Deci.AI’s founders Jonathan Elial COO (left), Yonatan Giefman CEO and Ran El Yaniv- Chief scientist. – Credit Deci
Microsoft is looking to Israel’s Deci.AI as an alternative to Sam Altman’s OpenAI. Globes reported that sources “close to the matter” said Microsoft is expanding its collaboration with the Israeli deep learning company that utilizes Artificial Intelligence (AI) to build AI.
Deep learning is a machine learning technique that teaches computers to do what comes naturally to humans: learn by example.
It makes sense that Microsoft, which is one of the main backers of OpenAI, is looking to hedge its bets, so to speak. OpenAI has been the center of a great deal of controversy recently. The company is being sued by writers like John Grisham, Game of Thrones author George R.R. Martin and many others over copyright infringement.
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Elon Musk, one of OpenAI’s founders, is also suing the company for breach of contract charging that the company has failed to live up to its found principle of working, “for the benefit of humanity broadly.”
Then there was all of the drama surrounding last year’s firing then rehiring of Sam Altman in just a few day period.
Founded in 2019 by CEO Dr. Yonatan Geifman, Ran El-Yaniv, and COO Jonathan Elial, a former senior Google researcher, 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.
While GPUs have traditionally been the hardware of choice for running convolutional neural networks (CNNs), explains Deci, CPUs, already more commonly utilized for various computing tasks, would serve as a much cheaper alternative. Although it is possible to run deep learning inference on CPUs, generally they are significantly less powerful than GPUs. Consequently, deep learning models typically perform 3-10X slower on a CPU than on a GPU.
Deci says that its tech closes the gap significantly between GPU and CPU performance for CNNs and it boasts that tasks that previously could not be carried out on a CPU because they were too resource intensive are now possible.
Deci.AI has been making a number of moves lately.
In January, Deci.AI entered a collaboration with Qualcomm Technologies, Inc. to introduce advanced Generative Artificial Intelligence (AI) models tailored for the Qualcomm Cloud AI 100, Qualcomm Technologies’ performance and cost-optimized AI inference solution designed for Generative AI and large language models (LLMs).
