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OpenAI recently released its latest o3 and o4-mini AI models, which achieve state-of-the-art performance in many areas. However, these new models have not improved upon the issue of 'hallucinations,' exhibiting even more severe instances than previous OpenAI models. 'Hallucinations,' the generation of factually incorrect information by AI models, remain one of the most challenging problems in AI today. Previous generations of models showed improvements in reducing hallucinations; however, o3 and o4-mini have not.

Researchers at Westlake University have recently developed a new model capable of detecting text generated by artificial intelligence. Professor Zhang Yue, the team leader, stated in an interview that this model utilizes an unsupervised algorithm to effectively determine if an article is AI-generated, a crucial development in the rapidly advancing field of AI. Professor Zhang Yue mentioned that with continuous technological advancements, AI applications in creative fields are becoming increasingly prevalent. However, this rise brings challenges, such as AI hallucinations, a phenomenon where AI generates inaccurate or nonsensical information.

Recently, Vectara released a report titled 'Hallucination Ranking', comparing the performance of different large language models (LLMs) in generating hallucinations while summarizing short documents. This ranking utilized Vectara's Hughes Hallucination Evaluation Model (HHEM-2.1), which is regularly updated to assess the frequency of false information introduced by these models in summaries. According to the latest data, the report highlighted key metrics such as hallucination rates, factual consistency rates, response rates, and average summary lengths of several popular models.

As businesses increasingly adopt large language models (LLMs), improving the accuracy of model knowledge and reducing hallucination phenomena has become a significant challenge. Researchers at Meta AI have introduced a 'Scalable Memory Layer' in a recent paper, which may provide a solution to this issue. The core idea of the scalable memory layer is to add more parameters to the LLMs without increasing computational resources during inference, thereby enhancing their learning capabilities. This architecture is suitable for storing large amounts of factual knowledge while maintaining...

A characteristic widely regarded as a flaw of artificial intelligence - 'hallucination' - has surprisingly become key to scientific breakthroughs. According to Fortune magazine, Professor David Baker, one of the winners of the 2024 Nobel Prize in Chemistry, achieved significant research breakthroughs using the 'hallucination' feature of AI models. Professor Baker, from the University of Washington, is the only American scientist among this year's three Nobel Prize winners in Chemistry. He successfully invented a novel protein using computer software, an achievement that ultimately earned him this honor. Image source note: The image is AI-generated and authorized.

On November 12, 2024, the Baidu World Conference grandly opened at the Shanghai World Expo Center. The conference included a main forum, four sub-forums, and over thirty sessions of public courses on artificial intelligence. Baidu's founder, Robin Li, delivered a speech titled 'Applications Have Arrived' at the main forum, introducing Baidu's latest technological breakthroughs and application achievements in the field of artificial intelligence, while also providing an in-depth discussion on future industry trends.

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.

In this era of information explosion, content creators are extremely busy. According to a survey, most creators spend more than 20 hours per week producing new content for their niche. As a result, the time left for them to interact with their fans is minimal. However, Mark Zuckerberg, the head of Meta, believes that artificial intelligence (AI) could be the "lifeline" to solve this problem.Image source note: Image generated by AI, image authorized service provider MidjourneyRecently, Zuckerberg

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.

Dictionary.com has chosen 'hallucination' as the Word of the Year for 2023, highlighting the widespread application of artificial intelligence. Search data shows a 45% increase in searches for 'hallucination', with overall AI-related terms growing by 62% year-on-year. Google CEO Sundar Pichai noted that the 'hallucination problem' in AI remains unresolved. The term originates from Latin, underscoring the ongoing influence of artificial intelligence on societal changes.

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.

OpenAI GPT-4 stands out on the Vectara leaderboard with only a 3% hallucination rate in document summarization and an accuracy rate of 97%. The Vectara evaluation reveals that GPT-4 Turbo and GPT-4 perform the best, followed by GPT-3.5 Turbo, while the highest-rated non-OpenAI model is Meta Llama. Vectara has released open-source models that can check the hallucination rate of language models to enhance the credibility of generative AI systems. Google's models performed moderately on the leaderboard.

Cambridge Dictionary has announced 'Hallucination' as the Word of the Year for 2023, as AI technology redefines the concept. AI tools like ChatGPT have sparked significant interest but have also raised questions about the reliability of AI-generated text. AI 'hallucinations' are having real-world impacts, involving fabricated legal cases and other practical situations. An AI ethicist from Cambridge University points out that AI 'hallucination' anthropomorphizes artificial intelligence.

The Galactica model from Meta was taken offline just three days after its release due to hallucination issues, with LeCun expressing regret. Galactica is regarded as an early attempt at large language models, positively influencing Meta's subsequent projects. The model's lead author, Ross Taylor, admitted that the foundational model was not thoroughly checked prior to release, but he still emphasized its research value. Joelle Pineau, Vice President of AI Research at Meta, highlighted that Galactica was a research project, not a product. The removal of Galactica has sparked significant discussion.

LexisNexis first revealed its Lexis+ AI initiative last May, utilizing large language models to answer legal questions. The company has lifted restrictions on Lexis+ AI, making it widely available to clients in the U.S. Lexis+ AI provides reliable results with 'hallucination-free' legal citation links. It enables conversational searching, document drafting, case summarization, and document analysis. LexisNexis claims that Lexis+ AI can enhance the speed of legal professionals.