This section provides a brief overview of popular tools. The tools are described for information purposes only and are not an endorsement. Please consult with your instructor, supervisor, and journal publication for their generative AI usage policies. Approach usability and application with caution and discretion. The generative AI landscape is continuously evolving, and while we have included some current popular tools, this guide is subject to change since numerous new and open-source models are being developed.
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Campus Note: The University of Illinois Urbana-Champaign's Technology Services department provides a list of approved resources on their Generative AI Resources page. Any application not on their list is not approved and should not be used with University solutions or devices.
There are an ever-growing number of AI tools, and keeping up with the state-of-the-art can be dizzying! While front-runners in closed-source, paid platforms are starting to become somewhat established among large tech players (Microsoft, Google, Facebook, Adobe, etc), the open-source movement in generative AI is fertile and varied! We present a few options of both in the below sections. Please note that running these open-source models locally often requires significant computer hardware, but you can also experiment with these tools via various cloud computing platforms
As generative AI becomes more prevalent in our lives, it is important to understand the benefits as well as the limitations of these tools. There are a myriad of ways in which generative AI tools can support and enhance the research process and can provide:
This LibGuide provides a brief overview of popular tools. The tools are described for information purposes only and are not an endorsement. Please consult with your instructor, supervisor, and journal publication for their generative AI usage policies. Approach usability and application with caution and discretion.
Last Updated: November 2024