How To Use AI to Give You More Time for Creative Work
Perhaps the most frustrating part of writing my dissertation was searching for papers. Writing the literature review itself wasn’t an issue; finding relevant papers was. Don’t get me wrong: an online literature search is way easier than hunting through piles of magazines in long-forgotten library stacks while beating off hungry Morlocks (okay, that’s a bit of an exaggeration. There was only one Morlock and it had just eaten).
Although searching through online databases is definitely easier on the feet and stirs up less dust, it still leaves a lot to be desired. Although finding material is easy, finding relevant material is not—having all the world’s knowledge at your fingertips means having to wade through what feels like a good chunk of it to find what you need.
It’s the wading part that is exhausting and which overwhelms the excitement of discovery. Reading research papers can be fun, but not when you’re pressed for time and trying to finish writing a paper or a dissertation. The online search tools claimed to be able to find papers similar to ones I’d already found, but the reality was otherwise. Again, better than wandering around in dimly lit library basements, but still frustrating.
How Can AI Help?
Although an AI can simulate certain human behaviors, there’s nothing intelligent inside there. The lights are on and nobody’s home. However, AI is good at translating natural language into something a computer can understand and then translating the results back to something useful to us. It’s doing what computers do best: helping with a task that is time-consuming, exhausting, and frustrating. It’s reducing the load on human time and effort the same way that statistics software takes up the computational load of performing complex statistical operations. You still have to understand what you’re doing, but the computer does the annoying part.
The trick to taking advantage of AI is to recognize that, as OpenAI founder Sam Altman recently commented, “Infrastructure is destiny” (Washington Post, “Who Will Control the Future of AI”). This is as true about software infrastructure as it is about hardware infrastructure.
Without a robust software infrastructure to support it, using an AI is sort of like driving an antique car. It looks really cool and it’ll usually get you where you want to go, but it’s not very comfortable, it’s not entirely reliable, and it lacks power steering, power brakes, AC, and other modern features we’ve come to expect in cars. They were certainly great in their day and beat the horse and buggy, but it’s hard to imagine taking a long trip in one today.
AI is in a similar position. It’s cool and it’s powerful, but it lacks the needed features to make it really useful for everyone. That’s where AI infrastructure software comes in.
Infrastructure is Destiny
AI infrastructure software provides the foundation for taking full advantage of AI. Just as power steering, sensors, and AC make driving modern cars easier, safer, and more comfortable, AI infrastructure software makes AI easier to use and more reliable. The quality of your infrastructure determines the long-term success of your AI projects.
Infrastructure is what turns an AI LLM into a helpful assistant, manages the prompts, and constrains the search space so you don’t get nonsense or hallucinations. AI infrastructure software makes it easy to say, “Give me more papers like this one” and actually get useful results.
To be effective, AI infrastructure software provides several key features:
- Universal connectivity
- AI flexibility
- Advanced metasearch capabilities
- Enhanced prompt engineering
- Ease of use
Universal Connectivity
A major challenge with using AI is the time, cost, and security risks involved in copying data into specialized databases or into vendor clouds. Having multiple copies of data opens up a Pandora’s Box of issues, particularly around keeping data synchronized and identifying your single source of truth. With universal connectivity, AI infrastructure software lets you leave data in existing databases and brings the AI to the data. Data movement is sharply reduced, you aren’t dealing with multiple copies of data, and security risks are minimized. And even if security isn’t a big issue, adding new, specialized databases is expensive and the costs of maintaining them quickly add up. Infrastructure software lets you avoid that.
AI Flexibility
AI flexibility gives you control over which AI models you use. If you need a specialized model to work with scientific papers in a particular domain, you can use that model. You can combine multiple models from different vendors to produce more personalized or useful results. AI infrastructure software puts you in control.
Advanced Metasearch Capabilities
Let’s face it, this is what a researcher needs. Advanced metasearch combined with universal connectivity lets you search all available databases, your own email, Slack, WebEx, local storage, and more. You easily find the papers you need, as well as relevant notes, emails, and conversations. With AI identifying relevancy and context, you have a powerful data management system that makes everything easier. management system that makes everything easier. This is the search capability I wish I’d had access to.
Enhanced Prompt Engineering
Writing a simple AI prompt is easy. Writing a more complex one is hard. Writing a complex prompt that incorporates Retrieval Augmented Generation or other techniques to eliminate hallucinations and inaccurate responses is where the infrastructure software comes in. It preprocesses the prompt before passing it to the AI. Like the lane-finding features of a modern car, it keeps you from veering off into the weeds.
Ease of Use
AI infrastructure software needs to be easy to use and make AI easier to use. That is, after all, the whole point of it. Infrastructure software facilitates using and scaling AI projects so that we derive maximum benefit from them.
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The point of AI isn’t to do our creative work for us—rather, it’s to do the drudge work, those boring, time-consuming, but necessary tasks that must be completed before the real work can begin. I would never let an AI write my literature reviews, but I wish I’d had an AI to suggest actually relevant research for me to consider. AI infrastructure software makes that possible.
Sure, I’ll still have to read through a lot of papers, but now the papers I’m spending my time on are significantly more relevant to the project at hand. Because AI is tireless, it also finds me papers I’d never have found on my own. And, of course, the AI can be told to rank papers from better quality journals more highly, so the overall quality of the research improves.
By reducing the time spent on wading through irrelevant information, AI allows us to focus our energies on what matters, and that gives us more space for creativity and insight. Rather than drowning in drudgery, AI lets us spend more of our time experiencing the awe and excitement of research. The sooner we use AI infrastructure software to harness the power of AI, the sooner we get to eliminate the boring, frustrating work and focus on what really matters.
To find out how you can be a leader in applying AI infrastructure to increasing creativity and improving research, contact SWIRL today.