智东西2月13日报道，今天凌晨，AI独角兽Anthropic宣布已完成300亿美元（约合人民币2070.19亿元）G轮融资，投后估值达3800亿美元（约 合人民币2.62万亿元），公司年化经常性收入已达140亿美元（约合人民币699.09亿元），在过去三年中每年平均增长超10倍。 ▲Anthropic公告（来源：X） 据Anthropic公告透露，本次融资的资金将助力前沿研究、产品开发及基础设施扩建，目前Claude是唯一在三大全球云平台Amazon Web Services Bedrock、Google Cloud Vertex AI、Microsoft Azure Foundry同时可用的AI模型。 消息一经发布，马斯克立刻跳出来质疑Anthropic的Claude模型涉及种族和性别歧视的问题。 ▲马斯克发表质疑（来源：X） 有网友在下方评论称"求你了Elon，好好搞一下Grok吧。"马斯克回复道："4.2会更好。" | woke reply == (") | | Please Elon, work on Grok a little bit more, few days ago gave me a pre ...

Core Viewpoint - The article discusses a significant review paper titled "AI Meets Brain," which bridges cognitive neuroscience and artificial intelligence, focusing on how human memory mechanisms can inform the development of human-like memory systems in agents [2][6]. Summary by Sections Memory Definition - Memory is redefined as not just data storage but as a cognitive link that connects past experiences with future decisions, involving a two-stage process in the human brain [6]. Perspectives on Memory - From a cognitive neuroscience perspective, memory serves as a bridge between past and future [6]. - For large language models (LLMs), memory exists in three forms: parametric memory, working memory, and explicit external memory [7]. - Agent memory transcends simple storage, functioning as a dynamic cognitive architecture that integrates experiences and environmental feedback [8]. Importance of Memory - Memory plays a crucial role in enhancing agent capabilities by overcoming context window limitations, building long-term personalized profiles, and driving experience-based reasoning [12][13]. Memory Classification - The review categorizes memory based on cognitive neuroscience definitions, distinguishing between short-term and long-term memory, with long-term memory further divided into episodic and semantic memory [15][21]. Memory Storage Mechanisms - Memory storage in the human brain involves dynamic cooperation across brain regions, while agent memory systems are explicitly engineered to optimize data structure selection for computational efficiency [31][32]. Memory Management - Memory management in agents is a continuous process involving extraction, updating, retrieval, and application, contrasting with the static nature of traditional memory systems [33][34]. Future Directions - Future agent memory systems should aim for omni-modal capabilities, integrating various data types beyond text, and facilitating skill transfer across different agents [49][50].

Claude can now connect to @benchling, PubMed, and https://t.co/poBaIt4Qz9, among other platforms. And our new Agent Skills can help Claude follow scientific protocols and procedures consistently. ...