Deci: Using AI to craft the next generation of deep learning

After recently raising US$25mn, we take a look at how Deci uses its deep learning platform to help companies transform AI

Founded in 2019, Deci is a deep learning company that harnesses AI to help solve an AI efficiency gap. 

It has created a development platform for deep learning aimed at making it easy for AI developers to build, optimise and then deploy their models quickly, in the cloud, at the edge or on mobile devices.

Deci’s deep learning development platform is powered by Deci’s proprietary AutoNAC (Automated Neural Architecture Construction) technology, an algorithmic optimisation engine that empowers data scientists to build best-in-class deep learning models that are tailored for any task, data set and target inference hardware. 

“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,” Yonatan Geifman, CEO and co-founder of Deci. 

Solving the growing AI efficiency gap

Deci recently announced it has raised US$25mn in a Series B funding round, which comes seven months after Deci secured US$21mn in Series A funding, bringing Deci’s total funding to US$55.1mn. 

The funds will be used to expand Deci’s go-to-market activities, as well as further accelerate the company’s R&D efforts.

According to Deci, deep learning-powered advancements in AI have led to innovations that have the potential to revolutionise services, products, and consumer applications. However, the AI efficiency gap, a situation in which hardware is unable to meet the increasing computing demands of models that are growing in size and complexity, has proven to be an obstacle to more widespread AI commercialisation. 

“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. 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,” said Geifman, CEO and co-founder of Deci. 

Deci’s deep learning platform helps data scientists eliminate the AI efficiency gap by adopting a more productive development paradigm. With the platform, AI developers can leverage hardware-aware Neural Architecture Search (NAS) to quickly build optimised deep learning models that are designed to meet specific production goals.

Share

Featured Articles

Pick N Pay’s Leon Van Niekerk: Evaluating Enterprise AI

We spoke with Pick N Pay Head of Testing Leon Van Niekerk at OpenText World Europe 2024 about its partnership with OpenText and how it plans to use AI

AI Agenda at Paris 2024: Revolutionising the Olympic Games

We attended the IOC Olympic AI Agenda Launch for Olympic Games Paris 2024 to learn about its AI strategy and enterprise partnerships to transform sports

Who is Gurdeep Singh Pall? Qualtrics’ AI Strategy President

Qualtrics has appointed Microsoft veteran Gurdeep Singh Pall as its new President of AI Strategy to transform the company’s AI offerings for customers

Should Tech Leaders be Concerned About the Power of AI?

Technology

Andrew Ng Joins Amazon Board to Support Enterprise AI

Machine Learning

GPT-4 Turbo: OpenAI Enhances ChatGPT AI Model for Developers

Machine Learning