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  2. Elements of AI - Wikipedia

    en.wikipedia.org/wiki/Elements_of_AI

    Elements of AI is a massive open online course (MOOC) teaching the basics of artificial intelligence. [1] The course, originally launched in 2018, is designed and organized by the University of Helsinki and learning technology company MinnaLearn . [ 2 ]

  3. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    Explainable AI (XAI), or Interpretable AI, or Explainable Machine Learning (XML), is artificial intelligence (AI) in which humans can understand the decisions or predictions made by the AI. [129] It contrasts with the "black box" concept in machine learning where even its designers cannot explain why an AI arrived at a specific decision. [ 130 ]

  4. TensorFlow - Wikipedia

    en.wikipedia.org/wiki/TensorFlow

    A TPU is a programmable AI accelerator designed to provide high throughput of low-precision arithmetic (e.g., 8-bit), and oriented toward using or running models rather than training them. Google announced they had been running TPUs inside their data centers for more than a year, and had found them to deliver an order of magnitude better ...

  5. Investing in artificial intelligence (AI): A beginner’s guide

    www.aol.com/finance/investing-artificial...

    Analysts at International Data Corp. (IDC), a provider of market intelligence, predict that worldwide revenues for the AI market could reach $900 billion by 2026, logging a compound annual growth ...

  6. Wikipedia : WikiProject AI Cleanup

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

    Welcome to WikiProject AI Cleanup—a collaboration to combat the increasing problem of unsourced, poorly written AI-generated content on Wikipedia. If you would like to help, add yourself as a participant in the project, inquire on the talk page , and see the to-do list .

  7. Attention Is All You Need - Wikipedia

    en.wikipedia.org/wiki/Attention_Is_All_You_Need

    Transformer architecture is now used alongside many generative models that contribute to the ongoing AI boom. In language modelling, ELMo (2018) was a bi-directional LSTM that produces contextualized word embeddings, improving upon the line of research from bag of words and word2vec. It was followed by BERT (2018), an encoder-only Transformer ...

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