Anuket Project

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MOTORS: Models - Tools - Research-Studies

What is more valuable to Telcos:

Click for anchor link We build better ML-models to important problems

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Click for anchor link We optimize the existing model for important problems

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Click for anchor link We build tools that can help telcos to build ML-Models

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Click for anchor link We conduct research studies with thorough and systematic analysis

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Models/Frameworks

Telcos have (for past 15-20 yrs - maybe even more) AI/ML systems solving business problems (customer churns) and/or legacy Network management (failures prediction, anomaly detection, etc.).  Is it Important that the ML-models we develop (related to Telco Clouds) should work in these frameworks (of legacy systems) ?

Click for anchor link Integration with legacy AI/ML Systems

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YES (we don't want to maintain multiple systems)
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NO (Managed by different silos)
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Importance of AI/ML Problems related to NFV

Please add any other problems you consider that is important here:



Click for anchor link Importance of Failure Prediction (VM)

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Click for anchor link Importance of Failure Prediction (Containers)

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Click for anchor link Importance of Failure Prediction (Links)

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Click for anchor link Importance of Failure Prediction (Apps)

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Click for anchor link Importance of Failure Prediction (Services - control/middleware/)

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Click for anchor link Importance of Traffic Engineering (Ex: Reinforcement Learning)

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Click for anchor link Importance of Other Predictions (resource utilization, attack, SLA-breach)

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Click for anchor link Importance of Resource Optimization (scheduling, deployment scaling, migration, etc.)

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Click for anchor link Importance of Anomaly Detection (metrics, logs, stats)

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Click for anchor link Importance of Alert Filtering/classification - Finding Actionable Alerts

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Click for anchor link Importance of Correlation - as part of causal analysis

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