InfoQ Homepage Social Networking Content on InfoQ
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Probabilistic Programming for Software Engineers
Michael Tingley provides a preview of how Facebook is advancing probabilistic programming, as well as some of the big problems they used it to solve.
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Real-Time Data Streaming with Azure Stream Analytics
Alexander Slotte introduces Azure Stream Analytics, its ecosystem, and real world examples streaming Twitter feeds as well as sensor data from Raspberry Pi.
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Computational Propaganda - How Algorithms Influence our Decisions
Pawel Rzeszucinski discusses the Cambridge Analytica case, Brexit and the use of bots for influencing people’s decisions.
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Let's Start an Epidemic
Doc Norton explores how things like disease, politics, and even moods travel through social networks, discussing the impact people have on others.
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From Research to Production with PyTorch
Jeff Smith covers some of the latest features from PyTorch including the TorchScript JIT compiler, distributed data parallel training, TensorBoard integration, new APIs, and more.
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wav2letter++: Facebook's Fast Open-Source Speech Recognition System
Vitaliy Liptchinsky introduces wav2letter++, an open-source deep learning speech recognition framework, explaining its architecture and design, and comparing it to other speech recognition systems.
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Using Technology to Protect against Online Harassment Panel
The panelists discuss the changes society has seen since the advent of social media and how they're building the next generation of software tools to protect against online harassment.
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Canopy: Scalable Distributed Tracing & Analysis @ Facebook
Haozhe Gao and Joe O’Neill present Canopy, Facebook’s performance and efficiency tracing infrastructure. They talk about the lessons learned and present case studies of its use.
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Applied Performance Theory
Kavya Joshi explores the use of performance theory in real systems at companies like Facebook, and discusses how it can be leveraged, to prepare systems for flux and scale.
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Drivetribe: A Social Network on Streams
Aris Koliopoulos talks about how common problems in social media can be resolved with a healthy mix of stream processing and functional programming.
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Continuous Optimization of Microservices Using ML
Ramki Ramakrishna shares Twitter’s recent experience in applying Bayesian optimization to the performance tuning problem, discussing a service used for continuously optimizing microservices.
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Hardware & Provisioning Engineering @Twitter
M. Singer and N. Johnson present the Provisioning Engineering system at Twitter, called Wilson, which together with Audubon is designed to handle every part of a server's lifecycle.
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