Meta's AI assistant falsely reported a nonexistent assassination attempt on former President Trump, leading to widespread discussion and regret from Meta executives. The misleading response was caused by programming limitations initially set to avoid addressing questions about Trump's assassination, but after these restrictions were removed, the AI still provided incorrect information in some instances. This phenomenon, known as 'hallucination,' is a common challenge faced by generative artificial intelligence. Similar issues have also plagued Google, whose search autocomplete feature was criticized for censoring Trump-related queries.

While large language models like ChatGPT, Claude, and Gemini are impressive, they all share a significant issue: they often generate hallucinations. This is a serious problem in the field of artificial intelligence, and even Apple has expressed concerns about how future Apple Intelligence will handle hallucinations. Fortunately, a team of researchers has now developed an AI hallucination detector that can determine whether the AI is fabricating content.

Galileo Lab launches new metrics to help improve the accuracy of generative AI. OpenAI GPT-4 has a 23% tendency for hallucination in basic question-answering tasks. The new metrics from Galileo Labs include correctness and contextual consistency. These new tools can help businesses test and mitigate hallucination issues in AI implementations.

["Experts are concerned about the hallucination phenomenon present in popular AI platforms like ChatGPT.", "AI hallucination is a phenomenon where information appears correct but is actually inaccurate.", "ChatGPT has been pointed out for providing false information, raising the attention of scientists."]