A collaborative approach to training AI models can yield better results, but it requires finding partners with data that ...
One of the key challenges of machine learning is the need for large amounts of data. Gathering training datasets for machine learning models poses privacy, security, and processing risks that ...
A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
As machine learning becomes more pervasive in the data center and the cloud there will be a need to share and aggregate information and knowledge but without exposing or moving the underlying data.
Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...
Let’s imagine a fictional company, Global Retail Corporation, a multinational retail chain struggling with its initial approach to AI integration. They built custom generative AI applications on their ...
FedCare delivers the first visual pipeline that pinpoints, classifies and mitigates FL failures in real time, cutting ...
The workflow of FTI-SLAM framework. The SLAM front-end comprises federated learning-enhanced deep neural networks for odometry, embedding, and loop closure detection. After optimising odometry based ...
Privacy-preserving AI technique enables researchers to improve cancerous brain tumor detection by 33%. SANTA CLARA, Calif.--(BUSINESS WIRE)--What’s New: Intel Labs ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback