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2. Artificial intelligence in Wikimedia projects - Wikipedia

   en.wikipedia.org/wiki/Artificial_intelligence_in...

   Subsets of the Wikipedia corpus are considered the largest well-curated data sets available for AI training. [ 19 ] [ 20 ] A 2012 paper reported that more than 1,000 academic articles, including those using artificial intelligence, examine Wikipedia, reuse information from Wikipedia, use technical extensions linked to Wikipedia, or research ...

3. Recursive self-improvement - Wikipedia

   en.wikipedia.org/wiki/Recursive_self-improvement

   Recursive self-improvement (RSI) is a process in which an early or weak artificial general intelligence (AGI) system enhances its own capabilities and intelligence without human intervention, leading to a superintelligence or intelligence explosion.

4. Wikipedia : WikiProject AI Cleanup

   en.wikipedia.org/wiki/Wikipedia:WikiProject_AI...

   To identify AI-generated images and ensure appropriate usage. To help and keep track of AI-using editors who may not realize the deficiencies of AI as a writing tool. The purpose of this project is not to restrict or ban the use of AI in articles, but to verify that its output is acceptable and constructive, and to fix or remove it otherwise.

5. Opinion: AI-assisted writing is close to becoming as standard ...

   www.aol.com/news/opinion-ai-assisted-writing...

   Using AI to generate ideas, create an outline and provide specific instructions for writing each paragraph, Terry wasn’t using an AI assistant; he had become the assistant — and so will we.

6. Automated journalism - Wikipedia

   en.wikipedia.org/wiki/Automated_journalism

   [3] [4] [5] There are four main fields of application for automated journalism, namely automated content production, Data Mining, news dissemination and content optimization. [6] Through artificial intelligence (AI) software, stories are produced automatically by computers rather than human reporters. These programs interpret, organize, and ...

7. Transfer learning - Wikipedia

   en.wikipedia.org/wiki/Transfer_learning

   Transfer learning (TL) is a technique in machine learning (ML) in which knowledge learned from a task is re-used in order to boost performance on a related task. [1] For example, for image classification, knowledge gained while learning to recognize cars could be applied when trying to recognize trucks.