Intelligence of Large Models Comparable to That of a Five-Year-Old Child, Says Professional at Shanghai-Chongqing Institute of Artificial Intelligence
Intelligence of Large Models Comparable to That of a Five-Year-Old Child, Says Professional at Shanghai-Chongqing Institute of Artificial Intelligence
TMTPOST—A recent news report about poor capabilities of many large AI models in solving simple arithmetic problems has sparked heated discussions in China.
TMTPOST——最近關於許多大型人工智能模型在解決簡單算術問題方面的能力不佳的新聞報道在中國引發了激烈的討論。
Users asked 12 AI models, including GPT-4o, whether "Which number is bigger? 9.11 or 9.9?" Only four models—Alibaba's Tongyi Qianwen, Baidu's Wenxin Yiyan, Minimax, and Tencent's Yuanbao—provided the correct answer, while the other eight, including ChatGPT-4o, gave incorrect responses.
用戶詢問了包括GPT-4o在內的12種人工智能模型,是否 「哪個數字更大?9.11 還是 9.9?」只有四種型號——阿里巴巴的統易千文、百度的文心一言、Minimax和騰訊的元寶——提供了正確的答案,而包括ChatGPT-4O在內的其他八個模型給出了錯誤的答案。
This discrepancy highlights significant issues with the mathematical capabilities of large AI models, showing numerous problems that need to be addressed.
這種差異凸顯了大型人工智能模型數學能力的重大問題,顯示了許多需要解決的問題。
In an exclusive interview with TMTPost, Qi Peng, Director of the AI Large Model Center at Shanghai-Chongqing Institute of Artificial Intelligence, noted that while large models have immense potential and can handle complex problems with generalization abilities, their current level of intelligence is still rudimentary.
上海重慶人工智能研究所人工智能大模型中心主任齊鵬在接受《TMTPost》獨家採訪時指出,儘管大型模型具有巨大的潛力,可以通過泛化能力處理複雜問題,但它們目前的智能水平仍處於初級水平。
Qi likened these models to "five-year-old children" due to limitations such as insufficient computational power, inadequate text data, and challenges with accuracy and reliability.
由於計算能力不足、文本數據不足以及準確性和可靠性方面的挑戰等侷限性,齊將這些模型比作 「五歲的孩子」。
Qi holds bachelor's and master's degrees at Tsinghua University and a Ph.D. from the University of Wisconsin-Madison and has extensive experience in data science and AI. Under his leadership, the Shanghai-Chongqing Institute of Artificial Intelligence has developed the "Zhao Yan" large language model, which ranked third globally and second domestically in the SuperCLUE Chinese Large Model Intelligence Benchmark in March this year.
齊擁有清華大學的學士和碩士學位以及威斯康星大學麥迪遜分校的博士學位,在數據科學和人工智能領域擁有豐富的經驗。在他的領導下,上海-重慶人工智能研究所開發了 「趙巖」 大語言模型,該模型在今年3月的SuperClue中國大型模型智能基準測試中排名全球第三,在國內排名第二。
Additionally, in July, Qi and his team, including PhD student Zhuang Shaobin, replicated the Sora text-to-video model in an open-source community project. The advanced Latte spatiotemporal decoupling attention architecture enabled the generation of 16-second (128-frame) videos, a significant improvement from the previous 3-second (24-frame) capability.
此外,在7月,齊和他的團隊,包括博士生莊少斌,在一個開源社區項目中複製了Sora文本轉視頻模式。先進的 Latte 時空解耦注意力架構支持生成 16 秒(128 幀)視頻,與之前的 3 秒(24 幀)能力相比有了顯著改進。
Qi explained that the Sora model functions like a new "tool" that addresses various issues. Beyond video generation, Sora can be applied in areas such as autonomous driving and physical world simulation. The most immediate application is in video creation, where users can input text descriptions to rapidly produce videos, thus enhancing efficiency and convenience.
齊解釋說,Sora模型的功能就像一個解決各種問題的新 「工具」。除了視頻生成,Sora 還可以應用於自動駕駛和物理世界模擬等領域。最直接的應用是視頻創作,用戶可以在其中輸入文字描述來快速製作視頻,從而提高效率和便利性。
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Qi also observed that while large models have broad applications across various sectors, real-world deployment remains limited. The primary challenges include the models' mathematical and engineering deficiencies and the inherent limitations of statistical methods in achieving 100% accuracy.
齊還觀察到,儘管大型模型在各個領域都有廣泛的應用,但實際部署仍然有限。主要挑戰包括模型的數學和工程缺陷以及統計方法在實現 100% 準確性方面的固有侷限性。
Looking to the future of artificial general intelligence (AGI) development, Qi emphasized that humanity is at a pivotal moment on the path to AGI. Although current models have not yet reached AGI standards, he believes that ChatGPT has positioned human beings at a critical juncture in history.
展望人工通用智能(AGI)發展的未來,齊強調人類正處於通往人工智能之路的關鍵時刻。儘管目前的模型尚未達到 AGI 標準,但他認爲 ChatGPT 將人類置於歷史的關鍵時刻。
While the intelligence of large models can continue to advance from a child's level to that of top experts, they will always require supportive infrastructure and tools for effective operation and application. Although developing these facilities might be relatively inexpensive, they are crucial for the practical use and societal value of large models, Qi added.
儘管大型模型的智能水平可以繼續從孩子的水平提升到頂級專家的水平,但它們始終需要支持性的基礎設施和工具來進行有效的操作和應用。齊補充說,儘管開發這些設施可能相對便宜,但它們對於大型模型的實際用途和社會價值至關重要。