Interacting with AI

Kubernetes—the container orchestration engine used by all of the top technology companies—was built from the ground up to run and manage highly distributed workloads on huge clusters. Thus, it provides a solid foundation for model development. Daniel Whitenack demonstrates how to easily deploy and scale AI/ML workflows on any infrastructure using Kubernetes. Read more.

Carl Osipov walks you through creating increasingly sophisticated image classification models using TensorFlow. Read more.

High-resolution land cover maps help quantify long-term trends like deforestation and urbanization but are prohibitively costly and time intensive to produce. Mary Wahl and Banibrata De demonstrate how to use Microsoft’s Cognitive Toolkit and Azure cloud resources to produce land cover maps from aerial imagery by training a semantic segmentation DNN—both on single VMs and at scale on GPU clusters. Read more.

Xiaoyong Zhu, Gheorghe Iordanescu, Wilson Lee, and Ivan Tarapov walk you through building a deep learning model and intelligent applications on edge devices running iOS, Android, and Windows, using a working example that helps clinicians in areas with less access to radiologists identify possible lung diseases. Read more.

Uber has implemented an ML and NLP system that suggests the most likely solutions to a ticket to its customer support representatives, making them faster and more accurate while providing a better user experience. Piero Molino, Huaixiu Zheng, and Yi-Chia Wang describe how Uber built the system with traditional and deep learning models and share the lessons learned along the way. Read more.

Over the last few years, convolutional neural networks (CNN) have risen in popularity, especially for computer vision. Anirudh Koul explains how to bring the power of convolutional neural networks and deep learning to memory- and power-constrained devices like smartphones. Read more.

Modern radiological lung cancer screening is an entirely manual process, leading to high costs and inter-reader variability. Daniel Golden offers an overview of a deep learning-based system that automatically detects and segments lung nodules in lung CT exams and explains how it was tested for safety and efficacy. The system is FDA cleared and segments nodules as accurately as a clinician. Read more.

We now live in the age of assistive and AI companions, where everything is coming alive. Danielle Krettek demonstrates how to design for the "invisible" emotional layer of experience that marks this new wave of technology. Read more.

Join Ari Kaplan, Erin LeDell, Chris Coad, and David Kearns to see where AI meets business intelligence, as they explore the latest ML technologies and concepts powering today's decisions, including Hortonworks, Aginity Amp, H2O.ai, IBM Data Science Experience, and more—using real-life baseball data to illustrate the concepts. Read more.

Clara’s human-in-the-loop scheduling service combines the precision of machine intelligence and the judgement of an expert team. Jason Laska explores the trade-offs between text annotations defined for fast data entry and those meant solely for training machine learning models, using the application of DateTime text as it pertains to meeting-attendee availability to guide the discussion. Read more.

Machine learning algorithms are being developed and improved at an incredible rate but are not necessarily accessible to the broader community. A. Besir Kurtulmus offers an overview of DanKu, a new blockchain-based protocol for evaluating and purchasing ML models on a public blockchain such as Ethereum that provides everyone access to high-quality, objectively measured machine learning models. Read more.

Labhesh Patel explains how deep learning is informing Jumio's computer vision through smarter data extraction, fraud detection, and risk scoring and how Jumio is leveraging massive datasets and human review to dramatically improve the accuracy of its machine learning algorithms to detect bogus IDs and streamline the verification process of legitimate documents. Read more.

Over 400M people worldwide have some sort of speech or hearing disorder that prevents them from participating in the job market. Goodman Gu offers an overview of Stride4All, an initiative using AI to open work up for disabled people and empower them for teamwork, and showcases a prototype that uses deep learning and computer vision technologies for gesture recognition of American Sign Language. Read more.

For developers building a bot or virtual agent, the critical question is which bot to build and why? Today, most can’t answer it without a manual intent discovery process, largely based on guesswork, that uncovers only a percentage of possible opportunities. Ofer Ronen demonstrates techniques, based on machine learning, for faster, more efficient intent discovery. Read more.