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China's smart speaker market rebounded in 618 2025, with online sales reaching 802K units (+7.5% YoY) and revenue up 15.2%. AI model adoption (36.8% products) drove growth. Xiaomi and Baidu's new models led innovation in voice interaction. The market revival after 4-year slump signals sustained AI-driven expansion.....

At the 2025 new product launch event held recently in Xi'an, Philips Audio and Accessories Company introduced three groundbreaking products, attracting the attention of many tech enthusiasts. These new products include the "Blade" magnetic charging power bank designed for young white-collar workers and Generation Z, the 8 Pro AI Earphones tailored for business elites, and the KTV Cloud Speaker suitable for family entertainment. This series of innovative products not only highlights Philips' leadership in the consumer electronics field, but also marks the opening of a new market segment in China. Among them, the most eye-catching

Recently, Google announced that the API of its flagship AI model, Gemini2.5Pro, has been reintroduced to the free tier of Google AI Studio. This news has triggered widespread attention and enthusiastic discussions within the developer community. According to AIbase, this move marks another important advancement in Google's efforts to popularize AI technology, offering developers lower barriers to innovation. As the most advanced AI model from Google so far, Gemini2.5Pro is known for its exceptional multimodal capabilities and strong reasoning power.

Recently, Google officially launched a new command-line tool - Gemini CLI. This tool is based on Google's self-developed Gemini2.5Pro AI model, aiming to provide developers with convenient AI Q&A and content generation services. With Gemini CLI, developers can directly call the power of AI in their own terminal interface, thereby improving programming efficiency and work convenience. One of the highlights of Gemini CLI is its support for up to 1 million tokens

Recently, Google accidentally published a blog post about the Gemini CLI, but the page is now returning a 404 error. The unpublished article revealed several key features of the Gemini CLI, sparking discussions in the developer community. The content indicates that the Gemini CLI is an open-source command-line interface (CLI) tool for Gemini2.5Pro, supporting a context window of up to 1 million tokens, suitable for handling complex code and large-scale data.

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

At the recently held 'Force Primordial Power Conference', ByteDance’s Volcano Engine officially launched the DouBao large model 1.6 and video generation model Seedance 1.0pro. This release marks another leap forward in AI technology, particularly in multi-modal understanding and video generation, demonstrating strong market competitiveness. DouBao 1.6 has performed excellently in multiple international authoritative evaluations, especially excelling in complex reasoning and competition-level mathematics tests. Tan Dai, President of Volcano Engine, stated that this model not only supports multi-

At the FORCE Original Power Conference, Volcano Engine officially launched BeanPod Large Model 1.6 and its new video generation model Seedance 1.0 Pro, marking a comprehensive upgrade of AI cloud-native full-stack services. As a leading family of multimodal, high-value models, BeanPod Large Model 1.6 has undergone significant improvements in functionality and performance. ByteDance CEO Liang Ruobo stated at the launch event that BeanPod Large Model 1.6 adopts a unified pricing model, creating an input length-based pricing approach.

OpenAI announced a major price cut of 80% for its flagship reasoning model o3 and simultaneously launched the high-performance o3-pro model. This move significantly reduces developer costs, triggering a new round of competition in the AI market. o3 Price Drop Significantly OpenAI has made significant adjustments to the pricing of the o3 model as follows: Input Tokens: Original price was $10 per million tokens, now reduced to $2 per million tokens. Output Tokens: Original price was $40 per million tokens, now reduced to $8 per million tokens. Cached Input Tokens: An additional 75% discount is provided.

Recently, OpenAI announced the launch of its latest o3-pro AI model, which is designed to provide more reliable and accurate responses for enterprises. As an advanced version of the o series inference models, o3-pro supports more software tool integrations and is particularly suitable for businesses and developers requiring high precision and accuracy. However, the response speed of o3-pro has slowed down compared to previous models. OpenAI stated that due to o3-pro's enhanced capabilities with richer tools, it needs extra time when handling complex problems.

Recently, OpenAI's ChatGPT has experienced some ups and downs, causing chaos among global users due to its downtime. The company quickly released the new-generation model — o3-pro. This upgraded model is more precise in handling complex problems and demonstrates significant advantages in scientific research, programming, education, and writing, becoming more intelligent and feature-rich. The o3-pro model is now available to Pro and Team users, replacing the original o1-pro, Enterp

In the recent Fiction.Live benchmark test, Gemini2.5Pro performed excellently in understanding and reproducing complex stories and backgrounds, leading ahead of OpenAI's o3 model. This test goes far beyond traditional "needle-in-a-haystack" tasks, focusing on a model's ability to handle deep semantics and context-dependent information within large contexts. According to the test data, when the context window length reaches 192,000 tokens (approximately 144,000 words), the performance of the o3 model drops sharply, while