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  2. Hubert Dreyfus's views on artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Hubert_Dreyfus's_views_on...

    Book cover of the 1979 paperback edition. Hubert Dreyfus was a critic of artificial intelligence research. In a series of papers and books, including Alchemy and AI, What Computers Can't Do (1972; 1979; 1992) and Mind over Machine, he presented a pessimistic assessment of AI's progress and a critique of the philosophical foundations of the field.

  3. Generative artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Generative_artificial...

    If AI-generated content is included in new data crawls from the Internet for additional training of AI models, defects in the resulting models may occur. [185] Training an AI model exclusively on the output of another AI model produces a lower-quality model.

  4. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Transformer_(deep_learning...

    For many years, sequence modelling and generation was done by using plain recurrent neural networks (RNNs). A well-cited early example was the Elman network (1990). In theory, the information from one token can propagate arbitrarily far down the sequence, but in practice the vanishing-gradient problem leaves the model's state at the end of a long sentence without precise, extractable ...

  5. The furious pace of AI model releases underscores AI’s rapid ...

    www.aol.com/finance/furious-pace-ai-model...

    This pace of model releases says a lot about the current state of AI. It also makes it more difficult for customers—and everyone else—to keep up. AI model releases become business as usual

  6. Here's the Worst-Case Scenario for Nvidia Stock - AOL

    www.aol.com/finance/heres-worst-case-scenario...

    A cheap AI model capable of trading blows with the best models from Open AI and Anthropic isn't enough on its own to scuttle Nvidia's growth story. Cheap and efficient AI models could spur more ...

  7. Flux (text-to-image model) - Wikipedia

    en.wikipedia.org/wiki/Flux_(text-to-image_model)

    Flux (also known as FLUX.1) is a text-to-image model developed by Black Forest Labs, based in Freiburg im Breisgau, Germany. Black Forest Labs were founded by former employees of Stability AI. As with other text-to-image models, Flux generates images from natural language descriptions, called prompts.