The blog post "The Differences Between Deep Research, Deep Research, and Deep Research" explores three distinct interpretations of "deep research." The first, "deep research" as breadth, involves exploring a wide range of related topics to build a comprehensive understanding. The second, "deep research" as depth, focuses on intensely investigating a single, narrow area to become a leading expert. Finally, "deep research" as time emphasizes sustained, long-term investigation, allowing for profound insights and breakthroughs to emerge over an extended period. The author argues that all three approaches have value and the ideal "depth" depends on the specific research goals and context.
Holden Karnofsky examines the question of whether advanced AI will pose an existential threat. He argues that while it's difficult to be certain, the evidence suggests a substantial likelihood of catastrophe. This risk stems from the potential for AI systems to dramatically outperform humans in many domains, combined with misaligned goals or values, leading to unintended and harmful consequences. Karnofsky highlights the rapid pace of AI development, the difficulty of aligning complex systems, and the historical precedent of powerful technologies causing unforeseen disruptions as key factors contributing to the risk. He emphasizes the need for serious consideration and proactive mitigation efforts, arguing that the potential consequences are too significant to ignore.
Hacker News users generally praised the article for its thoroughness and nuanced approach to causal inference. Several commenters highlighted the importance of considering confounding variables and the limitations of observational studies, echoing points made in the article. One compelling comment suggested the piece would be particularly valuable for those working in fields where causal claims are frequently made without sufficient evidence, such as nutrition and social sciences. Another insightful comment discussed the practical challenges of applying Hill's criteria for causality, noting that even with strong evidence, definitively proving causation can be difficult. Some users pointed out the article's length, while others appreciated the depth and detailed examples. A few commenters also shared related resources and tools for causal inference.
Summary of Comments ( 24 )
https://news.ycombinator.com/item?id=43236184
Hacker News users generally agreed with the author's distinctions between different types of "deep research." Several praised the clarity and conciseness of the piece, finding it a helpful framework for thinking about research depth. Some commenters added their own nuances, like the importance of "adjacent possible" research and the role of luck/serendipity in breakthroughs. Others pointed out the potential downsides of extremely deep research, such as getting lost in the weeds or becoming too specialized. The cyclical nature of research, where deep dives are followed by periods of broadening, was also highlighted. A few commenters mentioned the article's relevance to their own fields, from software engineering to investing.
The Hacker News post titled "The Differences Between Deep Research, Deep Research, and Deep Research" (linking to an article on deep research) has generated a moderate number of comments, exploring various facets of the topic.
Several commenters discuss the differing interpretations of "deep research" depending on the context. One points out the distinction between academic research, industrial research, and personal exploration, highlighting how the goals, methodologies, and expected outcomes vary significantly. They elaborate on the pressures and constraints within each setting, such as the publish-or-perish dynamic in academia versus the market-driven focus in industry.
Another commenter picks up on the author's mention of "exploratory research" and contrasts it with "exploitative research." They argue that genuine deep research often involves a blend of both, where initial exploration paves the way for focused exploitation of promising avenues. This commenter further suggests that the most impactful research often arises from a willingness to embrace uncertainty and delve into uncharted territory, rather than simply optimizing existing knowledge.
A few comments focus on the practical challenges of conducting deep research, particularly within a corporate environment. They discuss the difficulty of securing funding and resources for long-term, open-ended projects, especially when faced with pressure to deliver short-term results. One commenter shares personal anecdotes about navigating these challenges, emphasizing the importance of effectively communicating the value of deep research to stakeholders and demonstrating its potential impact, even if it's not immediately apparent.
The concept of "depth" itself is also debated. Some commenters argue that true depth isn't solely about the duration of a research project, but also about the level of intellectual rigor, the thoroughness of the investigation, and the novelty of the insights generated. They caution against equating long hours with deep work and emphasize the importance of focused effort and critical thinking.
Finally, a few commenters offer practical advice for aspiring researchers, such as the importance of building a strong foundation of knowledge, developing effective research habits, and cultivating a mindset of curiosity and perseverance. They also recommend seeking mentorship and collaborating with others to broaden perspectives and accelerate learning. One commenter suggests maintaining a research journal to document progress, reflect on learnings, and generate new ideas.