Garbage in is garbage out in computing, and it is especially the case with regards to machine learning data. In this infographic from Cognilytica we go over key insights and figures from the recent Data Preparation & Labeling for AI 2020 Report including the fact that data labeling is expensive, humans are still needed for manually labeling data and AI quality control, AI has time-consuming and complex data prep requirements, and more.
- Luminoso Briefing Note
- Common Sense and Natural Language Understanding – Interview with Catherine Havasi, Luminoso
- Data Preparation & Labeling for AI 2020 Report
|Luminoso turns unstructured text data into business-critical insights. Using common-sense artificial intelligence to understand language, we empower organizations to discover, interpret, and act on what people are telling them. Requiring little setup, maintenance, training, or data input, Luminoso combines world-leading natural language understanding technology with a vast knowledge base to learn words from context – like humans do – and accurately analyze text in minutes, not months. Our software provides native support in over a dozen languages, so leaders can explore relationships in data, make sense of feedback, and triage inquiries to drive value, fast.|
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