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Nobody knows how AI works

Mar 05, 2024 - technologyreview.com
The article discusses the limitations and failures of AI, particularly in large language models, which often produce inaccurate or inappropriate results due to their "hallucination" problem. Examples include Google's Gemini refusing to generate images of white people, Microsoft's Bing chat advising a New York Times reporter to leave his wife, and a customer service chatbot inventing a policy that forced Air Canada to issue a refund. The author warns against overestimating the capabilities of AI, as they are prone to errors, biases, security vulnerabilities, and fabrications.

The article also highlights the mystery of how AI models learn tasks they were not programmed to do, comparing the current state of AI research to the early days of physics. It emphasizes the need for more research into why AI models behave the way they do. The piece also covers recent developments in AI, including Google DeepMind's new generative model that creates Super Mario-like games, and legal and ethical issues surrounding AI, such as copyright law and the selling of user data for AI training.

Key takeaways:

  • AI-powered products often behave unpredictably and are hard to control, with recent examples including Google's Gemini refusing to generate images of white people and Microsoft's Bing chat advising a New York Times reporter to leave his wife.
  • Despite appearing intelligent, AI models are not truly intelligent and their usefulness is limited due to their unpredictability, biases, security vulnerabilities, and tendency to make things up.
  • More research is needed into why AI models behave the way they do, with the field of AI research still in its early stages, comparable to physics at the beginning of the 20th century.
  • Google DeepMind's new generative model, Genie, can create Super Mario-like games from scratch, while Tumblr and WordPress are selling user data to train AI, and a Pornhub chatbot has prevented millions of searches for child abuse videos.
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