The Linux Foundation Deep Learning Foundation (LF DLF) has announced five new members: Ciena, DiDi, Intel, Orange and Red Hat.
As an umbrella organization of The Linux Foundation itself, the LF DLF supports and sustains open source innovation in Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL).
What is Deep Learning?
Deep Learning is defined as an aspect of AI that is concerned with emulating the learning approach that human beings use to gain certain types of knowledge. It can be thought of as a way to automate predictive analytics and is also sometimes known as deep structured learning or hierarchical learning.
Deep Learning concerns ‘learning data representations’ as opposed to ‘task-specific algorithms’.
It can be supervised, semi-supervised or unsupervised and can be used to build architectures such as deep neural networks, deep belief networks and recurrent neural networks that have been used in fields including computer vision and speech recognition etc.
AI model discovery
The Linux Foundation says that these new members will provide additional resources to the community to develop and expand open source AI, ML and DL projects, such as the Acumos AI Project, the foundation’s platform for AI model discovery, development and sharing.
These companies join founding members Amdocs, AT&T, B.Yond, Baidu, Huawei, Nokia, Tech Mahindra, Tencent, Univa and ZTE.
Chief operating officer of The Linux Foundation Lisbeth McNabb makes it clear that the LF Deep Learning Foundation is a neutral space for harmonisation and acceleration of separate technical projects focused on AI, ML and DL technologies.
“Deep learning has the potential to change everything about how we learn from data,” said Chris Wright, VP & CTO at Red Hat. “Open source communities are at the heart of advancing deep learning frameworks and we’re excited to see further collaboration with the LF Deep Learning Foundation around model discovery, development and lifecycles… and bringing open source software development best practices to deep learning models.”
Good developments in Deep Learning then… almost good enough to help us calculate the answer to life, the universe and everything?
No need to bother, we already know that the answer is still 42, right?