long sleeves and the collars. Stay stiff all day. Get 20% off using code TV at collars and co.com. >> Tech stocks are still ripping higher today. Nvidia, Microsoft, Broadcom.These are all fresh record highs. But Deirdre Bosa has a new deep dive on an overlooked problem with the latest wave of AI models, which has powered much of the recent rally. Deirdre what can you tell us.So Kelly the next frontier in AI. It's not just chatting or summarizing, it's reasoning. And that means thinking through problems, mak ...

Core Insights - The article discusses the emergence and evolution of "Deep Research" systems in the AI Agent exploration wave, highlighting the rapid development and competition among major players like Google, OpenAI, and Anthropic since late 2024 [1][2] - A comprehensive survey from Zhejiang University provides a framework for understanding and evaluating the current landscape of deep research systems, emphasizing the shift from model capability to system architecture and application adaptability as the main competitive focus [1][2] Group 1: Current Landscape and System Comparisons - The ecosystem of deep research systems is characterized by significant diversity, with different systems focusing on various technical implementations, design philosophies, and target applications [3] - Key differences among systems are evident in their foundational models and reasoning efficiency, with commercial giants leveraging proprietary models for superior performance in handling complex reasoning tasks [4] - Systems also differ in tool integration and environmental adaptability, showcasing a spectrum from comprehensive platforms to specialized tools [5] Group 2: Application Scenarios and Performance Metrics - In academic research, systems like OpenAI/DeepResearch excel due to their rigorous citation and methodology analysis capabilities, while in enterprise decision-making, systems like Gemini/DeepResearch thrive on data integration and actionable insights [8] - Performance metrics reveal that leading commercial systems maintain an edge in complex cognitive ability benchmarks, although specialized evaluations highlight the strengths of various systems in specific tasks [9][10] Group 3: Implementation Challenges and Technical Solutions - The implementation of deep research systems involves strategic trade-offs across architecture design, operational efficiency, and functional integration [12] - Core challenges include managing hallucination control, privacy protection, and ensuring interpretability, with solutions focusing on source grounding, data isolation, and transparent reasoning processes [15] Group 4: Evaluation Frameworks - The evaluation of deep research systems is evolving from single metrics to a multi-dimensional framework that assesses functionality, performance, and contextual applicability [16] - Functional evaluations focus on task completion capabilities and information retrieval quality, while non-functional assessments consider performance efficiency and user experience [17][18] Group 5: Future Directions in Reasoning Architecture - Future advancements in deep research systems are expected to address limitations in context window size, enabling more comprehensive analysis of large-scale research materials [22][23] - The integration of causal reasoning capabilities and advanced uncertainty modeling will enhance the systems' applicability in complex fields like medicine and social sciences [27][30] - The development of hybrid architectures that combine neural networks with symbolic reasoning is anticipated to improve reliability and interpretability [25][26]

Links:- ML for Beginners: https://t.co/4BjD3ePOET- AI for Beginners: https://t.co/RMGBL5sRfe- NN Zero to Hero: https://t.co/BGKZvCTGeN- Paper implementations: https://t.co/SN0DH2BLQq- Made with ML: https://t.co/2xrM6s50X0- Hands-on LLMs: https://t.co/KTZUVbsAFY- Advanced RAG techniques: https://t.co/3n1fgpc72t- Agents for Beginners: https://t.co/O52uS8quyh- Agents towards production: https://t.co/3n1fgpc72t- AI Engg. Hub: https://t.co/b2WVNQqcBANote: This roadmap moves toward LLMs, NLP, and AI agents after ...

Core Insights - The "2025 Data Intelligence Conference" was held in Beijing, where the China Academy of Information and Communications Technology (CAICT) released the "AI Agent Industry Map 1.0" to outline the landscape of the AI agent industry, core technologies, and commercial pathways [1][3] - Kaimiride was recognized as one of the first representative vendors in the "Marketing AI Agent" category due to its self-developed AI agent platform and deep applications of AI in the financial sector [1][3] Industry Overview - The rapid development of AI technologies, particularly large models, is transforming AI from a singular application into a core engine driving the transformation of various industries [3] - The "Government Work Report 2025" emphasizes the continuation of the "Artificial Intelligence +" initiative, supporting the widespread application of large models [3] Company Highlights - Kaimiride's AI agent platform integrates cutting-edge AI technologies, featuring capabilities in intelligent perception, autonomous decision-making, efficient execution, and real-time feedback, while supporting mainstream large model access and secure private deployment [4] - In marketing scenarios, the platform enhances efficiency in peer marketing by intelligently analyzing and generating recommendation lists for peer clients, significantly improving the efficiency of traditional client selection methods [5] - The platform also upgrades retail marketing by deeply understanding customer needs and risk preferences, intelligently recommending suitable financial information and investment products, thereby enhancing customer experience and conversion rates [5] - The recognition in the "AI Agent Industry Map 1.0" marks a significant milestone for Kaimiride in the integration of AI and financial technology innovation [5] - Kaimiride plans to increase R&D investment and deepen the application of AI agent technology in financial scenarios, aiming to provide smarter and more efficient solutions for financial institutions [5]

Investment Rating - The industry investment rating is "Positive" (维持) [6] Core Viewpoints - The report is optimistic about the development of the electricity market, which brings new opportunities for the electricity system [3] - The transition from passive reliance on natural conditions to active participation in market operations is a core variable for optimizing economic efficiency in the industry [8] - The report highlights the importance of electricity market trading capabilities, especially in regions like Xinjiang and Inner Mongolia, where new projects will rely heavily on market transactions [8] Summary by Relevant Sections - **Electricity Market Development**: The report emphasizes the positive outlook for the electricity market, driven by reforms that enhance market participation and efficiency [3][8] - **New Energy Projects**: New energy projects in regions like Xinjiang and Inner Mongolia are expected to shift from subsidy-dependent models to market-driven mechanisms, with specific pricing structures outlined for different project types [8] - **Software and Hardware Opportunities**: The report suggests focusing on companies involved in software applications for electricity trading and hardware that supports market transactions, recommending specific companies for investment [8] - **Active Value Creation**: The shift from passive to active value creation in the new energy sector is expected to unlock significant investment opportunities, with several companies identified as potential beneficiaries [8]

Market Overview - The three major indices opened mixed, with the Shanghai Composite Index down 0.12% and the Shenzhen Component Index down 0.04%, while the ChiNext Index opened up 0.02% [1] - The military industry and diversified finance sectors showed the highest gains, while innovative drugs and composite materials sectors experienced the largest declines [1] Index Performance - Shanghai Composite Index: 3451.72, down 0.12%, with a trading volume of 61.03 billion [2] - Shenzhen Component Index: 10389.23, down 0.04%, with a trading volume of 102.07 billion [2] - ChiNext Index: 2128.86, up 0.02%, with a trading volume of 49.77 billion [2] External Market Influences - U.S. stock indices showed mixed results, with the Dow Jones down 106.59 points (0.25%) and the Nasdaq up 61.02 points (0.31%) [3] - The Nasdaq Golden Dragon China Index fell by 0.6%, with significant declines in several Chinese concept stocks [3] Institutional Insights - CITIC Securities expects MLF and reverse repos to maintain net injections, projecting a net injection of 118 billion yuan in June 2025 [4] - Huatai Securities highlights a positive policy outlook aimed at boosting consumer credit demand, with 19 specific measures to support consumption [5] - Guojin Securities emphasizes the growth potential in the electronics sector, particularly in AI-PCB and computing hardware, with strong demand expected in the second and third quarters [6] - China Galaxy Securities notes a mismatch in domestic AI investment, suggesting that the second half of the year presents a good opportunity for investment [7]

Finally! You can reliably test AI Agents without humans:- One Agent asks questions.- The Agent being tested responds.- Another Agent Judges.Here’s a complete breakdown (with code): https://t.co/wDm2a4zN0bAvi Chawla (@_avichawla):How Agents test Agents, clearly explained (with code): ...

Data cybersecurity company Rubrik announced Wednesday its intent to acquire Predibase. Predibase is a venture-backed startup that helps companies train and fine-tune open source AI models to customize them to their needs. Rubrik is the latest company to make an acquisition with the goal of boosting enterprise AI agent adoption. Terms of the deal were not disclosed, though CNBC reported that the deal was between $100 million and $500 million, a sizable range. Rubrik declined to comment on the deal size. Pr ...

Group 1 - The Hong Kong stock market opened higher, with the Hang Seng Tech 30 ETF rising by 0.9%, continuing the upward trend from the previous day [1] - The company Mifus (02556) led the sector with a 6.25% increase, having accumulated over 15% growth in the last two trading days, currently trading at 47.9 HKD with a transaction volume of 118 million HKD [1] - Mifus has been ranked first in the "Top 50 AI SaaS Influential Enterprises" list for seven consecutive years, showcasing its market leadership [1] Group 2 - The company has achieved high revenue growth and significantly improved cash flow, driven by its AI + SaaS ecosystem, which has enabled breakthroughs in both small and key account markets [2] - Customer stickiness continues to improve, with the commercialization of AI Agent accelerating, contributing to sustained performance growth [2] - The company's T-cloud product is deepening its presence in the small and medium-sized business (SMB) market, while the Zhenke product is expanding into large enterprise clients, covering five major industries [2]

截至2025年6月25日 10:14，中证人工智能主题指数(930713)上涨0.76%，成分股润泽科技(300442)上涨5.15%，石头科技(688169)上涨4.84%，深桑达 A(000032)上涨3.17%，光环新网(300383)上涨3.09%，科沃斯(603486)上涨2.46%。AI人工智能ETF(512930)上涨0.68%，最新价报1.33元。 规模方面，AI人工智能ETF最新规模达20.34亿元。 消息面上，谷歌DeepMind团队发布首个可以完全在机器人本地运行的视觉-语言-动作（VLA）模型Gemini Robotics On-Device。这个模型不仅能离线运行， 还保持了相当强悍的操作能力，能遵循指令完成各种需要精细操作的任务。支持从人形机器人到工业双臂机器人的多种机器人本体上部署，响应延迟低。此 前3月份发布的Gemini Robotics虽然性能强大，但需要依赖云端计算。而这次的On-Device版本，直接把AI塞进了机器人的"大脑"里，彻底解决了网络延迟和 连接不稳定的问题。 民生证券指出，AI Agent解决了生成式AI模型的应用局限，推动AI技术向实用、智能方向发展：海 ...