InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Algorithms behind Modern Storage Systems
Alex Petrov talks about modern storage system approaches, discussing storage internals, evaluation techniques to choose a database best suitable for a certain data.
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Zero to Production in Five Months @ ThirdLove
Megan Cartwright discusses how ThirdLove built their first machine learning recommendation algorithm that predicts bra size and style.
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Designing Automated Pipelines for Unseen Custom Data
Kevin Moore discusses some challenges in designing automated machine learning pipelines that can deal with custom user data that it has never seen before, as well as some of Salesforce’s solutions.
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Goldilocks and Artificial Intelligence
Rob Keefer discusses some of the positive and negative impacts of AI on human performance, offering a framework for determining the right amount of AI to mix into a system that will help users.
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Migrating from Big Data Architecture to Spring Cloud
Lenny Jaramillo discusses how Northern Trust migrated to PCF, highlighting how this helped them accelerate the delivery of functionality to their customers.
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Crisis to Calm: Story of Data Validation @ Netflix
Lavanya Kanchanapalli discusses safe data propagation at Netflix, circuit breakers, data canaries and staggered rollout effective, and efficient validations via sharing data and isolating change.
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The Right Amount of Trust for AI
Chris Butler discusses the building blocks of AI from a product/design perspective, what trust is, how trust is gained and lost, and techniques one can use to build trusted AI products.
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Machine Learning Interpretability in the GDPR Era
Gregory Antell explores the definition of interpretability in ML, the trade-offs with complexity and performance, and surveys the major methods used to interpret and explain ML models in the GDPR era
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The Future of AI
The panelists discuss the future of artificial intelligence.
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Nearline Recommendations for Active Communities @LinkedIn
Hema Raghavan focusses on technologies they have built to power LinkedIn’s “People You May Know” product and describes their nearline platform for notification recommendation.
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Solving Business Problems with AI
The panelists discuss using AI to solve business problems.
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Human-centric Machine Learning Infrastructure @Netflix
Ville Tuulos discusses the tools Netflix built for the data scientists and some of the challenges and solutions made to create a paved road for machine learning models to production.
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