Research and tools from Intel AI Lab
Intel AI Lab, a team of deep learning researchers, data scientists, and neuroscientists, has been focused on state-of-the art research and development in the field of artificial intelligence. Our core areas of research range from projects with a direct impact on upcoming and future generations of Intel technologies to novel algorithm development in areas such as natural language, speech, and vision. Our open source frameworks are widely being adopted by academia and industry alike – NLP Architect is our natural language offering that consists of modular components and core models that can be added to any NLP workflow. RL Coach, a research framework for training and evaluating reinforcement learning (RL) agents is now available with AWS Sagemaker. Distiller is our neural network compression library. These libraries, along with our compiler and distributed learningplatforms from Intel AI Products Group provide a full stack of tools for prototyping and scaled deployment on Intel hardware.
Dr. Yinyin Liu is the Head of Data Science in the Artificial Intelligence Products Group at Intel. At Intel AI, Yinyin leads a team of deep learning (DL) researchers and data scientists working on NLP and RL research and providing in-depth data science for AI product engineering. She is responsible for setting the strategy on converging data science with research and connecting with community through open-source libraries and frameworks, as well as working with partners and customers to apply innovative AI solutions to solve problems across industry domains. Yinyin works with her team to build capabilities in various areas in NLP, RL, model compression and apply data science through the stack with foundational AI software and hardware. Yinyin has also driven algorithmic requirements for the Intel Nervana NNP. Yinyin represents Intel at the Partnership on AI, an organization working on making AI beneficial for people and society. Yinyin was recently named one of the 9 women in Silicon Valley to watch who are leading in artificial intelligence. She has research experience in machine learning, deep learning, neuromorphic computing and robotics.