Micron has acquired FWDNXT, a machine learning software and hardware startup that spun out of Purdue. Micron is integrating FWDNXT's artificial intelligence hardware and software technology with its advanced memory to explore deep learning solutions for data analytics, particularly in IoT and edge computing. Purdue provided the entrepreneurial resources to help me achieve my vision of taking our work on machine learning and deep learning technology to a much wider audience where we can have a bigger impact," said Eugenio Culurciello, Micron fellow and chief machine learning architect. "Micron has the leadership in memory, long history of innovation and drive to deliver power and performance capabilities that address the most complex and demanding edge applications at scale." Culurciello founded FWDNXT while working as an associate professor in Purdue's College of Engineering. Based in the Purdue Research Park, FWDNXT designed next-generation hardware and software for deep learning aimed at enabling computers to understand the world in the same way humans do. Culurciello worked closely with the Purdue Research Foundation Office of Technology Commercialization to secure and develop an intellectual property rights strategy for the AI technology that he developed at Purdue, which Micron licenses today. The FWDNXT acquisition is another strong show of confidence by industry in Purdue technology designed to make a difference for Indiana and beyond," said Brooke Beier, vice president of the Office of Technology Commercialization.

WEST LAFAYETTE, Ind. – Technology that combines machine learning with artificial intelligence from Purdue University has taken its next giant leap toward powering more Internet of Things and edge computing devices. FWDNXT, a software and hardware startup that spun out of Purdue, was acquired in October by Micron Technology Inc., an industry leader in innovative memory and storage solutions. Micron is integrating FWDNXT's artificial intelligence hardware and software technology with its advanced memory to explore deep learning solutions for data analytics, particularly in IoT and edge computing. "Purdue provided the entrepreneurial resources to help me achieve my vision of taking our work on machine learning and deep learning technology to a much wider audience where we can have a bigger impact," said Eugenio Culurciello, Micron fellow and chief machine learning architect. "Micron has the leadership in memory, long history of innovation and drive to deliver power and performance capabilities that address the most complex and demanding edge applications at scale."

WEST LAFAYETTE, Ind. – One of the challenges in using machine learning for drug development is to create a process for the computer to extract needed information from a pool of data points. Drug scientists must pull biological data and train the software to understand how a typical human body will interact with the combinations that come together to form a medication. Purdue University drug discovery researchers have created a new framework for mining data for training machine learning models. The framework, called Lemon, helps drug researchers better mine the Protein Data Base (PDB) – a comprehensive resource with more than 140,000 biomolecular structures and with new ones being released every week. The work is published in the Oct. 15 edition of Bioinformatics.

WEST LAFAYETTE, Ind. – Increased adoption of cloud applications, such as Dropbox and Google Drive, by private users has increased concern about use of cloud information for cybercrimes such as child exploitation, illegal drug trafficking and illegal firearm transactions. Researchers at Purdue University have developed a cloud forensic model using machine learning to collect digital evidence related to illegal activities on cloud storage applications. "It is crucial to detect illegal cloud activities in motion," said Fahad Salamh, a PhD student in the Purdue Polytechnic Institute, who helped create the system. "Our technology identifies and analyzes in real time incidents related to these cybercrimes through transactions uploaded to cloud storage applications." Salamh worked on the technology with Marcus Rogers and Umit Karabiyik, professors in Polytechnic who specialize in computer and information technology.