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ChatGPT’s “Deep Research” feature promises to be a game-changer for anyone who loves to dive into the depths of research without spending hours sifting through endless links. Launched initially for ChatGPT Pro users at $200/month, it’s now accessible for those paying $20/month, albeit with some restrictions. But, how well does it actually work? Does it live up to the hype or fall short of expectations? In this article, we’ll look at what Deep Research can do, its strengths, its limitations, and how it compares to other AI research tools.
A Personal Research Experiment
As someone who enjoys getting lost in the rabbit hole of research, the idea of having an AI tool that could conduct real-time research for me seemed like a dream. OpenAI’s Deep Research feature promised to do just that, compiling detailed reports from various sources, saving me time and effort. I decided to put it to the test with three distinct research challenges: an espresso maker guide, beginner-friendly astronomy resources, and an exploration of the Lake George Monster legend.
Deep Research, after a somewhat slow response time (anywhere from five minutes to 30), delivered comprehensive reports. The results were thorough, well-structured, and at times, overwhelmingly detailed. However, they were also somewhat flawed – often providing product recommendations that leaned towards pricier options and occasionally offering outdated information. But the quirky enthusiasm that filled each report was endearing and made the entire experience somewhat charming.
What Undercode Says:
– The Quirky Librarian Analogy
The first takeaway from my Deep Research test is that while ChatGPT excels at gathering diverse information, it sometimes struggles with keeping things precise. Much like a brilliant but absent-minded librarian, it can pull together highly detailed reports on niche topics. But occasionally, it misses the mark by presenting unnecessary information or outdated facts. For instance, when asking for beginner astronomy resources, I received great equipment suggestions, but some event information was outdated – a flaw that might be more about the sources it pulled from than ChatGPT itself.
– A Game-Changer for DIY Research
What makes Deep Research stand out is its ability to craft organized, easy-to-digest reports based on an initial query. For example, when tasked with finding an espresso maker setup guide, I was provided not only with product recommendations but also helpful tips and common mistakes to avoid. This level of detail is perfect for someone who wants to quickly get a comprehensive view of a subject without wading through a ton of articles.
– Speed vs. Accuracy
A potential issue with Deep Research is the varying speed at which it delivers results. For tasks requiring deep dives, it can take a while (anywhere from five to thirty minutes). However, it’s worth noting that the length of time is often justified by the depth of the response. The results can be overwhelming, but for those who value thoroughness, it’s a trade-off worth considering. That said, if you’re looking for instant results, the speed might be a dealbreaker.
– Comparison with Other AI Tools
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– Limitations: AI Needs Human Supervision
While the reports generated by Deep Research are impressive, they still require human oversight. AI is, at its core, a tool that helps in gathering information, but it is not infallible. There’s still a need to verify sources, especially when information might be outdated or inaccurate. In my case, the report on the Lake George Monster legend was fun to read but lacked the clarity I would expect regarding the distinction between firsthand accounts and modern retellings. It’s essential to treat AI-generated research as a starting point, not an authoritative source.
– Is Deep Research Truly Deep?
While it may seem like Deep Research is providing deep insights, the reality is that the tool is more of a guide than a researcher. It synthesizes available information and presents it in a digestible format, but it cannot replace the hands-on effort of someone truly invested in deep research. Think of it like getting a head start on your project rather than completing the whole thing for you.
Fact Checker Results
- Accuracy and Updates: Some of the information, especially regarding events and specific details, was outdated. This could be due to the sources Deep Research pulls from, not necessarily the tool itself.
Quirky Details: In the case of niche topics like the Lake George Monster, the report was engaging but lacked a clear distinction between primary and secondary sources. This could confuse users looking for purely factual data.
Report Structure: The structure and detail in the reports were impressive. However, in some cases, the focus on thoroughness meant that less relevant information was included, which could be a bit overwhelming.
In conclusion, ChatGPT’s Deep Research feature is an excellent tool for anyone looking to streamline their research process. While it’s not without its flaws, its ability to compile structured reports based on various sources is a valuable asset for anyone diving into a complex subject. However, like all AI tools, it should be used as a starting point rather than the final authority.
References:
Reported By: https://www.techradar.com/computing/artificial-intelligence/i-tried-deep-research-on-chatgpt-and-its-like-a-super-smart-but-slightly-absent-minded-librarian-from-a-childrens-book
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