У нас вы можете посмотреть бесплатно From IBM Research to Renaissance Technologies to Venture Capital Investing: A Journey in AI или скачать в максимальном доступном качестве, видео которое было загружено на ютуб. Для загрузки выберите вариант из формы ниже:
Если кнопки скачивания не
загрузились
НАЖМИТЕ ЗДЕСЬ или обновите страницу
Если возникают проблемы со скачиванием видео, пожалуйста напишите в поддержку по адресу внизу
страницы.
Спасибо за использование сервиса ClipSaver.ru
Visit our website: http://bit.ly/2GtXaiw David Magerman, Managing Partner, Differential Ventures Abstract The speaker, Dr. David Magerman, has experienced Artificial Intelligence and Financial Technology from a variety of perspectives. As an early data scientist, working at IBM Research's Speech Recognition Group in the 1990s, he helped pioneer some of the early approaches to applying AI and ML to practical problems. Over a twenty year career at quantitative trading giant Renaissance Technologies, he was one of the chief architects of their research and trading platforms, and the senior manager responsible for deploying newly-developed software systems into live trading. Now, after those two careers, he is using his experience at is newly founded VC firm, Differential Ventures, to invest in startups around data science. In this talk, David will discuss how his experience at IBM and Renaissance inform his investing in FinTech companies, and share his views on what financial firms should look for in technologies and technology vendors when incorporating AI into their company's tool boxes. Bio David Magerman is a founding managing partner at Differential Venture Partners, an early stage technology investment firm focusing on data-science driven startups. He is the former head of production at Renaissance Technologies, and one of the key architects and engineers of their equities research and trading systems. His 1994 PhD thesis for his degree in Computer Science from Stanford University produced groundbreaking research in using data science to machine learning and statistical modeling to solve problems in Natural Language Processing.