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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

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, Volc Engine officially announced the launch of the enterprise AI mid-platform HiAgent 2.0, aiming to address real-world business needs and pain points in the development of Agent applications, helping enterprises achieve efficient delivery of intelligent bodies from development to operations. HiAgent 2.0 is positioned as an enterprise AI mid-platform, and compared to its predecessor HiAgent 1.0, it has expanded in four dimensions of functionality. Upwardly, HiAgent 2.0 provides more industry scenario templates and a rich plugin market, significantly lowering the barrier to building intelligent bodies; towards

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

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.

On June 18th, the artificial intelligence research institute OpenAI officially open-sourced its customer service agent framework, marking an important step in the company's layout of enterprise-level AI solutions. This framework aims to promote the practical commercial application of intelligent agent systems from laboratory environments to real-world scenarios by providing transparent toolchains and clear implementation examples.

Artificial intelligence research company Anthropic recently announced its latest progress in explainable AI (Interpretable AI) technology, which aims to make the decision-making process of large language models more transparent. This breakthrough may have a profound impact on how enterprises formulate strategies for applying large language models. The core technology breakthrough developed by Anthropic allows researchers to understand the model's thinking process and trace the underlying logic leading to specific conclusions.

An artificial intelligence research company, Anthropic, is developing AI systems with 'explainability' that enables users to understand the decision-making processes of large language models (LLMs). This breakthrough research may have a profound impact on enterprises' strategies for applying large language models. Breakthrough Technology: Peering into the AI 'Black Box' Anthropic's research focuses on solving the 'black box' problem of current generative AI systems.

Learn how AICosts.ai helps businesses manage the costs of AI services like ChatGPT and Claude, addressing core issues such as fragmented billing management across multiple platforms, cost anomaly monitoring, and cross-platform optimization.

This comprehensive review of the Solar AI development tool examines how it generates complete applications via natural language input, reducing 83% of development time. Explore Solar's core features, use cases, and comparisons with mainstream tools to determine if it can truly deliver on its 'light-speed development' promise.