**Bengio团队提出多模态新基准，推动通用人工智能发展**
近日，加拿大Mila人工智能研究所的张天宇博士及其团队在人工智能领域取得重要突破。他们提出了多模态新基准，旨在推动通用人工智能（AGI）的发展。该研究团队强调，达成通用人工智能的关键在于让模型完成人类所能轻松完成的任务。为此，大模型开发需探索如何让机器像人类一样思考和推理。
该研究的核心在于他们提出的注意力机制和思维链技术。其中，注意力机制能够帮助机器在处理复杂任务时聚焦于关键信息，而思维链则模拟了人类的决策过程，使得机器能够按照一定的逻辑和推理顺序执行任务。这种技术不仅优化了现有模型的性能，还拓宽了人工智能的应用领域。尤其是他们在多模态领域的探索成果引人注目，包括音频预训练模型和关键词转字幕技术。目前张天宇博士的研究成果已在机器学习顶级会议上发表多篇论文。为此领域做出卓越贡献的图灵奖得主Yoshua Bengio教授对其研究寄予厚望。随着技术的不断发展和成熟，未来的机器可能会像人类一样进行多任务处理和智能化决策。对于机器之心AIxiv专栏的广大读者来说，这是一个值得关注和期待的领域。如果您对研究感兴趣或有优秀的工作想要分享，欢迎投稿至机器之心的邮箱：[投稿邮箱]。机器之心将持续关注并报道该领域的最新进展。
英语如下：
News Title: “Bengio Team Challenges GPT-4 and Claude 3.5 with New Benchmark: Exploring a New Path for General AI”
Keywords:
News Content: **Bengio Team Proposes Multimodal New Benchmark to Promote the Development of General Artificial Intelligence**
Recently, Dr. Zhang Tianyu and his team from the Mila Artificial Intelligence Institute in Canada have made significant breakthroughs in the field of artificial intelligence. They have proposed a multimodal new benchmark aimed at promoting the development of Artificial General Intelligence (AGI). The research team emphasizes that the key to achieving AGI is to enable models to complete tasks that humans can easily perform. Therefore, the development of large models needs to explore how to make machines think and reason like humans.
The core of this research lies in the attention mechanism and thinking chain technology they proposed. The attention mechanism helps machines focus on key information when dealing with complex tasks, while the thinking chain simulates human decision-making processes, enabling machines to perform tasks in a certain logic and reasoning order. This technology not only optimizes the performance of existing models but also broadens the application areas of artificial intelligence. Their research achievements in the multimodal field are particularly noteworthy, including audio pre-training models and keyword-to-subtitle technology. Dr. Zhang Tianyu’s research has been published in multiple papers at top machine learning conferences. Professor Yoshua Bengio, a Turing Award winner who has made outstanding contributions in this field, places high hopes on his research. With the continuous development and maturity of technology, future machines may perform multi-task processing and intelligent decision-making like humans. This is an area worthy of attention and expectation for readers of the machine learning AIxiv column. If you are interested in the research or have excellent work to share, please feel free to submit it to the email of machine learning AIxiv [email address]. Machine learning AIxiv will continue to pay attention to and report the latest progress in this field.
【来源】https://www.jiqizhixin.com/articles/2024-06-28-17
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