Designed for Integration Across Compute Markets.

Edge devices operate under strict power, memory, and bandwidth constraints. Shifting environmental conditions require models to adapt locally without transmitting continuous raw sensor streams to the cloud.

Local on-chip learning (e-prop) and event-driven MIMD execution enable in-situ parameter updates in 142 µs, allowing real-time adaptation with minimal idle energy draw.

Demonstrated on single-core FPGA hardware: 142 µs adaptation latency; near-zero idle clock dissipation under sparse event streams.

Synthesizable processor IP core integrated into edge microcontrollers or smart sensor ASICs alongside standard host cores.

Advanced driver-monitoring systems (DMS) and multi-sensor fusion require sub-millisecond reaction times across diverse driving conditions, varying lighting, and non-stationary driver postures.

Event-driven asynchronous processing eliminates sequential clock pipeline delays. Persistent temporal context maintains driver behavioral states without massive memory buffers.

Microarchitecture synthesis validated across 16nm/28nm automotive-grade process flows; foundational algorithmic work shaped contributions to India's AIS-184 safety standard.

Specialized neural processing coprocessor connected via AXI5 to the primary automotive safety SoC or gateway domain controller.

Autonomous robots operating in dynamic physical environments must continuously predict physical state transitions and adapt to varying payloads, terrains, and actuator friction.

Hardware-resident recurrent state paths maintain second-long continuous physical context for predictive control, avoiding catastrophic forgetting across shifting motor control modes.

Hardware evaluation demonstrating <0.8% degradation across 50 sequential benchmark tasks with dual-tier consolidation replay.

Embedded adaptive compute tile integrated into motor controller ASICs or robotic joint microcontrollers for localized closed-loop control.

Monitoring high-frequency vibrational, acoustic, and thermal telemetry across industrial turbines and manufacturing plants requires detecting micro-anomalies that unfold over extended time horizons.

Multi-second temporal context window directly in silicon processes continuous time-series waveforms, distinguishing normal machine degradation from acute mechanical failure.

Acoustic signal classification verified under hardware evaluation; standard-cell synthesis validated across 45nm high-reliability industrial nodes.

Edge AI accelerator block within industrial IoT sensor nodes or PLC controller silicon.

Electronic warfare (EW), radar signal de-interleaving, and communication intelligence systems must filter agile, hostile jamming signals in dense electromagnetic environments without prior signal templates.

Fast on-the-fly synaptic plasticity adapts to newly observed frequency hopping and jamming patterns in microseconds, preserving mission continuity under active interference.

Underwent external hardware evaluation with Bharat Electronics Limited (BEL), including bitstream programming, execution, telemetry monitoring, and output verification.

Dedicated signal classification engine integrated into digital signal processor (DSP) ASICs, radar processing chiplets, or secure mission SoCs.

Battery-powered wearables require continuous monitoring of biometric signals (PPG, ECG, motion) without draining sub-100mAh batteries or overheating on skin contact.

Asynchronous event-driven architecture keeps execution clusters completely dormant between heartbeat pulses, drawing only microwatts of baseline standby power.

Verified standard-cell implementation flow targeting 7nm FinFET at 0.60 mm² die footprint; passive thermal profile between 30°C and 50°C during active inference.

Ultra-low-power neural coprocessor macro integrated alongside Bluetooth LE / MCU controllers in wearable health silicon.

Emerging AI paradigms like World Models and Joint Embedding Predictive Architectures (JEPA) require continuous predictive state estimation of physical environments, which exhausts conventional GPU memory bandwidth.

Maintains latent temporal representations in fused silicon registers without continuous read/write cycles to external DRAM or bulky KV caches.

Zero-shot cross-modal representation transfer demonstrated on hardware evaluation with 0.0 ms transfer latency between abstract temporal domains.

Accelerated temporal processing subsystem within heterogeneous AI server chiplets or robotic world-model processors.