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Maluuba

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Revolutionize your work and learning with Maluuba, an AI-powered platform. Automate tasks, enhance productivity, and develop custom applications with ease. Join a community of developers to collaborate and share AI models. Empower yourself to solve real-world problems with intuitive tools.

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What is Maluuba?

Maluuba is a cutting-edge AI-powered platform that aims to transform the way individuals work and learn. It presents a comprehensive set of tools that empower users to streamline their workflow by automating repetitive tasks and boosting overall productivity. With Maluuba, users can effortlessly build, refine, and implement AI-driven bots and intelligent assistants. Moreover, they have access to a vast library of pre-built AI models and algorithms, which can be leveraged to develop customized applications. The platform also fosters collaboration among developers, providing them with an avenue to share and collaborate on their AI models and applications. Maluuba is driven by the vision of empowering individuals to utilize and create AI solutions to tackle real-world challenges. It offers a user-friendly interface and intuitive tools that facilitate a seamless onboarding experience and rapid development of solutions. By utilizing Maluuba, users can effortlessly create and deploy AI-powered applications capable of comprehending natural language, offering proactive insights, and automating tasks. Furthermore, users have the opportunity to collaborate with others, enabling them to collectively build and distribute AI models and applications.

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Maluuba FQA

  • What is the focus of Microsoft Research Montréal lab?icon plus
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Maluuba Use Cases

Maluuba is a product developed by Microsoft Research Lab - Montréal.

The lab focuses on advancing the state-of-the-art in deep learning and machine learning.

The lab collaborates with the academic community and partners with Mila (Montréal Institute of Learning Algorithms) and Professor Yoshua Bengio.

The lab's research areas include fairness, accountability, transparency, and ethics in AI (FATE), reinforcement learning, and language for learning and interaction.

The lab has published several notable research papers on deep learning and text matching algorithms.

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