What I've Learned Testing 100+ AI Tools For Research

In this video, I talk about how to effectively use AI tools for research and share what I’ve learned from using hundreds of them.

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While there are many specialized AI tools for researchers, I’ve found that general large language models, like ChatGPT, can handle most tasks if you know how to use them properly. The key is in how you prompt these models, and in this video, I go over the important elements of crafting the perfect prompt.

I discuss the role of AI tools in streamlining different stages of research, from literature reviews to writing and editing. Many of these tools, like SciSpace or Consensus, are great for specific tasks, but there isn’t a single one that can do it all. You need to build an AI toolkit with the best AI tools for your needs, combining different ones to cover the various steps in your research workflow.

One of the biggest takeaways from this video is that no matter how advanced AI for research becomes, it’s always a collaborative process. You need to guide the AI by providing clear context, specifying what you want, and giving it feedback so that it can improve its responses. I also mention that AI tools are constantly changing, so you have to stay flexible and ready to switch to a different tool if the one you’re using no longer meets your needs.

Finally, I address some of the misconceptions people have about using AI tools in research. For instance, some believe that using AI is “cheating” or that it’s too complicated to integrate into their workflow. However, I explain how publishers are relaxing rules around AI use, and how even major companies like Google allow AI-generated content. Ultimately, the goal is to find the best AI tools that work for you, without feeling overwhelmed by the ever-growing number of options.

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▼ ▽ TIMESTAMPS
00:00 Intro
02:28 Topsy Turvy World of AI Tools
04:06 Collaborative efforts between you and AI
05:03 The usual changes in AI
06:19 AI Rules and Regulations
07:35 AI Fatigue

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