Episode

What Comes After GPUs? Great Sky’s Bet on Brain-Like AI

Podcast
The Neuron: AI Explained
Published
May 27, 2026
Duration seconds
3594
Processing state
not_requested
Canonical source
https://podcasters.spotify.com/pod/show/the-neuron/episodes/What-Comes-After-GPUs--Great-Skys-Bet-on-Brain-Like-AI-e3jvk4j
Audio
https://anchor.fm/s/f51d3fd0/podcast/play/120622675/https%3A%2F%2Fd3ctxlq1ktw2nl.cloudfront.net%2Fstaging%2F2026-4-27%2F424997359-44100-2-dbc56e08c1d4c.mp3
JSON
/v1/public/podcasts/the-neuron-ai-explained-6886341/episodes/what-comes-after-gpus-great-sky-s-bet-on-brain-like-ai
Markdown
/podcast/the-neuron-ai-explained-6886341/what-comes-after-gpus-great-sky-s-bet-on-brain-like-ai.md

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Summary

What if the next big AI breakthrough is not a bigger model, but a completely different kind of computer? Jeff Shainline, co-founder and CEO of Great Sky, joins The Neuron to explain how his team is building brain-inspired AI hardware using superconductors, photonics, and analog computation. Great Sky’s architecture, called Superconducting Optoelectronic Networks, or SOENs, is designed to move beyond the traditional GPU roadmap by co-locating memory and processing, communicating with light, and mimicking some of the high-connectivity dynamics found in biological brains. In this conversation, Jeff breaks down why today’s chips can struggle with fast, multimodal inference; why transformers may be powerful but inefficient for some future workloads; how Great Sky’s system differs from quantum computing; and why early applications could include fusion reactors, particle physics, video understanding, content moderation, and eventually new model architectures that do not map neatly onto today’s hardware. Subscribe to The Neuron for grounded, practical conversations about where AI is going next—and what actually has to work before the hype becomes real.