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How a Wildlife AI Platform Solved its Data Challenge - InformationWeek

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Anyone working in data management and data science can attest to the challenge and time-consuming nature of mapping a set of data from a new source into a platform where it can be cleaned, validated, and ultimately analyzed and used to train algorithms. After all, your algorithms are only as good as the data used to train them. Now imagine if these data sets are coming from hundreds of external users who have employed any number of systems to collect this data, from Excel files to actual shoeboxes full of photos. That is the challenge that non-profit wildlife conservation machine learning and artificial intelligence service provider Wild Me has faced over its more than a decade of operation. The organization builds open software and AI for the conservation research community.


The 'Rage Design' Behind Flatfile's Onboarding Success

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David Boskovic was excited to join a company called Envoy back in 2016. He had worked with B2B startups since he was 18, and was looking forward to helping another tech startup scale an idea. But that excitement turned to dread when Boskovic realized his first job was to build yet another data onboarding system. "Eric [Crane] was leading product I was leading engineering, and for the umpteenth time in our careers, we had to build this CSV data onboarding solution for yet another SaaS company," Boskovic said. Envoy needed a painless way for new customers to move their existing data into its new SaaS offering so that it can do interesting things with it.


The nominees for the VentureBeat AI Innovation Awards at Transform 2020

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At our AI-focused Transform 2020 event, taking place July 15-17 entirely online, VentureBeat will recognize and award emergent, compelling, and influential work through our second annual VB AI Innovation Awards. Drawn from our daily editorial coverage and the expertise of our nominating committee members, these awards give us a chance to shine a light on the people and companies making an impact in AI. Here are the nominees in each of the five categories -- NLP/NLU Innovation, Business Application Innovation, Computer Vision Innovation, AI for Good, and Startup Spotlight. A senior principal scientist at Amazon Research and faculty member at the University of California, Santa Cruz, Dr. Hakkani-Tur currently works on solving natural dialogue for Amazon's Alexa AI. She has researched and worked on natural language processing, conversational AI, and more for over two decades, including stints at Google and Microsoft.