Cyc, the ambitious AI project started in 1984, aimed to codify common sense knowledge into a massive symbolic knowledge base, enabling truly intelligent machines. Despite decades of effort and millions of dollars invested, Cyc ultimately fell short of its grand vision. While it achieved some success in niche applications like semantic search and natural language understanding, its reliance on manual knowledge entry proved too costly and slow to scale to the vastness of human knowledge. Cyc's legacy is complex: a testament to both the immense difficulty of replicating human common sense reasoning and the valuable lessons learned about knowledge representation and the limitations of purely symbolic AI approaches.
The demise of the Cyc project, a monumental, decades-long endeavor to construct a comprehensive common-sense knowledge base and reasoning engine, is lamented in this elegiac post. The author meticulously details the project's ambitious goals, tracing its origins back to the 1980s and the vision of Douglas Lenat, who believed that imbuing machines with human-like common sense was the crucial missing piece in achieving true artificial intelligence. Cyc aimed to encode the vast tapestry of everyday knowledge, the unspoken assumptions and inferences that humans effortlessly make, into a formalized, symbolic representation. This involved painstakingly hand-crafting a massive ontology of concepts, relationships, and rules, a Herculean task that required the dedication of a specialized team for over three decades.
The post explores the philosophical underpinnings of Cyc, highlighting the inherent complexities of representing common sense, a domain characterized by vagueness, context-dependence, and exceptions to rules. It delves into the technical intricacies of CycL, the project's unique logic-based representation language, and the challenges encountered in scaling the knowledge base while maintaining consistency and accuracy. The sheer scope of the project, encompassing millions of assertions about the world, presented significant hurdles in terms of knowledge acquisition, validation, and maintenance.
Despite its noble aspirations and unwavering dedication, Cyc ultimately fell short of its initial grand vision. The post attributes this to a confluence of factors, including the limitations of symbolic AI approaches in capturing the fluidity and nuances of human cognition, the immense difficulty of formalizing common sense knowledge, and the underestimation of the sheer magnitude of the undertaking. The author suggests that the rise of data-driven, statistical AI paradigms, with their emphasis on learning from vast datasets, further overshadowed Cyc's symbolic approach.
While acknowledging Cyc's shortcomings, the post also recognizes its significant contributions to the field of artificial intelligence. It served as a valuable exploration of the intricacies of knowledge representation and reasoning, pushing the boundaries of what was considered possible. The vast knowledge base accumulated over decades, though imperfect, represents a remarkable achievement and a testament to the project's ambition and perseverance. Furthermore, Cyc's legacy lives on in the form of OpenCyc, a freely available version of the knowledge base, and in the lessons learned about the challenges and complexities of building truly intelligent machines. The post concludes with a melancholic reflection on the project's unfulfilled potential, a reminder of the enduring quest to unlock the secrets of human intelligence and imbue machines with the capacity for common sense.
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https://news.ycombinator.com/item?id=43625474
Hacker News users discuss the apparent demise of Cyc, a long-running project aiming to build a comprehensive common sense knowledge base. Several commenters express skepticism about Cyc's approach, arguing that its symbolic, hand-coded knowledge representation was fundamentally flawed and couldn't scale to the complexity of real-world knowledge. Some recall past interactions with Cyc, highlighting its limitations and the difficulty of integrating it with other systems. Others lament the lost potential, acknowledging the ambitious nature of the project and the valuable lessons learned, even in its apparent failure. A few offer alternative approaches to achieving common sense AI, including focusing on embodied cognition and leveraging large language models, suggesting that Cyc's symbolic approach was ultimately too brittle. The overall sentiment is one of informed pessimism, acknowledging the challenges inherent in creating true AI.
The Hacker News post titled "Obituary for Cyc" sparked a lively discussion with a variety of perspectives on the project's history, ambitions, and ultimate fate. Several commenters offered firsthand accounts or insights gleaned from their proximity to Cyc.
One compelling thread explored the tension between Cyc's pursuit of common sense reasoning and the emergent capabilities of large language models (LLMs). Some argued that LLMs, despite their statistical nature, effectively demonstrate a form of "emergent" common sense, questioning the need for Cyc's meticulously handcrafted knowledge base. Others countered that LLMs lack true understanding and are prone to errors, highlighting Cyc's potential to provide a more robust and reliable foundation for AI. This discussion touched upon the philosophical differences between symbolic AI, as exemplified by Cyc, and the connectionist approach of LLMs.
Another key theme revolved around Cyc's practical applications and its perceived lack of widespread impact. Several commenters questioned the commercial viability of Cyc and speculated on the reasons behind its relative obscurity. Some attributed this to the project's ambitious scope and the inherent difficulty of encoding common sense. Others pointed to management decisions or the challenges of integrating Cyc's technology into existing systems.
Several commenters shared anecdotes about their interactions with Cyc and its creators, offering glimpses into the project's culture and internal workings. These personal accounts provided a more nuanced picture of the challenges and triumphs faced by the Cyc team.
Some comments delved into the technical details of Cyc's architecture and knowledge representation, highlighting its unique approach to symbolic AI. These discussions offered insights into the complexities of building a system capable of representing and reasoning about common sense knowledge.
A few commenters expressed a degree of cautious optimism about Cyc's future, suggesting that its vast knowledge base could still hold value in specific applications or as a complement to other AI approaches. However, the overall sentiment seemed to be one of respectful acknowledgment of Cyc's historical significance, tinged with a sense of disappointment at its unfulfilled potential. The discussion reflected a broader debate within the AI community about the best path toward achieving artificial general intelligence.