Speaker: Daniela Braga (CEO of DefinedCrowd)
Date: Tuesday, Jan 24
Room: NSH 1507
DefinedCrowd was born out of the founder’s personal frustration around data quality and slowness when dealing with data providers. Artificial Intelligence is next big technology milestone which replaces humans in menial tasks, giving us more time to enjoy more human-human interactions and focus on the really creative tasks. But to achieve this technology leap, two things are required: high quality training data and state-of-the-art machine learning algorithms. In this talk, I will walk through the reasons behind the creation of DefinedCrowd and how we are solving the data quality problem faster and at scale, by combining the latest methodologies on crowdsourcing with machine learning. DefinedCrowd is a global company headquartered in Seattle, WA, with an R&D center in Lisbon, Portugal, graduated from the Microsoft Seattle Accelerator in Machine Learning (with less than 1% of acceptance rate and recognized by Microsoft as one of the fastest growing companies in the space) and which raised $1.1 M seed round in September 2016 from Amazon, Sony and Portugal Ventures. DefinedCrowd was also featured in http://www.inc.com/lisa-calhoun/7-artificial-intelligence-startups-to-watch-in-2017.html as one of the 7 AI companies to watch in 2017.
Founder and CEO of DefinedCrowd, one of the fastest growing startups in the AI space. With seventeen years working in Speech Technology both in academia and industry in Portugal, Spain, China and the US, Daniela Braga has deep expertise in Speech Science and is one the world leaders of Crowdsourcing adoption in large enterprises. Previously at Microsoft worked in pretty much all stacks of Speech Technology and shipped 26 languages for Exchange 14, 10 TTS voices in Windows 8 and was involved in Cortana. At Voicebox, created the Data Science and Crowdsourcing team, where she introduced Crowdsourcing for big data solutions and re-structured the Engineering infrastructure around data collection, processing, ingestion, instrumentation, storage, browsing and discoverability. Her effort has resulted in reducing data collection and processing costs by 80%; her approach has been adopted in multiple organizations. Dr. Braga is oftentimes guest lecturer in the University of Washington, USA, is the author of more than 90 scientific papers and several patents.