Month: June 2017

Digamma.ai CEO Q&A Series: Mark Chung of Verdigris

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Artificial Intelligence / Machine Learning
Verdigris

Digamma.ai CEO Q&A Series: Interview with Mark Chung, CEO and Co-Founder at Verdigris. 1. Verdigris provides real-time energy intelligence for facilities managers, enabling them to react faster with device-level monitoring and real-time alerts. What are the implications of your company’s technology on the building industry and to a larger extent, the environment? We target mission-critical facilities like distribution centers, factories, and even hotels because they are sources of major power consumption and often struggle to […]

The Five Food and Restaurant AI Chatbots You Should Know About

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Artificial Intelligence / chatbot / Machine Learning
ai-chatbots

Facebook Messenger chatbots have major potential, even if the field is relatively nascent one.  With Facebook launching Discover, a hub inside Messenger for discovering new and interesting chatbots to message with, there’s no excuse not to try out a new chatbot this summer — especially a food-related one. From analyzing your receipts to providing awesome restaurant recommendations, the following list represents a veritable freshmen class of powerful, value-adding, food and restaurants AI chatbots. Lunchcat Lunchcat, created by […]

Digamma.ai CEO Q&A Series: Michal Wroczynski of Fido.ai

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Artificial Intelligence
fido artificial intelligence

Digamma.ai CEO Q&A Series: Interview with Michal Wroczynski, CEO and founder at Fido Labs 1. Fido’s technology powers chatbots so that they can learn automatically from the internet and answer complex business questions based on a large volume of text. Tell me about how Fido got started in the first place and your novel approach in teaching machines how to reason more like humans. In 2003, we co-founded Fido Interactive and implemented many commercial projects of AI […]

Digamma.ai Q&A Series: Vsevolod Dyomkin of (m8n)ware

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Artificial Intelligence
NLP

Digamma.ai Q&A Series: Interview with Vsevolod Dyomkin  1. Grammarly is a commercial product. While developing it, did you encounter any interesting challenges and obtain any interesting research results in the NLP area? Did any interesting academic results arise from the development process or was the work purely an application of existing NLP algorithms? Grammarly operates in a field that is both down-to-earth and also has a history of relevant academic research.  In addition to its […]