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 podcast provides an in-depth analysis of recent key advancements in Artificial Intelligence, focusing on the emerging forms of AI Operating Systems (AIOS), the significant improvements in AI Coding capabilities, and the profound impact these have on enterprise organizations and workflows. The podcast argues that AIOS is fundamentally about building a centralized entry point. This entry point uses AI to enable interoperability between different tools and applications, ultimately enhancing overall collaboration efficiency. Guests cite data from SWE Bench and other sources to demonstrate AI Coding's ability to independently complete complex tasks. This suggests that the role of future engineers will evolve from specific coding to defining and managing AI Agents. The podcast emphasizes the importance of enterprises building 'AI-ready' infrastructure, including comprehensive documentation, testable environments, and standardized interfaces, enabling AI to efficiently access and utilize company resources, thereby achieving significant improvements in efficiency. In addition, the discussion touches on consulting and product opportunities brought about by AI transformation, and strategies for small teams to cope with competition from larger companies, such as matrix-style approaches or focusing on vertical niche areas. The core focus is on how AI reshapes technical infrastructure, changes the roles of engineers, and optimizes organizational collaboration. It highlights the need for enterprises to adapt quickly to an AI-centric future of work.

This podcast features an in-depth conversation with Zhang Jinjian, Partner at Oasis Capital, exploring 'Opportunities in a World of Accelerating Market Segmentation.' The podcast begins by analyzing the world's accelerated segmentation due to information overload and attention loss from the perspective of 'Frequency and Spectrum,' emphasizing that attention is a key scarce resource. Next, it explores AI as a Multimodal AI model with unlimited potential in perception and information processing, predicting a revolution in how we perceive the world, going beyond human cognition. The program encourages individuals to embrace their unique aesthetic sensibilities in an increasingly segmented world and focus on their core strengths. By leveraging the widespread adoption of AI to create scenario-based intelligent applications and identifying untapped opportunities, individuals can ultimately realize personal value and contribute to society.

This podcast features Shaonan, the creator of Flomo Notes and Product Thinking, delving into how tech products can remain measured and pragmatic in the current AI frenzy. Shaonan shares Flomo Notes' considerations when integrating AI features, prioritizing genuine user needs and cost-effectiveness, and avoiding blindly chasing flashy technologies. The discussion points out that the homogenization of basic functions due to AI proliferation requires products to build differentiation and brand identity through deeper concepts and well-designed user experiences (Prompt Engineering - viewing prompts as integral to product design). The podcast emphasizes the importance of private knowledge, personal reflections, and user behavior data for training more personalized and practical AI models. Additionally, Shaonan shares personal and unique uses of AI for emotion management, product design 'brainstorming partner', and self-awareness analysis. Finally, the conversation returns to the essence of entrepreneurship, stressing that in the AI era, pragmatically solving old needs and using new technologies to significantly reduce costs are key to finding new opportunities, advising entrepreneurs to stay focused and set reasonable expectations.

This episode of the Silicon Valley 101 podcast features experts analyzing the accelerated advancement of AI Agents in 2025. The discussion highlights three key drivers: the enhanced coding capabilities of Large Language Models (LLMs), the breakthrough application of Reinforcement Learning Fine-Tuning (RFT), and the initial development of the MCP Protocol for AI interaction. The podcast distinguishes between traditional machine learning Agents and the new LLM-based paradigm, emphasizing the latter's intelligent advancement in environmental interaction, autonomous learning, and the thinking-execution feedback loop. Guests share experiences and evaluations of leading AI Agent products like OpenAI Operator, Deep Research, Minos, Cursor, and Winsurf, analyzing their technical principles, applications, and limitations. The podcast also delves into the challenges facing general AI Agents, including data barriers, user cognitive costs, and network effects, and proposes entrepreneurial opportunities for focused, high-value Agents in specific verticals. Finally, the discussion emphasizes the importance of evaluation mechanisms for the continuous iteration and optimization of AI Agent products.

This podcast, recorded at the Ecstasy Podcast Festival, features Liu Fei, Zhang Yan (Longtian), and Guan Yadi in an in-depth discussion on knowledge management and learning efficiency in the AI age. The guests shared their experiences using AI to improve work efficiency, knowledge management, automated meeting summaries, etc., and explored AI's potential impact on education, noting the decreasing reliance on memory and the increasing importance of integration and innovation. The discussion also addresses the limitations of AI, such as LLM hallucination, and strategies to mitigate it. Furthermore, the podcast explores how individuals can build a cognitive framework and maintain critical thinking in the AI age, reflecting on the erosion of human skills due to technological advancements and how humans should adapt. The dialogue combines technical applications, industry impact, and humanistic perspectives, providing listeners with a multi-dimensional view, emphasizing AI's value as a tool and the importance of adapting to the technological wave.

This podcast focuses on the Google I/O 2025 conference, inviting multiple experts in technology and investment to provide in-depth analysis of Google's artificial intelligence advancements. The discussion covers Gemini models, Agent Technology (especially Code Agents and Consumer Agents), and the application of AI in search and AR/VR. Guests analyze the core challenges currently facing Agent Technology, such as the capability boundaries of General Agents and the demand for enterprise intelligent workflows. The podcast also compares domestic and international models regarding long context processing and complex Agent development, and explores how AI startups can find differentiated value and survival space under the accelerated layout of giants. The overall content is professional and in-depth, combining industry trends and practical experience to provide listeners with a multi-dimensional perspective.

This podcast focuses on Taleb's 《Anti-fragility》, discussing how to cope with challenges and benefit from them through anti-fragile thinking in a rapidly changing and uncertain era. The podcast introduces Black Swan events, highlighting their unpredictability, and distinguishes anti-fragility from resilience, defining it as a system's ability to benefit from stress. Next, the podcast analyzes the fragility of online personas and how companies can navigate tariff impacts by evolving into multinational corporations. In addition, the podcast explores the reasons for the unpredictability of the future, including the hidden causes of complex systems and the characteristics of chaos theory. Finally, the podcast emphasizes the importance of applying the barbell strategy in investment and decision-making, and shares practical tips for cultivating an anti-fragile mindset in life, such as accepting uncertainty, embracing mistakes, and achieving growth and happiness through elimination.

This episode features an in-depth interview with Chen Mian, AI application entrepreneur and founder of Lovart. He reflects on his years of experience at leading mobile internet companies (Tencent, 360, Baidu, Didi, Mobike, Meituan, ByteDance), as well as his reflections on business models, product development methodologies, and career decisions. Chen Mian believes AI is a more profound revolution than the mobile internet, bringing tremendous opportunities for application entrepreneurship. He details Lovart's entrepreneurial journey in the design vertical domain, including how to choose a multimodal approach to avoid the large model main track, build differentiated capabilities, and the struggles and responses when facing challenges such as subsidy wars, product removal, and broken capital chains in the early stages. The podcast discusses the company's process from near-death to recovery through fundraising and product iteration (from professional tools to more inclusive AI agents). Chen Mian shares lessons learned in customer acquisition, cash flow management, and team building in a competitive market, and offers unique insights into the future of the intelligent agent ecosystem, the relationship between general AI and vertical AI agents, the evolution of business models, and changes in team organizational structure. He emphasizes that entrepreneurship requires a high degree of vigilance to maintain sharp decision-making. The sense of accomplishment far outweighs monetary rewards and job titles.

This episode of the podcast is hosted by Liu Fei, inviting product operation consultant Pan Nongfei to delve into how technology companies can transcend traditional product management and move towards product management that emphasizes both commercial value and user value. Leveraging her extensive experience at companies like Microsoft, Tencent, and DJI, Ms. Pan proposes the 'Product Model × Profit Model × Expansion Model' model for measuring product management structure, emphasizing that it is key to breaking through performance bottlenecks. The podcast analyzes the differences between Internet companies (such as Tencent and Alibaba) in terms of profit models and business strategies, discusses the importance of product leadership as a core strategy (using Midea and DJI as examples), and how long-term technological investment can build genuine cost advantages and competitiveness. Additionally, the program explores the characteristics of top product companies, including unique product construction, exploration, and strategic decision-making methods, as well as the practical role of corporate vision in attracting talent and driving development. The content offers tech professionals valuable insights into integrating product development with business strategy for sustainable growth.