A.I. that can do “deep research” is becoming one of the top A.I. tools that the tech industry is betting on. The use cases are far and wide, but should business owners make the investment just yet?
The Five Most-Key Takeaways from This Blog Post
- Reaching insights sooner is one of the ambitions of this A.I. The overarching goal is for this A.I. to help researchers (including those in the private sector, of course) cut down on the time it takes to meet their goals.
- For business owners running an operation with heavy research-and-development initiatives, this A.I. could potentially make for a useful lab assistant of sorts. However, human research assistants can be
- A reported benefit of A.I. is that hallucination, which is normally seen as a negative of using A.I., can actually be a boon to the idea-formation stage early in a research project. For instance, the pharmaceutical industry has seen generative-A.I. hallucination offer promising drug designs.
- Information retrieval for issues like following compliance standards (and getting recommendations for how to follow such guidelines) can be useful with these A.I. models.
- Business owners that specifically research and develop or otherwise frequently use so-called “knowledge work” should consider deep-research A.I. tools.
The Significance for Business Owners
A.I. is shaping up to become an alternative to search engines, or rather like the high-powered longer-answer thing you go to when search engines are not cut out for the job.
Of course, A.I. is also transforming search engines through better understanding and multimodal search, along with generating more-creative results, such as custom-generating charts for a specific search query.
But deep research takes things a step further.
Instead of serving you up a smattering of articles to peruse, or a quick summary or carousel to scroll through, deep research can synthesize hundreds of internet resources to offer a comprehensive answer to a prompt.
Think of it as like sending off a research assistant to pore through a ton of resources to get an answer to a tough question. As you could imagine, this makes things pretty difficult, if not impossible, for a human on a deadline of, say, twenty or thirty minutes.
Adding spreadsheets and other data can be given to these platforms to guide them.
Use Case: United States National Laboratories
OpenAI partnered with the U.S. National Laboratories to help with deep research, along with other uses.
The partnership is for doing the things mentioned in the above sections: advancing and accelerating research.
Though the partnership is still quite new and the U.S. National Laboratories is likely still figuring out just how exactly to best use the A.I., it will be worth checking back in on this project down the line.
For business owners, any reports about how A.I. helped advance (or posed an obstacle to) research for U.S. National Laboratories will be worth paying attention to.
But let’s say you are looking to integrate deep-research A.I. soon, and want to know what any issues could be. The next section covers that.
Hallucination Worries
Here is where things get tricky: the problem of hallucination in A.I. is proving difficult to fully eradicate, if that is even at all possible.
Hallucination refers to A.I. that will give inaccurate results, or even simply make stuff up for the sake of answering the prompt it has been given. Think of it as like a human research assistant getting the facts wrong, or, more untrustworthily, outright lying on the report despite not actually knowing the answer to a question.
There is reason to be concerned here, as the hallucination problem persists, and even gets worse in some cases, as A.I. gets more powerful.
For this reason, things get paradoxical: if you are using A.I. to answer a question that you do not know the answer for, then how can you ensure that it is right without having to do the research yourself?
However, the benefit here could be that despite the hallucination problem, the tool itself can save time in gathering useful sources and offering fact-checkable claims.
The Last (But Not Least) Key Takeaway from This Blog Post
Overall, if you are in a research-heavy role, it can be useful to try out deep-research tools (you can get limited use of these tools for free on ChatGPT and Copilot) to see whether it actually helps you, or only replaces researching and thinking for yourself with fact-checking and second-guessing.
Other Great GO AI Blog Posts
GO AI the blog offers a combination of information about, analysis of, and editorializing on A.I. technologies of interest to business owners, with especial focus on the impact this tech will have on commerce as a whole.
On a usual week, there are multiple GO AI blog posts going out. Here are some notable recent articles:
- For Businesses and Other Organizations, What Makes a Successful Chatbot?
- IBM Watson vs. ChatGPT vs. Gemini: How Will Each Affect Search Engines?
- Using A.I. to Find Resources for Business Owners
- How Would Restricting Open-Source A.I. Affect Business Owners?
- The EU’s A.I. Act Has Become Law: The Implications for Business Owners (Especially American)
In addition to our GO AI blog, we also have a blog that offers important updates in the world of search engine optimization (SEO), with blog posts like “Google Ends Its Plan to End Third-Party Cookies”.
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