low-power-ai
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The Camera That Was Asked to Think for Itself
Pilot AI taught ordinary cameras to recognize what they saw without waiting for the cloud. Its quiet wager on efficient software carried it from drone experiments to consumer devices, defense imagery, and a 2022 acquisition.
The AI Chip Company That Sells No Chips
Expedera’s founders looked at neural networks and saw an old networking problem. Their answer is a packet-based engine that chipmakers can license, resize and tuck into everything from phones to cars.
CyberSwarm Inc.
CyberSwarm is a neuromorphic engineering company building brain-inspired, memristor-based hardware that lets machines learn and adapt locally, at the edge, without the cloud. Founded in 2017 by Mihai Raneti and headquartered in San Mateo, California with R&D roots in Ploiesti, Romania, the company is developing a neuromorphic System-on-a-Chip for cybersecurity and energy-efficient AI, positioning its architecture as a new computational layer between conventional digital systems and quantum computing. In May 2026 it raised a $50 million Series A to scale toward commercial deployment across automotive, aerospace, defense, healthcare and robotics.
DEEPX
DEEPX is a South Korean fabless semiconductor startup building ultra-low-power neural processing units (NPUs) for on-device and edge AI. Founded in 2018 by former Apple chip designer Lokwon Kim, the company designs AI accelerators - led by its 25 TOPS DX-M1 chip - that run vision and generative AI models at under 5 watts, aiming to move intelligence out of the data center and into robots, cameras, factories, mobility and everyday devices. It raised an $80.5M Series C in 2024 at a $529M valuation and positions itself as a 'Physical AI infrastructure company.'
ModelCat AI
ModelCat AI, formerly the low-power chip pioneer Eta Compute, builds an agentic, hardware-aware platform that automatically designs, trains, optimizes and validates machine-learning models for embedded, edge and IoT devices. Its patented AI-in-the-Loop workflow, backed by a physical hardware farm that calibrates results against real silicon, compresses a model-development cycle that once took 12 to 24 months down to a matter of days. The Sunnyvale company works with chipmakers including NXP and Alif Semiconductor to hand developers ready-to-run models tuned to the exact constraints of the hardware they will run on.
Applied Brain Research
Applied Brain Research (ABR) is a Waterloo, Ontario AI hardware company spun out of the University of Waterloo's Centre for Theoretical Neuroscience. It builds brain-inspired chips and software that run real-time AI - full-vocabulary speech recognition, text-to-speech and sensor processing - directly on edge devices at power levels measured in milliwatts. Its patented state-space models and the Legendre Memory Unit power the TSP1 Time Series Processor, which ABR calls the world's first single-chip solution for full-vocabulary speech recognition, doing the work of cloud voice AI while consuming 10 to 100 times less power.
EnCharge AI
EnCharge AI is a Santa Clara semiconductor startup, spun out of Princeton University, building AI accelerator chips based on analog in-memory computing. Its charge-based architecture runs heavy AI workloads on laptops, workstations and edge devices at roughly 20x the energy efficiency of conventional GPUs. Its first product, the EN100 accelerator, delivers 200+ TOPS within an 8.25W power budget, aiming to move generative AI out of the data center and onto the devices people actually hold.