no math required, every cross-domain connection drawn to a universally accessible field (history, biology, medicine, environment) so anyone can follow. By AI, about AI, for humans.
Language
🇺🇲
Publishing Since
4/29/2026
1 verified contact email on file for Machine's Learning
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Recent Episodes
June 15, 2026
EP041 — The Conversation You Can No Longer Read (Beyond Tokens)
When two AI agents cooperate, they usually type full sentences at each other — which quietly means a human can read along. Today's paper is a survey mapping the fast-growing alternative: agents passing their raw internal numbers directly, skipping words entirely. It's cheaper and loses less, but the channel becomes something no human can read — which doesn't solve the oversight problem so much as move it somewhere harder. The cross-domain parallel is shorthand: compressed for speed and readable only if you know the system — except a latent channel may have no words underneath it at all. Machine's Learning is a Plumbline Tools production. Support the show: https://plumbline.tools/podcast/
June 14, 2026
EP040 — Plan the Camps, Not the Climb (FF-JEPA)
A world model lets an AI imagine the future and plan by searching through it — but the imagined future falls apart the further ahead it looks, a failure called long-horizon collapse. FF-JEPA fixes it with a second, action-free model: a latent planner that proposes where to head next (a subgoal) rather than how to get there, so one impossibly long plan becomes a chain of short, reachable legs — and it needs no explicit goal image. The cross-domain parallel is siege-style mountaineering: a chain of camps, each sited to be reachable from the one below, with the climbing between solved locally — except a climber can see the real face, while the planner sites its camps inside its own imagined map and can mark one on a ledge that doesn't exist. Machine's Learning is a Plumbline Tools production. Support the show: https://plumbline.tools/podcast/
June 12, 2026
EP039 — Where the Ice Stops and the Water Starts (Stefan-CL)
Teach a neural network a new task and it tends to forget the old one — the stability-plasticity dilemma. A single-author paper called Stefan-CL borrows its whole method from the physics of freezing water: treat learned knowledge as solid ice, spare capacity as liquid, and let the boundary between them move outward as the network learns, freezing what it knows so new learning can't overwrite it — driving forgetting near zero without storing any old data. The cross-domain parallel is the Stefan moving-boundary problem from solidification physics, where the catch is that real freezing fronts don't stay smooth — they branch into frost-ferns. Machine's Learning is a Plumbline Tools production. Support the show: https://plumbline.tools/podcast/
41 total episodes available
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Frequently asked questions
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- What is Machine's Learning?
- How often does this podcast release new episodes?
This podcast updates daily.
- Where can I listen to this podcast?
This podcast is available on 4 platforms including Apple Podcasts, Spotify, and more. You can also use the RSS feed directly.
- Does this podcast accept guests?
No, this podcast does not typically feature guests.
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