Data Science Investment Counter —Funding raised by UK data science companies in 2018.
£ 5.640 Million

Twitter acquires fake-news spotting startup Fabula AI

Twitter has bought London-based startup Fabula AI, a company using machine learning (ML) to tackle fake news online.

Although the terms of the agreement have not been made public, it would appear that Fabula is more of an acqui-hire than an acquisition, with the team joining Twitter’s Cortex unit, the social network in-house group of researchers and engineers working on machine learning tech.

According to Twitter, a part of the team will now focus on machine learning applications in natural language processing (NLP), reinforcement learning, recommendations systems and graph deep learning. According to the same source, the new team will also focus on ML ethics.

‘We are really excited to join the ML research team at Twitter, and work together to grow their team and capabilities.” said Michael Bronstein, Fabula co-founder and leader of the new machine learning team at Twitter, “specifically, we are looking forward to applying our graph deep learning techniques [for] improving the health of the conversation across the service.’

Fabula was co-founded in 2018 by Michael Bronstein, Damon Mannion, Ernesto Schmitt and Federico Monti. The company uses  “geometric deep learning” to distinguish facts from fake news on social media.

“As this technology detects the spread pattern, it is language and locale independent; in fact, it can be used even when the content is encrypted,” Fabula says on its homepage. “We also believe that such an approach, given it is based on the propagation pattern through huge social networks, is far more resilient to adversarial attacks.”

The news comes after Twitter receiving harsh criticism about how the platform is used to share fake news on the web. Fabula AI’s acquisition will help Twitter to help “improve the health of the conversation” on the social network, according to CTO Parag Agrawal.

“By studying and understanding the Twitter graph, comprised of the millions of tweets, retweets and likes shared on Twitter every day, we will be able to improve the health of the conversation, as well as products including the timeline, recommendations, the explore tab and the onboarding experience,” he said.

“Machine learning plays a key role in powering Twitter and our purpose of serving the public conversation,” Agrawal concluded.

Image via Pixabay.

SHARE THIS ARTICLE:
BY SHACK15

Co-working space and blog dedicated to all things data science.

Subscribe to our newsletter