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Only 20% of German employees received AI training, with 70% never trained, risking EU AI Act violations. Bitkom warns firms must ensure AI skills for all workers, as AI boosts efficiency but needs proper use. 14% fear job loss to AI, 1/3 see AI replacing bosses.....

Open-source multimodal model EarthMind, designed for Earth observation data, uses spatial attention for precise localization and cross-modal fusion to integrate optical and radar data, supporting multi-granular analysis for disaster monitoring and urban planning.....

In the long-standing copyright infringement lawsuit filed by The New York Times against OpenAI, the case has made significant progress. According to Ars Technica, the federal judge presiding over the case has authorized The New York Times and its co-plaintiffs, The New York Daily News and the Investigative Reporting Center, to access OpenAI's user logs, including deleted content, to accurately determine the scope of the infringement. The New York Times believes that ChatGPT users may delete their history after bypassing the paywall, and therefore it is necessary to conduct large-scale data collection.

Recently, an AI Excel assistant called Shortcut has sparked heated discussions on social media. It enables users to effortlessly complete Excel tasks without writing complex formulas or VBA code through natural language processing (NLP) technology. The AIbase editorial team has compiled the latest information from social media to provide an in-depth analysis of Shortcut's powerful features and its potential impact on the fields of data processing and financial modeling. Shortcut: An Excel Revolution Driven by Natural Language

Large Language Models (LLMs) have achieved significant progress in complex reasoning tasks by combining task prompts with large-scale reinforcement learning (RL), as demonstrated by models like Deepseek-R1-Zero, which directly apply reinforcement learning to base models, showcasing strong reasoning capabilities. However, this success is difficult to replicate across different base model families, especially within the Llama series. This raises a core question: what factors lead to inconsistent performance of different base models during reinforcement learning? How does reinforcement learning perform in

In the field of artificial intelligence, OpenAI and Oracle recently announced a major collaboration, committing to invest in the 'Stargate' initiative, aiming to establish more data centers in the United States. This partnership is intended to meet the growing demand for computing power and to accelerate the development of AI technology. According to insiders, OpenAI will rent a large amount of computing power from Oracle's data centers, with an estimated use of about 4.5 gigawatts of electricity. The energy consumption of this data center is so large that it could power millions of American households.

Google's latest sustainability report reveals a startling fact: within just four years, the company's data center power consumption more than doubled, rising from 14.4 million megawatt-hours in 2020 to 30.8 million megawatt-hours in 2024. If the timeline is extended to ten years, compared to an estimated 4 million megawatt-hours in 2014, Google's data center power consumption has increased sevenfold. Growing electricity demand: data centers are major energy consumers, efficiency improvements face bottlenecks. Data shows that Google's power issues are almost entirely concentrated in data centers.

Recently, the AI company Anthropic invested millions of dollars to purchase and "dismantle" a large number of books for training its AI assistant Claude. This move has drawn widespread public attention and sparked heated discussions in the legal community. According to a report by the foreign media Ars Technica, Anthropic adopted a controversial method to obtain training data. They dismantled a large number of physical books, scanned them into digital files, and then destroyed the original copies. This practice was revealed in court documents.

In a recent episode of the podcast "Hard Fork," OpenAI's CEO Sam Altman voluntarily discussed the copyright lawsuit filed by The New York Times against OpenAI and its major investor, Microsoft. The lawsuit primarily accuses OpenAI of using The New York Times' content without authorization while training its large language models. Altman expressed concern about the lawsuit, particularly regarding a new request made by The New York Times' lawyers.

Recently, an intelligent academic research tool called ScholAI has attracted widespread attention. This innovative tool, based on the Multi-Cloud Platform (MCP), integrates functions such as paper search, analysis, management, CCF ranking query, and semantic query analysis, providing researchers with an efficient and intelligent academic research solution. The AIbase editorial team has compiled the latest information from the web to provide you with a comprehensive overview of ScholAI's unique advantages and future potential. Core Features of ScholAI: One

With the rapid development of artificial intelligence, data center infrastructure is facing unprecedented pressure, especially in terms of power supply and sustainability. Recently, at an industry roundtable meeting, experts discussed the major challenges faced by the UK data center industry, particularly how to maintain environmental commitments while supporting AI innovation. Image source note: The image is AI-generated. Richard Clifford, Vice President of Sales and Solutions for EMEA at MidjourneySalute Company, pointed out that our biggest

In the wave of digital transformation, Nangang Group has partnered with Huawei to launch the "YuanYe - Steel Big Model." This revolutionary model is based on Huawei's PanGu Big Model platform, aiming to connect four business interfaces throughout the steel production process, creating 20 artificial intelligence application scenarios, and comprehensively enhancing data flow and intelligence levels. To promote this transformation, Nangang Group has established a digital operation management system called "One Brain Three Centers," combined with a cloud-edge-end big data platform and an enterprise-level data hub. These measures have not only improved R&D...

Recently, Bilibili announced the integration of Qwen3 and Qwen-VL models, and based on this technology, launched InsightAgent. This initiative has significantly improved the efficiency of its commercial platforms, HuaFire and BiDa. During the recent 618 major e-commerce promotion event, Bilibili's commercial platforms leveraged InsightAgent to achieve a significant leap in commercial order conversion and data insight efficiency.