Israeli deep learning company Deci announced last Wednesday that it raised $25 million in Series B funding. The company strives to harness artificial intelligence to solve the problem of artificial intelligence efficiency.
The funding round was led by global software investor Insight Partners and was completed by existing investors Square Peg, Emerge, Jibe Ventures and Fort Ross Ventures, as well as new investor ICON.
Following a $21 million Series A funding round announced just seven months ago, the investment brings Deci’s total capital to $55.1 million.
The company hopes to use the newly acquired funding to expand its go-to-market activities and accelerate its R&D efforts.
Founded by Yonatan Geifman, Ph.D., Jonathan Elial, and Professor Ran El-Yaniv in 2019, Deci strives to advance deep learning and eliminate production bottlenecks throughout of the AI lifecycle. The company aims to minimize the AI efficiency gap – a phenomenon in which hardware is unable to meet the increasing demands of models – which hinders greater commercialization of AI. Unfettered advances in AI based on deep learning have the potential to revolutionize a wide range of industries, including medicine, manufacturing, transportation, retail, and communication.
“The growing gap in AI efficiency only further underscores the importance of ‘shifting left’ – taking into account production considerations early in the development lifecycle, which can then reduce considerably the time and cost involved in resolving potential roadblocks when deploying models into production,” Yonatan said. Geifman, CEO and co-founder of Deci. “Deci’s deep learning development platform has a proven track record of enabling companies of all sizes to do just that by providing them with the tools they need to successfully develop and deploy breakthrough AI solutions, regardless of regardless of the level of complexity or the production environment. This funding is a vote of confidence in our work to make AI more accessible and scalable for everyone.
Deci is tackling the inefficiencies of AI with its deep learning platform that helps data scientists adopt a more productive development paradigm. Through the platform, AI developers can leverage hardware-enabled Neural Architecture Search (NAS) to create deep learning models optimized for specific production goals. According to the company, the platform offers superior AI performance at reduced operational costs, reduced time to market and new applications. The platform is powered by Deci’s proprietary AutoNAC (Automated Neural Architecture Construction) technology, an algorithmic optimization engine that allows data scientists to build deep learning models suitable for any task, together of data and target inference material.
Deci aims to democratize NAS technology – a field previously confined to academia or industry giants (like Google) due to high costs. Deci recently announced version 2.0 of its platform to continue helping companies build, optimize, and deploy high-quality computer vision models.
“Having a more efficient infrastructure for AI systems can make AI products qualitatively different and better, not just cheaper and faster to run,” said Lonne Jaffe, Insight Partners managing director and board member. of Directors of Deci. “Deci’s powerful technology allows you to input your AI models, data, and target hardware – whether that hardware is at the edge or in the cloud – and guides you in finding alternative models that will generate similar predictive accuracy. with vastly improved efficiency. We are very excited to double our investment in Deci, supporting Yonatan and the team as they bring this essential technology to AI builders across the globe.