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Recently, Google officially launched its latest text-to-image model **Imagen4** through the Gemini API, marking an important milestone in the field of generative AI (AIGC). According to Google's official blog and community feedback, Imagen4 has achieved breakthroughs in generating text within images, solving a long-standing technical bottleneck in AIGC, and providing developers with a tool for creating high-quality visual content. It is reported that the model comes in two versions: **Imagen4** and **Imagen4Ultra**, with respective pricing details yet to be fully disclosed.

Anthropic, an American startup focused on generative artificial intelligence, recently announced the launch of a new feature called "Artifacts," which allows users to create personalized applications. Users can create by means of simple conversations without any programming knowledge. This feature's release marks an important step for Anthropic in the field of artificial intelligence application development. The Artifacts feature was initially launched last June and became available to all users in August. Users can access it next to the conversation window.

Recently, Ryan Roslansky, CEO of LinkedIn, stated that the number of job postings mentioning AI on the platform has increased sixfold over the past year. At the same time, the number of users adding AI skills to their profiles has shown even more significant growth, increasing by a full twentyfold. This change indicates that an increasing number of professionals are reshaping their career identities by incorporating AI-related skills, even if their actual experience may not be extensive. Roslansky

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.

The plan's advancement has triggered dissatisfaction among developers. According to VentureBeat, OpenAI's current API deprecation involves the GPT-4.5 Preview version, which is an intermediary model launched between GPT-4 and GPT-5. Multiple developers have stated that this sudden change has disrupted their development plans, forcing significant adjustments to applications already built based on this API. A developer who wished to remain anonymous commented: We understand the necessity of technological iteration, but the lack of sufficient buffer time in the schedule has brought additional pressure to development teams.

{ title: Anthropic Develops Explanable AI Technology Or Will Reshape Enterprise Large Language Model Strategy, content: Artificial intelligence research company Anthropic recently announced that it is developing an 'explainable' AI system. This technology is expected to allow enterprises to better understand the decision-making process of large language models (LLMs). This breakthrough study may have a profound impact on companies' strategies for applying LLMs.}

According to AIbase, AI code editor Cursor announced on June 17, 2025, a major upgrade for its Pro plan, officially removing the monthly 500 fast request limit and launching the long-anticipated 'unlimited use' mode. This move is seen as a milestone change by Cursor in responding to user demands and enhancing developer experience. AIbase pointed out that for a long time, the 500 fast request limit of the Cursor Pro plan has sparked extensive discussions among users. Many developers have reflected that in high-intensity coding environments

According to the latest prediction from Gartner, by 2028, 80% of generative AI business applications will be developed on existing data management platforms. This shift is expected to reduce development complexity and cut delivery time in half. Currently, the development of generative AI business applications mainly relies on combining large language models (LLMs) with corporate internal data, as well as evolving technologies such as vector search, metadata management, prompt design, and embedding techniques. However, without a unified management approach, companies may...

Earth System Models are crucial tools for predicting environmental changes, helping us better prepare for the future. However, these models have extremely high computational demands, limiting their operation at fine enough resolutions. Currently, most models operate at a resolution of approximately 100 kilometers, equivalent to the size of Hawaii, making accurate predictions for specific regions difficult. Nevertheless, for practical applications such as agriculture, water resource planning, and disaster response, city-scale prediction accuracy around 10 kilometers is vital. Therefore, improving the resolution of these models is essential for better protection.

Repello AI is a startup focused on generative AI security. The company recently secured $1.225 million in seed funding to further its mission of protecting generative AI systems from emerging threats. Founded in 2024, the company is dedicated to building continuous AI red team testing and security protection solutions, with two flagship products: ARTEMIS and Repello Guard. This round of financing was supported by multiple investment institutions, including one that has been integrated into G.

Recently, a new artificial intelligence (AI) plan from the Trump administration has attracted widespread attention. The plan aims to promote the application of AI technology across the entire federal government. A code repository named 'AI.gov' was discovered on GitHub. Although the page disappeared quickly after our inquiry, we still managed to capture backup information. Image source note: The image is generated by AI, and the image authorization service provider is Midjourney. According to backup data, the General Services Administration (GSA) and its Technology Transformation Services (TTS) team are

According to Science and Technology Daily, the world's first generative artificial intelligence radiology system integrated into clinical processes developed by Northwestern University School of Medicine is revolutionizing medical imaging diagnostics. This system can identify life-threatening conditions within milliseconds, providing an innovative solution to the global shortage of radiologists. The AI system has been fully deployed in 12 hospitals affiliated with Northwestern University. In five months of actual application in 2024, the system successfully analyzed nearly 24,000 radiology reports, increasing report generation efficiency by an average of 15.5%, boosting work efficiency for some doctors.

In today's cybersecurity battleground, the rapid rise of AI is placing unprecedented pressure on security operations teams. According to a recent survey of 500 senior cybersecurity experts from large U.S. enterprises, 86% of respondents increased their use of AI technologies over the past year to combat a rising tide of AI-driven attacks. While AI tools have helped security teams in threat detection and data analysis, it is concerning that nearly 70% of professionals believe that AI and other emerging technologies are making things worse.