Skip to main content

Envisioning is an emerging technology research institute and advisory.

LinkedInInstagramGitHub

2011 — 2026

research
  • Observatory
  • Newsletter
  • Methodology
  • Origins
  • Vocab
  • RSS Feeds
services
  • Signals Session
  • Bespoke Projects
  • Build Sessions
  • Pricing
  • Use Cases
  • Signals
  • Free scan↗free
impact
  • ANBIMAFuture of Brazilian Capital Markets
  • IEEECharting the Energy Transition
  • Horizon 2045Future of Human and Planetary Security
  • WKOTechnology Scanning for Austria
solutions
  • Innovation
  • Strategy
  • Consultants
  • Foresight
  • Associations
  • Governments
  • L&D
resources
  • Partners
  • Coding for Non-Coders
  • How We Work
  • Data Visualization
  • Multi-Model Method
  • FAQ
  • Security & Privacy
  • Public Sector
about
  • Manifesto
  • Community
  • Events
  • Support
  • Contact
ResearchServicesSignalsAbout
ResearchServicesSignalsAbout
  1. Home
  2. Research
  3. Substrate
  4. AI Chip Design

AI Chip Design

Korean companies including Samsung, Rebellions, Sapeon, and FuriosaAI are developing custom AI accelerator chips to reduce dependence on Nvidia GPUs for domestic AI workloads.

Geography: Asia Pacific · East Asia · South Korea

Back to SubstrateBack to South KoreaView interactive version

Several Korean companies are designing custom AI accelerator chips: Rebellions (ATOM chip for data center inference), Sapeon (Samsung spin-off building NPUs), FuriosaAI (low-power inference accelerators), and Samsung's own Exynos NPU division. The Korean government's AI Semiconductor Initiative provides R&D funding and guaranteed procurement for domestic AI chips in government data centers.

Korea's AI chip ambitions are partly motivated by supply security — Korean AI companies found themselves competing with global hyperscalers for scarce Nvidia GPUs during the AI boom of 2023-2025. Building domestic AI accelerators ensures that Korean sovereign AI models can train and run on Korean silicon, reducing a critical foreign dependency.

Rebelions' ATOM chip, fabricated at Samsung Foundry on 5nm, is designed for transformer inference workloads and claims competitive performance-per-watt with Nvidia's inference GPUs. FuriosaAI targets edge AI applications in autonomous driving and industrial automation. While none of these chips threaten Nvidia's training GPU dominance, they represent Korea's effort to own more of the AI value chain beyond memory — moving from supplying HBM to Nvidia to building complete AI compute solutions.

TRL
6/9Demonstrated
Impact
2/5
Investment
4/5
Category
Hardware

Research this in Signals

Scan AI Chip Design for yourself.

Signals turns a topic into a sourced research record you can inspect and rerun. Your first scan is free, and this one starts with AI Chip Design already loaded, so edit it or scan as is.