AI科研

Search documents
全固态电池又有重大突破!研究团队回应
Zhong Guo Qi Che Bao Wang· 2025-10-10 01:40
近日,中国科学院物理研究所研究员黄学杰团队联合华中科技大学、中国科学院宁波材料技术与工程研究所等组成的研究团队在全固态金属锂电池界 面领域的研究成果发表在国际学术期刊《自然-可持续发展》上。 据新华社报道,美国马里兰大学固态电池专家王春生教授评价道:"该研究解决了制约全固态电池商业化的关键瓶颈问题,为实现其实用化迈出了决 定性一步。" 全固态金属锂电池的界面问题一直困扰着所有的研究人员,听闻这条重要消息,《中国汽车报》记者第一时间采访了黄学杰。 界面难题长期待解 据专家介绍,硫化物电解质与锂金属负极在1 MPa压力下,初始阻抗可降低80%。在2MPa压力下,锂沉积的枝晶生长速率降低90%。立杆见影的效果 引来多个机构进行尝试。 丰田早期的全固态电池原型就采用外部加压方式,压力达5MPa。但这种方法会增加电池体积和重量,难以商业化。 人们憧憬全固态金属锂电池的美好前景,但实现起来确实不容易。金属锂负极因其最低还原电位和超高比容量被视为锂电池中"理想负极",而全固态 电池被认为是发挥金属锂负极的最好电池体系。但自从1923年吉尔伯特•牛顿•路易斯(Gilbert N. Lewis)计算出金属锂的标准电极电位,后续 ...
超470亿元,涌入港股!
Shang Hai Zheng Quan Bao· 2025-10-05 03:27
港股市场表现活跃,持续吸引资金进场投资。据Choice数据统计显示,截至9月29日,9月以来合计超470亿元资金借道含"港"ETF,流向港股市场。其中, 互联网、创新药、科技、黄金等领域成为资金聚集地。 | 证券代码 | 基金全称 | | 9月29日基金份额(万份)8月末基金份额(万份)9月成交均价(元)9月以来资金流入金融(万元) | | | | --- | --- | --- | --- | --- | --- | | 159792.SZ | 富国中证港股通互联网交易型开放式指数证券投资基金 | 9,131,685.52 | 7,945,285.52 | 0.8485 | 1,006,685.80 | | 159636.SZ | 工银瑞信国证港股通科技交易型开放式指数证券投资基金 | 2,537,725.06 | 2,186,225.06 | 1.2787 | 449.479.77 | | 517520.SH | 永赢中证沪深港黄金产业股票交易型开放式指数证券投资基金 | 590.090.40 | 328,740.40 | 1.4347 | 374,948.18 | | 513090.SH | 易方达中证 ...
AI论文“抄观点不抄字”引激辩
Ke Ji Ri Bao· 2025-09-22 00:09
Core Viewpoint - The emergence of AI-generated research outputs is sparking intense debate in academia regarding "idea plagiarism," where AI-generated papers may appropriate others' research methods or core ideas without proper attribution [1][2]. Group 1: Incidents of "Idea Plagiarism" - A case involving a tool named "The AI Scientist" developed by Sakana AI has been highlighted, where a researcher found that an AI-generated manuscript closely resembled his own research methods without citation [2]. - The "whistleblower team" reported that multiple AI-generated manuscripts exhibit a pattern of appropriating others' ideas without direct text copying, raising concerns about the originality of these outputs [2][3]. - An evaluation of AI-generated research proposals revealed that 24% of the works achieved a similarity rating of 4-5, indicating a high degree of similarity to existing research [3]. Group 2: Definitions and Disagreements on Plagiarism - The development team of "The AI Scientist" denied the plagiarism allegations, arguing that the AI-generated manuscripts differ in hypotheses and application areas, and that citation issues are common among human researchers [4]. - There is a divergence in academic opinion regarding what constitutes plagiarism, with some experts suggesting that the similarity levels do not meet the threshold for plagiarism [4][5]. - The definition of plagiarism is further complicated by differing views on whether intent should be a factor, with some experts arguing that AI's lack of subjective awareness complicates the issue [5]. Group 3: Challenges to the Academic System - The rise of AI-generated research poses significant challenges to the existing academic framework, as the volume of papers increases, making it difficult for researchers to verify the novelty of their ideas [6][7]. - Current methods for detecting "idea plagiarism" are inadequate, with existing tools failing to identify the sources of AI-generated papers effectively [7]. - The process used by "The AI Scientist" to verify originality is criticized for being overly simplistic, as it may overlook key literature and not match the judgment of domain experts [7]. Group 4: Need for Clear Standards - There is a consensus in academia on the necessity to establish clear guidelines for the use of AI research tools [8]. - The development team of "The AI Scientist" acknowledges the quality issues in AI-generated papers and suggests that these tools should primarily be used for idea generation, with researchers responsible for verifying the reliability of the outputs [8]. - The academic community faces the challenge of balancing the potential benefits of AI in research with the need for academic integrity [8].
开学&教师节双重豪礼,英博云算力低至8毛8/卡时,赶紧薅起来
机器之心· 2025-09-02 09:33
Core Viewpoint - The article highlights the launch of the "Autumn Computing Power Gratitude Return" campaign by Yingbo Cloud Platform, aimed at supporting educators and students during the new academic season and Teacher's Day with various promotional offers and discounts on computing power services [1]. Group 1: Promotional Activities - Activity 1: "Back to School Surprise Gifts" offers low prices for computing power, with rates as low as 0.88 yuan per card hour for the 4090 model during the promotional period from September 1 to September 30 [6]. - Activity 2: "Teacher's Day Exclusive Benefits" includes a free 50 yuan computing power voucher for new users upon registration and verification, along with various rebate offers for first-time and subsequent top-ups [7][8]. - The promotional highlights include significant discounts on card hour prices, such as the A800 model reduced from 6.39 yuan to 4.92 yuan, and the H800 model from 13.99 yuan to 10.76 yuan [9]. Group 2: Platform Features - Yingbo Cloud Platform utilizes a cloud-native architecture that supports container instances with rapid start-stop capabilities and fine-grained billing, allowing users to pay only for what they use, thus reducing computing costs for schools and students [11]. - The platform supports GPU+CPU mixed clusters, InfiniBand high-speed networking, and enterprise-level parallel storage, catering to needs for model training, algorithm validation, and distributed computing [11]. - Yingbo Cloud offers a dedicated booking section for educators to reserve computing power in advance, ensuring stable operation for classes and research training, along with flexible resource allocation options [11]. Group 3: Collaboration and Future Plans - Yingbo Cloud is actively assisting multiple universities and research institutions in AI research projects and is expanding its AI course teaching partnerships for the fall of 2025 [12]. - The platform invites more universities to join the "AI Course Partner Program," encouraging collaboration in AI education and research [12].
华蓝集团2025年中报简析:营收上升亏损收窄,盈利能力上升
Zheng Quan Zhi Xing· 2025-08-26 23:08
Core Viewpoint - HuaLan Group reported a revenue increase of 6.21% year-on-year for the first half of 2025, with total revenue reaching 206 million yuan, while the net profit attributable to shareholders was a loss of 17.93 million yuan, showing a year-on-year improvement of 13.18% [1] Financial Performance - Total revenue for Q2 was 111 million yuan, up 17.35% year-on-year, while the net profit attributable to shareholders for Q2 was a loss of 8.82 million yuan, down 37.97% year-on-year [1] - Gross margin increased by 3.18% to 35.62%, and net margin improved by 22.66% to -8.19% [1] - Total expenses (selling, administrative, and financial) amounted to 46.87 million yuan, accounting for 22.73% of revenue, a decrease of 8.31% year-on-year [1] Cash Flow and Financial Position - Cash and cash equivalents decreased by 17.19% due to lower sales collections and payments of previous tax and bonus obligations [2] - Operating cash flow per share was -0.42 yuan, down 51.79% year-on-year, indicating cash flow challenges despite increased revenue from solar power generation [5] - The net increase in cash and cash equivalents was down 29.08%, attributed to decreased sales collections and increased payments [5] Asset and Liability Changes - Fixed assets increased by 45.96% due to the completion of distributed solar projects, while construction in progress decreased by 97.28% as projects were transferred to fixed assets [2] - Short-term borrowings decreased by 41.65% as the company repaid bank loans without new borrowings [2] - Long-term borrowings increased by 7.93% due to financing for solar power station construction [2] Cost and Expense Analysis - Financial expenses surged by 296.78% due to increased interest expenses from long-term loans for solar projects [4] - Sales expenses decreased by 28.3% as there were no equity incentive expenses this year, and budget control was strengthened [3] - Management expenses also fell by 12.04% for similar reasons [3] Research and Development - R&D investment increased by 10.24% as the company intensified its focus on AI research and related expenses [5] Business Model and Investment Returns - The company's historical median ROIC is 16.4%, but the worst year recorded a ROIC of -0.57%, indicating variability in investment returns [6] - The business model relies heavily on capital expenditures, necessitating careful evaluation of the profitability of these investments [6]