InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Facial Recognition Adversarial Attacks, Policy and Choice
Gretchen Greene demonstrates the technical feasibility of facial recognition adversarial attacks, describes using it at airports and borders and invites contributions to their open sourced prototype.
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Creating Robust Interpretable NLP Systems with Attention
Alexander Wolf introduces Attention, an interpretable type of neural network layer that is loosely based on attention in human, explaining why and how it has been utilized to revolutionize NLP.
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The Whys and Hows of Database Streaming
Joy Gao talks about how database streaming is essential to WePay's infrastructure and the many functions that database streaming serves.
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Patterns of Streaming Applications
Monal Daxini talks about streaming application patterns and anti-patterns, and use cases and concrete examples using Apache Flink.
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Massively Scaling MySQL Using Vitess
Sugu Sougoumarane gives an overview of the salient features of Vitess, and at the end, covers some advanced features with a demo.
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Monitoring AI with AI
Iskandar Sitdikov discusses a solution, tooling and architecture that allows an ML engineer to be involved in delivery phase and take ownership over deployment and monitoring of ML pipelines.
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Migrating ML from Research to Production
Conrado Silva Miranda shares his experience leveraging research to production settings, presenting the major issues faced by developers and how to establish stable production for research.
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Unintended Consequences of AI — Panel Discussion
The panelists discuss some of the unexpected and unintended consequences AI might have.
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PCF Data Collection for TBM
Chris Busch and Raj Sivaraj overview the foundation data collection needs of Mastercard, and how data is collected and provided back to product teams with critical expense data for show-back.
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Building a Voice Assistant for Enterprise
Manju Vijayakumar talks about Einstein Assistant - an AI Voice assistant for enterprises that enables users to "Talk to Salesforce".
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Reasoning about Uncertainty at Scale
Max Livingston presents a case study of using Bayesian modelling and inference to directly model behavior of aircraft arrivals and departures, focusing on the uncertainty in those predictions.
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Machines Can Learn - a Practical Take on Machine Intelligence Using Spring Cloud Data Flow and TensorFlow
Christian Tzolov showcases how building a complex use-case, such as real-time image recognition or object detection, can be simplified with the help of the Spring Ecosystem and TensorFlow.
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