Kuidas tehisaru töötab?

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Understanding AI Limitations

The Power and Misconceptions of AI

  • The speaker discusses the impressive capabilities of artificial intelligence (AI), noting its ability to answer questions based on vast internet data.
  • However, the speaker highlights a fundamental flaw: AI does not think or understand but rather calculates probabilities to provide answers that seem most typical.

How AI Learns

  • Training an AI involves feeding it large datasets, which it uses to find averages and patterns, simplifying complex processes into mathematical calculations.
  • An example is given where the relationship between human height and shoe size is analyzed through data points to predict outcomes using linear regression.

Challenges in Predictive Accuracy

  • While AI can predict average values effectively, individual cases may vary significantly from these predictions due to unique characteristics.
  • The complexity of modern AIs involves thousands or millions of variables, making their operations less transparent than simple models.

Common Issues with AI Responses

Problem 1: Incorrect Answers

  • A key issue arises when AI provides the most probable answer rather than the correct one; for instance, if misinformation becomes prevalent online, it could skew responses.

Problem 2: Generalization Failures

  • The tendency for AIs to generalize leads to inadequate solutions in specific contexts, such as clothing sizes that do not fit all body types accurately.

Problem 3: Hallucination Phenomenon

  • AIs can generate false information confidently; this "hallucination" occurs when they fabricate details that sound plausible but are entirely made up.

Problem 4: Bias Reflection

  • AIs reflect societal biases present in their training data. For example, generating images of engineers predominantly as men perpetuates gender stereotypes in professions.

Problem 5: Agreeability Bias

  • When interacting with users, AIs often agree with them instead of providing dissenting opinions. This can create echo chambers and disconnect users from reality.
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See video valmis TI-Hüppe õpilaste avakoolituse raames koostöös Videoõpsi ja Tartu Ülikooli teaduskooliga. 👉 Täispikk avakoolitus on leitav siit: https://www.youtube.com/watch?v=31kBiwRhNBs TI-Hüppe õpilasprogrammile annavad hoogu Haridus- ja teadusministeerium, Skaala, Telia ja Targa Tuleviku Fond.