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Google's NotebookLM introduces video summaries, converting complex info into narrated slides. It auto-generates videos from user-uploaded images/charts. Demoed at I/O 2025, the feature will roll out gradually. Currently English-only, multilingual support planned.....

OpenAI launches ChatGPT Study with interactive prompts and scaffolding responses for systematic learning across subjects. Available to all users, with an Edu version coming soon. Educators see potential to transform teaching methods.....

Perplexity company launches an AI browser called Comet, which transforms YouTube videos into interactive learning tools. Users can pause videos at any time to ask questions, and the AI assistant provides instant answers and supplements related knowledge, enabling a shift from passive watching to active learning. This tool is especially suitable for complex subjects, as it optimizes answers based on user habits and offers personalized learning paths. Its deep integration with the browser environment makes responses more contextually relevant. Although still in the testing phase, it has already shown the potential to revolutionize the way education is delivered.

VLM2Vec-V2, a multimodal embedding framework developed by Salesforce Research and other institutions, breaks through the limitations of traditional models. Based on the Qwen2-VL architecture, this framework innovatively unifies image, video, and visual document retrieval tasks. It adds five new evaluation tasks to expand the MMEB dataset. With key technologies such as dynamic resolution and M-RoPE, it achieved an average score of 58.0 across 78 datasets, leading in performance, especially in video tasks. Although its document retrieval is slightly behind ColPali, it

Recently, Tmall Elf officially announced the launch of the new Wow AI Sister Machine Smart Version. This new product features a large AI screen, offering excellent audio and visual experience and smart functions. Upon its release, it immediately attracted the attention of many consumers, and now it is available for reservation across all channels. The Wow AI Sister Machine Smart Version offers users three versions to choose from, meeting different needs. The 6+128GB version has a promotional price of 3,699 yuan, the 6+256GB version is priced at 3,999 yuan, and the long-lasting battery version is 4,399 yuan.

The Qwen-MT machine translation model is officially released. Qwen-MT is based on the powerful Qwen 3 model, and has been trained on a massive amount of multilingual and translation data. It combines reinforcement learning technology to significantly improve the accuracy and fluency of translation results. Developers can experience its fast and accurate translation capabilities directly through the Qwen API (qwen-mt-turbo). The core highlights of Qwen-MT include supporting bidirectional translation between 92 languages, covering more than 95% of the global population, and meeting a wide range of language communication needs.

WordPecker is an open-source AI language learning tool featuring personalized vocab extraction, 100+ languages, voice chat with OpenAI Agent, and interactive exercises. It represents the future of smart language learning.....

Recently, the ByteDance Seed team collaborated with the University of Hong Kong and Fudan University to introduce an innovative reinforcement learning training method called POLARIS. This method successfully enhances the mathematical reasoning capabilities of small models to levels comparable to those of large models through a carefully designed Scaling RL strategy, offering a new approach for optimizing small models in the field of artificial intelligence. Experimental results show that the 4 billion parameter open-source model Qwen3-4B trained using POLARIS achieved remarkable performance on AIME25 and AIME24 mathematical tests.

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

New Oriental officially launched its first consumer-facing original AI education product - New Oriental AI 1-on-1 today. This is not only a major breakthrough in teaching methods, but also marks a critical step in New Oriental's strategic layout of "Education + AI." The core competitiveness of New Oriental AI 1-on-1 lies in providing learners with a high-frequency interactive 1-on-1 learning experience. The AI teacher can realistically reproduce the learning environment, achieving real interaction and real Q&A. At the same time, the AI teacher is patient, responsible, proficient in teaching, and can provide timely feedback, as well as praise and encourage students.

Recently, a research team from the University of Hong Kong, The Chinese University of Hong Kong, and SenseTime has released a groundbreaking framework - GoT-R1. This new multimodal large model significantly enhances the semantic and spatial reasoning capabilities of AI in visual generation tasks by introducing reinforcement learning (RL), successfully generating high-fidelity and semantically consistent images from complex text prompts. This advancement marks another leap in image generation technology. Currently, although existing multimodal large models have made significant progress in generating images based on text prompts

As enterprises accelerate the adoption of AI technologies, effectively managing complex AI workflows has become a key challenge. Latest industry analysis indicates that building a robust AI orchestration layer is an effective solution to address prompt chaos. The Dilemma in Choosing AI Orchestration Frameworks: Currently, there are many AI orchestration tools and frameworks on the market, including well-known solutions like LangChain, which presents a challenge for enterprise technology selection.

On June 18, 2025, the technology media outlet VentureBeat officially announced the finalists for the 2025 Women in AI Awards. This award aims to honor female leaders and innovators who have made outstanding contributions in the field of artificial intelligence. Background and Significance: The VentureBeat Women in AI Awards was established in 2023 and is the first authoritative award in the AI industry to specifically recognize women practitioners.

On June 18, 2025, technology media VentureBeat officially announced the finalists for the 2025 Women in AI Awards. This award aims to honor outstanding contributions by women in the field of artificial intelligence and promote industry diversity. The background and significance of the award: Launched in 2020, the VentureBeat Women in AI Awards have become one of the most prestigious female-exclusive honors in the AI industry.

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.

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.}