Conference:  Transform X 2022

Authors: Mike Schroepfer, Alexandr Wang

2022-10-19

Mike Schroepfer, Meta’s first Senior Fellow and Former CTO, has been a driving force behind transformative technologies, from his time leading groundbreaking work in computer vision, natural language processing, and the metaverse to his focus today on combating climate change with technology. Schroepfer will sit down with Scale Founder and CEO Alexandr Wang to share lessons from Facebook’s transition from being web-focused to becoming mobile-focused and, ultimately, an AI-centric company. He will explain the developer pain that motivated an industry-standard framework like React Native, as well as the motivations behind keeping PyTorch as a community-focused tool, built for researchers. He will discuss large language models and how more carefully curated, differentiated, and high-quality data will drive significant advancements in capabilities in the near term. He will also cover the future of augmented and virtual reality, including real-time machine translation with closed-captioning, contextual recognition of real-world objects to create more helpful applications, and more efficient hardware with native AI.At Meta, Schroepfer focuses on supporting the company’s strategic technology priorities including its investments in AI and development of technical talent. From 2013 to 2022, he served as Meta’s Chief Technology Officer, where he led the development of the technology and teams that enabled the company to scale to billions of people around the world and make breakthroughs in fields like AI and virtual reality.

Conference:  OpenAI + Data Forum 2022

Authors: Jeff Zemerick

2022-06-23

Bringing NLP capabilities to Apache Solr through ONNX and OpenNLP

• Apache OpenNLP is a Java-based NLP tool that has been around for over a decade and offers various capabilities such as tokenization, document classification, and named entity recognition
• Apache Solr depends on Apache Lucene for search functionality, and Apache Lucene has a dependency on Apache OpenNLP for some NLP operations
• The ONNX Runtime allows for the use of deep learning models across programming languages, architectures, and platforms, enabling the use of NLP services created in other languages
• The speaker demonstrates how a deep learning model trained using PyTorch or Tensorflow can be used for inference from a Java search stack of Apache OpenNLP, Apache Lucene, and Apache Solr
• The speaker discusses the challenges and relationships between OpenNLP, Lucene, and Solr, and provides resources for attendees to get started with these open source projects