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Arkady Borkovsky San Francisco, California, United States500+ connections Join to connect Activity We are introducing Colibri Smart Agendas: AI hears what you have said and reminds you what to...
Arkady was a Co-founder of Arcadia Intelligent Systems which after several transformations became Yandex, the most successful search portal in Russia. From early 1990s Arkady worked on intelligent text processing at different search companies. He recently left Yahoo! to put together Yandex Labs – the Yandex development center in California.
View Arkady Borkovsky’s profile on LinkedIn, the world’s largest professional community. Arkady has 1 job listed on their profile. See the complete profile on LinkedIn and discover Arkady’s ...
Arkady Borkovsky is the Founder & Chief Technology Officer, Yandex Labs at Yandex. Yandex Founder & Chief Technology Officer, Yandex Labs Aug 2008 Related Hubs Recent News and Activity Funding Round • Jun 27, 2013 Robin Labs raised $700,000 / Seed from AltaIR Capital and 2 other investors Discover more funding rounds
Arkady Borkovsky is the Chief Technology Officer of Yandex Labs at Yandex NV. Wallmine is a radically better financial terminal. Sign up in seconds, it's free! Sign up Already have an account? Sign in or Sign up with Google Sign up with Facebook What does Yandex NV do?
Arkady Yuryevich Volozh (Russian: Аркадий Юрьевич Волож; born 11 February 1964) is a Kazakhstan born Israeli serial technology entrepreneur, computer scientist, investor and philanthropist. He pioneered the development of search and navigation technology as well as intelligent products and services powered by machine learning.
Yandex was founded in 1997 by Arkady Volozh (current CEO), Arkady Borkovsky, and Ilya Segalovich. "Yet Another iNDEXer" was the key phrase from which the name of the company was created. From its foundation, Yandex has worked to deliver relevant and useful search results to its users while leveraging a variety of high tech algorithms thus ...
Arkady Borkovsky [...] Vishnu Vyas Computing the pairwise semantic similarity between all words on the Web is a computationally challenging task. Parallelization and optimizations are necessary.