Current applications
- Data-centre AI accelerators
- On-device neural processors
- Application-specific inference chips
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Compute Fabric
Applied technology
Compute Fabric
Core AI Compute Silicon — GPU, NPU, TPU & ASIC
Purpose-built processors turn AI workloads into scalable, energy-aware computing infrastructure.
Technology in practice
Where the system is applied—and what enables it.
This page maps a technology domain relevant to FUURAA’s long-term mission. It does not claim a current FUURAA product, service or partnership.
Enabling technology stack
- Tensor and matrix processing units
- Advanced packaging and chiplets
- Low-precision and mixed-precision computing
Technology trajectory
Current capability, scaling frontier and long horizon.
The group trajectory describes a directional maturity view, not a deployment commitment.
Current landscape
Accelerators support model training, inference and domain-specific AI services across cloud and edge systems.
Scaling frontier
Heterogeneous processors will be orchestrated as shared compute pools optimised for workload, latency and energy.
Long-horizon direction
Compute may become increasingly specialised, modular and co-designed with models, memory and networks.
Technology group
Compute Fabric
The silicon, memory, networks and physical systems that turn intelligence into dependable capacity.
CurrentEstablishedScalingAcceleratingLong horizonFrontier
Related technologies
More from Compute Fabric.
AI Servers & Intelligent Compute Clusters
Cluster architecture converts individual accelerators into dependable infrastructure for large-scale AI.
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Advanced Memory & High-Speed Interconnects — HBM, NVLink & InfiniBand
Memory bandwidth and interconnect efficiency determine how effectively large AI systems can use compute.
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Edge & On-Device AI — AI PCs, Phones & Smart Glasses
Local intelligence improves latency, privacy, resilience and access when cloud connectivity is limited.
Explore technology →What We Build