How can we democratize machine learning on IoT devices

| February 12, 2020

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TinyML, as a concept, concerns the running of ML inference on Ultra Low-Power (ULP 1mW) microcontrollers found on IoT devices. Yet today, various challenges still limit the effective execution of TinyML in the embedded IoT world. As both a concept and community, it is still under development.Here at Ericsson, the focus of our TinyML as-a-Service (TinyMLaaS) activity is to democratize TinyML, enabling manufacturers to start their AI businesses using TinyML, which runs on 8, 16 and 32 bit microcontrollers.Our goal is to make the execution of ML tasks possible and easy in a specific class of devices. These devices are characterized by very constrained hardware and software resources such as sensor and actuator nodes based on these microcontrollers.Below, we present how we can bind the as-a-service model to TinyML. We will provide a high-level technical overview of our concept and introduce the design requirements and building blocks which characterize this emerging paradigm.

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BADR provides end-to-end data-driven solutions and software engineering services. We are accelerating the process of building an affordable coherent software team with the right skills.We believe that Knowledge beats Gut feeling, and reliance on real Data is the only way to efficient decision making.

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Predictive analytics can help financial institutions and customers detect fraud, financial management, predicting markets, improving products, better user experience, etc. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "Is predictive analytics is the future of finance?", "acceptedAnswer": { "@type": "Answer", "text": "Predictive analytics is called the ‘future of financial software,’ which means it can provide accurate planning and cost-effectiveness." } },{ "@type": "Question", "name": "How can analytics be used in finance?", "acceptedAnswer": { "@type": "Answer", "text": "Analytics helps in predicting revenue, improve supply chains, identify trouble spots, understand where the company is bleeding money, and fraud detection." } },{ "@type": "Question", "name": "How do predictive analytics benefit financial institutions?", "acceptedAnswer": { "@type": "Answer", "text": "Predictive analytics can help financial institutions and customers detect fraud, financial management, predicting markets, improving products, better user experience, etc." } }] }

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BADR

BADR provides end-to-end data-driven solutions and software engineering services. We are accelerating the process of building an affordable coherent software team with the right skills.We believe that Knowledge beats Gut feeling, and reliance on real Data is the only way to efficient decision making.

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