CSHL 2020 Conference "From Neuroscience to Artificially Intelligent Systems," Cold Spring Harbor, New York, March 24-28, 2020

会议主题为“从神经科学到人工智能系统”，将在冷泉港实验室举行，将汇集来自神经科学、认知科学、机器学习和计算机科学等不同学科的研究人员，阐明一种融合方法，探索人工智能系统的新方向。而机器学习（ML）和人工智能（AI）已经彻底改变了我们处理大型数据集并推断其中模式的能力。机器学习和人工智能的算法进步创造了全新的经济领域，并有可能带来无数的社会效益。然而，与人工系统相比，自然系统更善于与世界互动。此外，它们这样做的处理和能量限制要少得多。本次会议的指导原则是，神经科学的见解对于设计下一代人工智能和机器学习系统至关重要。这次会议将汇集来自人工智能和神经科学学科的国际科学家。参与者将来自学术中心、研究机构和工业中心，包括该领域的领导者、知名研究者、初级教师、博士后研究员和研究生。这种广泛的代表性将使科学主题的出色覆盖，同时为参与者之间的协同互动提供机会。亲密和非正式的环境将促进社区一级对该领域的挑战和机遇的讨论。该项目的结果将通过确定新的和简单的方法来从大脑功能的见解中提取设计ML和AI算法，从而产生广泛的影响。受邀的研讨会参与者将包括非常多样化的参与者，以实现多个方面的多样性，包括教师级别、性别、代表性不足的群体和机构多样性。这种方法将促进早期职业研究人员的科学和专业发展，并将来自传统上代表性不足的群体的科学家纳入其中。研讨会将汇集不同学科的研究领导者进行深入讨论，旨在利用神经科学的见解来设计下一代机器学习和人工智能系统。这次会议将集中讨论最成功的统一范例，并寻求探索其基础和推广。会议将确定生物学、进化论和神经科学的工具、模型和理论，这些工具、模型和理论可用于催化人工智能系统的新设计，这些系统可能与自然系统一样熟练。这一活动与《国家人工智能研究与发展战略计划》是一致的，该计划确定了其首要战略目标，即需要在人工智能有长期回报潜力的领域对人工智能研究进行长期投资。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The conference,"From Neuroscience to Artificially Intelligent Systems", to be held at Cold Spring Harbor Laboratory will bring together researchers from diverse disciplines such as neuroscience, cognitive science, machine learning and computer science to articulate a convergence approach to explore new directions in artificially intelligent systems. While machine learning (ML) and artificial intelligence (AI) has revolutionized our ability to process large data sets and infer patterns within them. Algorithmic advances in ML and AI have created entirely new sectors of the economy and have the potential for myriad societal benefits. However, natural systems remain more adept at interacting with the world compared to artificial ones. Moreover, they do so with considerably less processing and energetic constraints. The guiding principle of this conference is that insights from neuroscience are vital for designing the next generation of AI and ML systems. This meeting will assemble an international gathering of scientists from both AI and neuroscience disciplines. Participants will be drawn from academic centers, research institutes and industrial centers and will include leaders in the field, established investigators, junior faculty, postdoctoral fellows, and graduate students. This broad representation will enable excellent coverage of the scientific topics while providing opportunities for synergistic interactions among the participants. The intimate and informal setting will promote community-level discussion of challenges and opportunities for the field. The results of this project will achieve broad impact by identifying new and facile approaches to draw from insights into brain function to design ML and AI algorithms. Invited workshop participants will include a very diverse range of participants in order to achieve diversity across a number of dimensions, including faculty rank, gender, underrepresented groups and institutional diversity. This approach will facilitate the scientific and professional development of early career researchers as well as the inclusion of scientists from traditionally underrepresented groups.The workshop will bring together research leaders across diverse disciplines for intensive discussions aimed at leveraging insights from neuroscience to design the next generation of machine learning and artificially intelligent systems. This meeting will focus on the most successful examples of unification and seek to explore their basis and generalization. The meeting will identify tools, models and theories from biology, evolution and neuroscience that can be used to catalyze new designs of artificially intelligent systems that can potentially be as adept as natural ones. This activity is consistent with the National Artificial Intelligence Research and Development Strategic Plan, which identifies as its first strategic objective the need to make long-term investments in AI research in areas with the potential for long-term payoffs in AI.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.