Machine learning plays a key role in powering Twitter and our purpose of serving the public conversation. To continually advance the state of machine learning, inside and outside Twitter, we are building out a research group at Twitter, led by Sandeep Pandey, to focus on a few key strategic areas such as natural language processing, reinforcement learning, ML ethics, recommendation systems, and graph deep learning. We are excited to announce that, to help us get there, we have acquired Fabula AI (Fabula), a London-based start-up, with a world-class team of machine learning researchers who employ graph deep learning to detect network manipulation. Graph deep learning is a novel method for applying powerful ML techniques to network-structured data. The result is the ability to analyze very large and complex datasets describing relations and interactions, and to extract signals in ways that traditional ML techniques are not capable of doing.

Twitter announced on Monday it has acquired Fabula AI, a London-based machine learning research company. Fabula AI's team will join Twitter and work alongside Sandeep Pandey as part of Twitter's research group focused on natural language processing, reinforcement learning, machine learning ethics, recommendation systems and graph deep learning. Fabula's graph deep learning research is used to detect network manipulation. With this acquisition, Twitter aims to use Fabula's capabilities to better identify bad actors and malicious behavior on the platform, in addition to enhancing its recommendations processes. While the Fabula research team will initially focus on improving the health of conversations happening on Twitter, the company said the team's efforts will expand in the future, aiming to help stop spam and abuse, as well as improve recommendations, the explore tab and the onboarding experience.

Twitter announced that it has acquired London-based Fabula AI. The financial terms of transactions are not disclosed. The announcement stated that Twitter has established a research group lead by Sandeep Pandey. The research groups look into areas like natural language processing, reinforcement learning, ML ethics, recommendation systems, and graph deep learning. In one of the posts titled "Fake News revealed through artificial intelligence", it was revealed that Fabula AI team, Michael Bronstein, professor and researcher at the USI Institute of Computational Science (ICS), fellow ICS researchers Federico Monti and Dr Davide Eynard, developed a new method based on algorithms and artificial intelligence that could prove to be the most effective solution to the spreading of fake news through the Internet.

UK startup Fabula AI reckons it's devised a way for artificial intelligence to help user generated content platforms get on top of the disinformation crisis that keeps rocking the world of social media with antisocial scandals. Even Facebook's Mark Zuckerberg has sounded a cautious note about AI technology's capability to meet the complex, contextual, messy and inherently human challenge of correctly understanding every missive a social media user might send, well-intentioned or its nasty flip-side. "It will take many years to fully develop these systems," the Facebook founder wrote two years ago, in an open letter discussing the scale of the challenge of moderating content on platforms thick with billions of users. "This is technically difficult as it requires building AI that can read and understand news." But what if AI doesn't need to read and understand news in order to detect whether it's true or false? Step forward Fabula, which has patented what it dubs a "new class" of machine learning algorithms to detect "fake news" -- in the emergent field of "Geometric Deep Learning"; where the datasets to be studied are so large and complex that traditional machine learning techniques struggle to find purchase on this'non-Euclidean' space. The startup says its deep learning algorithms are, by contrast, capable of learning patterns on complex, distributed data sets like social networks.