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Neuromorphic Computing Startups in Europe

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Neuromorphic Computing startups in Europe

There are 24 Neuromorphic Computing startups in Europe which include Innatera, Plumerai, XMOS, SpiNNcloud, Polyn. Out of these, 14 startups are funded, with 4 having secured Series A+ funding.
Over the past 10 years, an average of 1 new company has been launched annually. Notably, several of these startups have been founded by alumni of Harvard Business School, Harvard University and London Business School (LBS).

Here is the list of top Neuromorphic Computing startups in Europe

Provider of neuromorphic microprocessors. It leverages a computing system called spiking neural network to encode voltage spikes, realize its cognitive functions, and to encode sensor information through which the processor can mimic the brains mechanisms.

Key facts about Innatera

Provider of a deep learning solution to enable inference on edge devices. Offers a solution that makes small machines intelligent by enabling them to use deep learning locally and in real-time for automated warehouses, retail, smart cameras, micromobility, and other applications. Also offers an ecosystem of open-source Python packages for building, training, and deploying BNNs.

Key facts about Plumerai

3. XMOS

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Developer of cycle-accurate software programmable processors and related solutions. It offers processors, voice and audio interfaces, and development tools. The company provides solutions for audio, collaboration, motor and motion control, voice AI, and security applications. Its processors are used in consumer, industrial, and automotive sectors. The company also provides direct support, training, evaluation kits, and software components.

Key facts about XMOS

Developer of infrastructure solutions for new-generation artificial intelligence. The company focuses on brain-inspired computing architecture designed for sparse algorithms. Its systems are designed to be scalable and energy-proportional.

Key facts about SpiNNcloud

Developer of AI-based IP cores for neuromorphic analog signal processing chips. Its features include direct analog and digital inputs, running of deep neural networks, neuromorphic architecture, asynchronous processing, pre-trained artificial neural networks, sensor MCUs, and prototyping on neural net models. The applications of the chips include fitness trackers, smartwatches, health monitoring devices, remote care for the elderly.

Key facts about Polyn

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