Anyone who has tried current AI systems such as Siri or Bots for Messenger knows they are only able to understand a limited set of commands. Semantic Machines is developing fundamentally new machine learning technology that is able to understand the meaning and context of multi-turn conversations. As a result, the Company's new AI platform can engage in fluid, sustained conversations to solve more complicated requests, bringing us closer to the systems envisioned in science fiction.
AI is the hottest topic in Silicon Valley today amongst top tech firms because it has the potential to completely upend the Internet industry as we know it. If companies like Facebook or Apple successfully develop powerful AI Assistants that can address a user's requests naturally, it would largely eliminate the need to visit other sites like Google, Amazon, Expedia etc. Conversational AI Assistants have the potential to directly book travel, answer questions, resolve customer support issues, summon ride services and more - all without the user ever visiting websites or apps branded by those services. AI Assistants also have the potential to unlock powerful new capabilities not currently possible with search engines or apps by simultaneously interacting with many services at once to achieve a user's request. In this context, it is clear how this technology would confer a powerful advantage to whichever company was behind the market leading AI Assistant.
As the creator of core language understanding AI technology behind Google Assistant, Professor Liang is regarded as one of the world's top AI researchers. "Semantic Machines has made profound advances in the area of AI dialogue systems, and I couldn't pass up the opportunity to work with them" said Professor Liang. "They have assembled an unbelievable team, probably the most advanced in the world, and it is tremendously exciting to work with this group to create the fundamental technology needed to make conversational computing a reality," he continued.
Co-founder of Semantic Machines, Professor Dan Klein commented "Percy is one of the most extraordinary researchers I've ever worked with and I'm thrilled that he will be contributing his considerable talents here. Semantic Machines is doing something very exciting. We are building a technology platform that could change how people and computers interact forever."
Semantic Machines CEO Dan Roth commented, "Starting with the visionary leadership of Dan Klein and Larry Gillick, we've made tremendous progress towards solving conversational artificial intelligence. We've built one of the best research and engineering teams in the world to work on this immensely exciting challenge. Anyone who has followed AI or the NLP space over the last several years knows that there are a few names that keep driving the technology forward, solving the hard problems. We're very fortunate to have many of the very best including Dan Klein, Percy Liang, Larry Gillick and others. The technical team at Semantic Machines is something we are extremely proud of. Watching them make such tremendous progress on the platform is truly inspiring."
About Semantic Machines, Inc.
Semantic Machines is a privately held Artificial Intelligence technology developer with offices in Berkeley, California and Boston, Massachusetts. Backed by $21M in venture capital from Bain Capital Ventures, General Catalyst and others, the company is creating the fundamental AI technology needed to teach computers to understand language, comprehend context and interact naturally. The company plans to provide its highly customizable AI platform technology to strategic partners. The company website is http://www.semanticmachines.com
About Professor Percy Liang
Percy Liang is now Lead Scientist at Semantic Machines, and a Professor of Computer Science at Stanford University. His research spans theoretical machine learning to practical natural language processing; topics include semantic parsing, question answering, machine translation, online learning, method of moments, approximate inference, Bayesian modeling, and deep learning. He has over 60 publications appearing in top venues and has received several paper awards. Percy received a B.S. in computer science from MIT and a Ph.D. from UC Berkeley in 2011. After graduation, he spent one year at Google, where he was one of the founding members of the semantic parsing team. His awards include an IJCAI Computers and Thought Award (2016, given to a single AI researcher every two years), an NSF CAREER Award (2016), a Sloan Research Fellowship (2015), and a Microsoft Research Faculty Fellowship (2014).
SOURCE Semantic Machines Inc.