By Daljeet Virdi (cast.app, UIUC), Dileep Pasumarthi (Microsoft Bing, UIUC), and Dickey Singh. This is an updated and edited version of the article we published here in January 2020. Natural Language Generation from Structured Data Over the past few years, rapid improvement in state-of-the-art (SOTA) general language models (BERT, GPT-2, GTP-3, XL-Net, etc. and BERT-forks like […]
Are current robotic bartenders and baristas merely vending machines? What would make them more human?
Self-supervised learning is autonomous supervised learning, and a significant challenge for the next decade.
I previously published this on Hackernoon.
Will job losses in the Autonomous Era be different? Will we create jobs like how we have in the previous industrial revolutions? Is educating people, creating UBI and jobs enough?
With success in self-driving cars, similar use cases in business become possible. Self-governing systems that can self-maintain, self-heal, self-learn, and self-improve are becoming a reality.
How Artificial Visual Perception (vision + interpretation) applies to machines, computers, and autonomous vehicles.
Human Intelligence enables humans to think, reason, decide, retain, experience, use symbols to build complex descriptions, recognize patterns, and merge concepts to form new concepts.
Inline with the traditional Halloween inspired AI, and just in time for Halloween 2017, MIT released Shelley AI a conversational and collaborative horror story generator over Twitter. Last year the Nightmare machine generated Halloween inspired images.
China is searching “deep learning” 50x compared to US*
Backhoes and Artificial Intelligence
Pervasiveness of Artificial Intelligence augmented Digital Assistants and what’s next