Deci, an Israeli startup that offers an artificial intelligence AI deep learning platform that it says harnesses AI to solve the AI efficiency gap, raised $25 million in a Series B funding round led by global software investor Insight Partners. Deci’s total funding to date has now reached $55.1 million.
Deep learning is also known as deep structured learning. It is part of a larger group of machine learning methods that are based on artificial neural networks with representation learning. Learning can be supervised, semi-supervised or unsupervised.
NVidia explains Deep learning is a subset of AI and machine learning that uses multi-layered artificial neural networks to deliver state-of-the-art accuracy in tasks such as object detection, speech recognition, language translation, and others.
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Deep learning differs from traditional machine learning techniques in that they can automatically learn representations from data such as images, video or text, without introducing hand-coded rules or human domain knowledge. Their highly flexible architectures can learn directly from raw data and can increase their predictive accuracy when provided with more data.
Amazon explains that organizations are increasingly turning to deep learning because it allows computers to learn independently and undertake tasks with little supervision, promising extraordinary benefits for both science and industry. Unlike traditional machine learning, deep learning attempts to simulate the way our brains learn and process information by creating artificial “neural networks” that can extract complicated concepts and relationships from data. Deep learning models improve through complex pattern recognition in pictures, text, sounds, and other data to produce more accurate insights and predictions.
Founded in 2019 by Yonatan Geifman, Ran El-Yaniv, and Jonathan Elial, Deci offers an end-to-end deep learning acceleration platform, which the company says allows AI developers “build, optimize, and deploy faster and more accurate models for any environment, including cloud, edge, or mobile.”
The platform is powered by Deci’s Automated Neural Architecture Construction (AutoNAC) technology, an algorithmic optimization engine that squeezes maximum utilization out of any hardware. The AutoNAC engine contains a Neural Architecture Search (NAS) component that redesigns a given trained model’s architecture to optimally improve its inference performance (throughput, latency, memory, etc.) for specific target hardware while preserving its baseline accuracy.
“The growing AI efficiency gap only further highlights the importance of ‘shifting left’ – accounting for production considerations early in the development lifecycle, which can then significantly reduce the time and cost spent on fixing potential obstacles when deploying models in production,” said Yonatan Geifman, CEO and co-founder of Deci. “Deci’s deep learning development platform has a proven record of enabling companies of all sizes to do just that by providing them with the tools they need to successfully develop and deploy world-changing AI solutions – no matter the level of complexity or production environment. This funding is a vote of confidence in our work to make AI more accessible and scalable for all.”