{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Crazy Wisdom","title":"Episode #403: Unlocking AI’s Brain: Knowledge Graphs, LLMs, and the Future of Reasoning","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/9ef65d12\"></iframe>","width":"100%","height":180,"duration":2442,"description":"In this episode of the Crazy Wisdom Podcast, host Stewart Alsop welcomes Chia Yang, co-founder of whyhow.ai, a company specializing in data infrastructure and AI-powered knowledge graphs. They discuss the pivotal role of knowledge graphs in AI, particularly in enhancing structured search and reasoning, contrasting them with more stochastic systems like large language models (LLMs). Chia explains how knowledge graphs allow for more structured, reliable connections between data, and how this impacts the development of production-grade AI systems. He also touches on the limitations of LLMs, the significance of neurosymbolic approaches, and the future of AI reasoning. For further resources, Chia encourages listeners to visit whyhow.ai, check out their Medium articles, and join the discussion on their Discord channel.Check out this GPT we trained on the conversation!Timestamps00:00 Introduction to the Crazy Wisdom Podcast00:26 Understanding Knowledge Graphs02:32 The Role of Knowledge Graphs in AI05:08 Challenges and Limitations of LLMs09:51 Production Grade Systems and SOPs13:17 Competency Crisis and Real-World Problems18:11 The Future of Human and Machine Collaboration21:03 Exploring Social Inequality and Learning Challenges21:57 The Importance and Complexity of Data22:44 Understanding Knowledge Graphs and LLMs24:29 Building Practical Systems with LLMs25:42 The Evolution of Knowledge Graphs29:12 Technical Aspects of the Platform31:52 Philosophical Insights on Language and AI36:48 Future Milestones and Beta Program38:24 Final Thoughts on Knowledge GraphsKey InsightsThe Power of Knowledge Graphs: Knowledge graphs are central to creating structured representations of data, enabling more reliable and hierarchical relationships between information. They play a crucial role in enhancing AI systems' ability to retrieve relevant information and reason through complex problems, contrasting with the more flexible but less deterministic nature of LLMs.Limitations of Large...","thumbnail_url":"https://img.transistorcdn.com/UZbrDrlO5VTfDNcq188THwbv0T09vcmLyzx3BcPI9bs/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS81Y2Rj/OGFiMTYyMGFkNTM5/N2NjOWI2MWM5YzQ1/YTc2Ny5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}