Podcasts

In this episode, Li Guangmi interviews Zhang Xiangyu, Chief Scientist of Jieyue Xingchen, for an in-depth analysis of the ten-year development and future trends of Multimodal AI. Zhang Xiangyu shares his academic experience in deep learning, Model Scaling, and focuses on discussing the counterintuitive phenomenon encountered in the training of current LLMs: while general capabilities are enhanced, reasoning (especially mathematical) abilities may decline. He analyzes that this is related to the inherent limitations of the Next Token Prediction Paradigm, and introduces how the O series models effectively solve this problem by introducing the Chain of Thought (CoT). In addition, the interview delves into the challenges of visual and language Multimodal AI fusion in understanding and generation integration, as well as the two potential "GPT-4 moments" of future AI: long context and model Online Learning/Autonomous Learning, emphasizing the importance of learning from nature's feedback. The episode offers profound insights from a leading scientist on the forefront of AI technology.

This episode features Peter Deng, a former product executive at OpenAI, Instagram, Uber, Facebook, and other leading companies, offering an in-depth analysis of the keys to building and scaling products to reach a billion users. Peter shares the counter-intuitive lesson learned at Uber that 'the product itself is not that important,' emphasizing that users consume the overall experience. (This includes factors like price, efficiency, and customer service.) He believes that tech giants often succeed through the effective application of existing technologies rather than relying solely on technological breakthroughs. The podcast elaborates on the importance of establishing strategic thinking and a growth team during the scaling phase. Peter introduces his unique framework of five types of product managers and shares key hiring strategies, such as the 'six-month rule,' emphasizing the recruitment of complementary skills and a growth mindset. His unique insights into AI's disruption of education highlight the increasing importance of the ability to ask questions and advanced abstract reasoning. Furthermore, he discusses AI startup moats (competitive advantages through exclusive data and workflow integration), the value of AI product teams, effective upward communication strategies, and learning from failure, providing valuable guidance and career development insights for technology practitioners.

This podcast, compiled by host Zhuang Minghao from his course content, focuses on the AI industry's three core themes in June 2025: technology, products, and capital. On the technology side, it discusses the growing consensus around Agents as a key industry focus, the continuous improvement of L2 Inference Model capabilities, and the role of pre-training, post-training, and Reinforcement Learning in evolving model capabilities, especially the new trends of Synthetic Data and Reinforcement Learning through model mutual evaluation. It emphasizes the fierce competition between the US and China in basic models and the Open Source Ecosystem. On the product side, it analyzes how AI technology is reshaping product forms, especially the resurgence of browsers as battlegrounds for AI applications, and the importance of visualizing the AI execution process in product design. From an operational perspective, it discusses the common use of promotion strategies like invitation codes. On the capital side, it reveals the acceleration of AI company valuations with revenue growth, frequent mergers and acquisitions, and explores early investment opportunities in the Agent era related to Inference Models, Synthetic Data, tooling, protocols, and infrastructure. The podcast offers a clear, comprehensive, and multi-dimensional perspective on the current AI industry landscape and future trends.

Stripe CEO Patrick Collison interviews OpenAI co-founder Greg Brockman, revealing how OpenAI evolved from an unconventional, technology-driven approach to an AI leader. Brockman revisits the Dota 2 AI project's validation of the scaling hypothesis and shares lessons on managing uncertainty and embracing surprises. He candidly discusses the GPT-3 API launch challenges and envisions AI's future in personalized interaction, healthcare, education, and programming, predicting AI-assisted programming's transformation into 'AI colleagues' or even 'AI managers'. The interview explores AI's energy and data bottlenecks and OpenAI's product decision-making. Finally, Brockman reflects on his journey and offers a lighthearted retrospective on AGI timelines, emphasizing OpenAI's commitment to disruptive AI breakthroughs.

This podcast delves into the recent Google I/O Conference, assessing Google's latest advancements in the AI domain and its impact on the industry landscape. The guests concurred that Google successfully overturned its previous perception of lagging in the AI competition through this conference. With technological breakthroughs such as Gemini 2.5 Pro and the Veo3 Video Generation Model, as well as the strategy of deeply integrating AI into core product ecosystems like Search, Gmail, and Chrome, Google demonstrated its strong technological strength and product innovation capabilities, achieving a resurgence. The discussion analyzed the disruptive progress of the Veo3 model in video generation (especially in native audio) and its impact on content creation and post-production. At the same time, the podcast explored the impact of AI technology on traditional search models and how Google is innovating while maintaining its core advantages. The launch of Deepseek after the Spring Festival had a positive impact. The guests also compared the differences and mutual influence between China and the United States in the research and development paths of LLM technology (such as inference models), and analyzed and looked forward to the technological trends (Agent, Coding, Multi-modal) and entrepreneurial directions (hardware entry points, application in niche scenarios, service-oriented) in the AI era, emphasizing the importance of adapting to technological changes and productization capabilities. The entire podcast presents a comprehensive, in-depth, and professional discussion of Google's AI strategy, cutting-edge technology applications, and future industry development.

This episode features an in-depth interview with Zhu Mingming (Misa), founder of AR glasses company Rokid, tracing his 11-year journey in hardware entrepreneurship. The interview begins with his early experience of having his first operating system company acquired by Alibaba. He shares details about receiving investment from Alibaba during a period of extreme financial difficulty, as well as his exploration and insights while participating in YunOS and AI Lab within Alibaba. The focus then shifts to Rokid's journey, including his shift from philosophy to computer science, the company's initial attempts with AI speakers and the challenges faced (such as competition from large companies and the characteristics of not being a platform product), and the critical decision in 2019 to fully commit to the AR glasses area. Zhu Mingming elaborates on the underlying logic of AR glasses as an ideal hardware platform in the AI era, compares the product definition differences between the China-US markets for smart glasses, and depicts the future of personal smart devices after the deep integration of AI and AR. He also candidly shares insights on team adjustments, financing strategies (relying on trust from friends and mentors), strategies for competing with tech giants, and his views on the entrepreneurial environment in Hangzhou. This reveals his resilience and wisdom in navigating the challenging hardware landscape.

This episode interviews Yubo, founder of Yuque and former executive at Alibaba/ByteDance, delving into his motivations for transitioning from a large tech company executive to an independent AI entrepreneur. Yubo candidly shares his experiences working in large companies for many years, including the limitations of management positions, differences in corporate culture (Alibaba vs. ByteDance), and the reasons driving him to pursue a 'freedom dream' and ultimately choose entrepreneurship. He provides a detailed introduction to the product concept of his AI startup project, YouMind, emphasizing AI as a 'partner' for creators, committed to lowering the barrier to creation, providing the joy of co-creation, rather than merely being an efficiency tool. The interview also directly addresses the challenges in the entrepreneurial process, such as fundraising difficulties and ambiguous product definition, to which Yubo adopts a 'tree-planting' philosophy, emphasizing patience in waiting for the product to grow naturally. He believes that entrepreneurship needs to answer three core questions: 'Are you willing, are you capable, and is it worthwhile?' and shares his insights on honest expression, internet communities, and user co-creation. The entire conversation is filled with sincere personal reflections and a forward-looking perspective on AI and entrepreneurship.

This episode features a dialogue with Wang Zhongyuan, Dean of the Beijing Academy of Artificial Intelligence (BAAI), delving into the future development path of Artificial Intelligence. Dr. Wang Zhongyuan shares the trends of AI evolving from Large Language Models to Multimodal, Embodied Intelligence (Embodied AI), AI for Science, and World Models, emphasizing the critical role of Native Multimodal and World Models for AI to enter the physical world. He elaborates on BAAI's philosophy of 'Focus on long-term impact rather than personal recognition,' supporting young scientists in cutting-edge exploration and creating an innovative research environment. The discussion also covers Wang Zhongyuan's rich personal experiences, from Microsoft, Facebook to Meituan and Kuaishou, sharing growth and reflections under different corporate cultures, emphasizing the importance of fundamental skills, details, and resilience. The program explores topics such as the balance between speed and stability in technological innovation, the controversy and technical routes of World Models, and the rise of Embodied Intelligence, outlining the grand prospect of AI moving from the digital world to the physical world. Wang Zhongyuan also shares BAAI's practices and challenges in open source, talent development, and pursuing the goal of becoming a world-leading research institution, providing listeners with profound insights into AI frontiers, career development, and institutional operations.