• Artificial Intelligence (AI) learns from data in a way that is similar to how humans learn from experience . First, AI is given a large amount of data, such as images , text , numbers , or sounds . This data helps the AI understand patterns and relationships.

    AI uses machine learning algorithms to analyze the data . During training, the AI makes predictions and then checks if they are correct . If it makes a mistake, it adjusts its rules to improve next time . This process repeats many times until the AI becomes accurate and reliable .

    There are different ways AI learns:

    Supervised learning: learning with labeled data

    Unsupervised learning: finding patterns without labels

    Reinforcement learning: learning through rewards and penalties

    Over time, AI becomes smarter and can make decisions, recognize speech , identify images , recommend content , and much more .
    https://youtu.be/O_dJ9fxI5FM
    Artificial Intelligence (AI) learns from data in a way that is similar to how humans learn from experience πŸ§ πŸ“š. First, AI is given a large amount of data, such as images πŸ–ΌοΈ, text πŸ“, numbers πŸ”’, or sounds 🎧. This data helps the AI understand patterns and relationships. AI uses machine learning algorithms to analyze the data πŸ”. During training, the AI makes predictions and then checks if they are correct βœ…βŒ. If it makes a mistake, it adjusts its rules to improve next time πŸ”„. This process repeats many times until the AI becomes accurate and reliable 🎯. There are different ways AI learns: Supervised learning: learning with labeled data 🏷️ Unsupervised learning: finding patterns without labels 🧩 Reinforcement learning: learning through rewards and penalties πŸ†βš οΈ Over time, AI becomes smarter and can make decisions, recognize speech πŸ—£οΈ, identify images πŸ‘οΈ, recommend content πŸ“², and much more πŸš€. https://youtu.be/O_dJ9fxI5FM
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  • In “The Mind-Reading Potential of AI,” Professor Chin-Teng Lin explores how artificial intelligence can interpret human brain signals and emotions using technologies like brain-computer interfaces (BCI), EEG, and machine learning .
    The talk explains how AI can “read” mental states such as focus, stress, and intention—not by magic, but by analyzing brainwave patterns . It also highlights future applications in healthcare, rehabilitation, education, and human-machine interaction, while raising important ethical questions about privacy and consent .
    https://youtu.be/TtpYsFVlQNc
    In “The Mind-Reading Potential of AI,” Professor Chin-Teng Lin explores how artificial intelligence can interpret human brain signals and emotions using technologies like brain-computer interfaces (BCI), EEG, and machine learning πŸ§¬πŸ’‘. The talk explains how AI can “read” mental states such as focus, stress, and intention—not by magic, but by analyzing brainwave patterns πŸ“ŠπŸ§ . It also highlights future applications in healthcare, rehabilitation, education, and human-machine interaction, while raising important ethical questions about privacy and consent πŸ”βš–οΈ. https://youtu.be/TtpYsFVlQNc
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  • In “The Mind-Reading Potential of AI,” Professor Chin-Teng Lin explores how artificial intelligence can interpret human brain signals and emotions using technologies like brain-computer interfaces (BCI), EEG, and machine learning .
    The talk explains how AI can “read” mental states such as focus, stress, and intention—not by magic, but by analyzing brainwave patterns . It also highlights future applications in healthcare, rehabilitation, education, and human-machine interaction, while raising important ethical questions about privacy and consent .
    https://youtu.be/NfLXzoAe6b4
    In “The Mind-Reading Potential of AI,” Professor Chin-Teng Lin explores how artificial intelligence can interpret human brain signals and emotions using technologies like brain-computer interfaces (BCI), EEG, and machine learning πŸ§¬πŸ’‘. The talk explains how AI can “read” mental states such as focus, stress, and intention—not by magic, but by analyzing brainwave patterns πŸ“ŠπŸ§ . It also highlights future applications in healthcare, rehabilitation, education, and human-machine interaction, while raising important ethical questions about privacy and consent πŸ”βš–οΈ. https://youtu.be/NfLXzoAe6b4
    0 Commenti 0 condivisioni 394 Views