Archives for self supervised learning - Page 2


Meta announced project CAIRoke, an end-to-end neural model for building on device systems, to help deliver better dialogue capabilities, true world creation, and exploration.


Meta announced project CAIRoke, an end-to-end neural model for building on device systems, to help deliver better dialogue capabilities, true world creation, and exploration.


Meta is coming up with their first conference detailing their progress of the metaverse after the major rebranding from Facebook. The virtual event ‘Inside the lab: Building for the metaverse with AI’ will be held on February 23 at 10:30 PM (IST) and have speakers across the AI board. The opening and closing notes will […]


graph structure has much additional information with them like node attributes, and label information of nodes. Using this source of information, we can have unprecedented opportunities to design advanced level self-supervised pretext tasks


in the self supervised learning process we are mainly focused about making the data workable to the downstream algorithms. but when using the self-supervised learning we make the data specifically for classification we can say the process is self-supervised classification.
Explainability is emerging for many domains such as medical imaging, assisted driving, and manufacturing defect detection.
Explainability is emerging for many domains such as medical imaging, assisted driving, and manufacturing defect detection.


Facebook believes that self-supervision is one step on the path to human-level intelligence.


Contrastive learning can be applied to both supervised as well as self-supervised settings.


For instance, Facebook AI Research (FAIR) has been championing self-supervised learning (SSL) for quite some time.