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2 changes: 1 addition & 1 deletion config.toml
Original file line number Diff line number Diff line change
Expand Up @@ -69,7 +69,7 @@ ignoreErrors = ["error-remote-getjson", "error-remote-getcsv"]
# eventsUrl = "https://s3.amazonaws.com/uvarc-resources/website/events.csv"

[params.support]
enableForms = true
enableForms = false

[params.metrics]
coreHours = "22,753,716.4"
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1 change: 1 addition & 0 deletions content/post/2026-may-maintenance.md
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Expand Up @@ -123,6 +123,7 @@ The modules to be removed during this maintenance are listed below.
|openmm |7.5.0 |-|
|peer |1.3 |-|
|R |4.3.1 |4.4.1+ |
|rapidsai |25.06 |26.02 |
|rmats-turbo |4.1.1 |-|
|skopeo |1.13.1 |-|
|snakemake |9.8.1 |9.16.3 |
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9 changes: 9 additions & 0 deletions content/userinfo/faq/rivanna-faq.md
Original file line number Diff line number Diff line change
Expand Up @@ -102,6 +102,15 @@ if [ -f /etc/bashrc ]; then
PS1="\s-\v\$"
alias vi='vim'
```
## Can I install GenAI tools on Rivanna or Afton to help with coding?
Use of AI tools on RC resources must comply with the University's policies governing [acceptable use of information technology resources](https://uvapolicy.virginia.edu/policy/irm-002). This includes restrictions on downloading or using prohibited applications (e.g., DeepSeek AI, TikTok, WeChat, CapCut).

Users should follow the University's GenAI Use Guidelines and are encourage to use appropriately contracted and licensed GenAI tools (i.e, M365 Copilot) with [Sensitive](https://security.virginia.edu/definitions/sensitive-data) or [Internal Use](https://uvapolicy.virginia.edu/policy/IRM-003) research data. Data classified as "Public" may be used with other GenAI tools.

## Does this prevent training or fine-tuning AI models for research?
No. Standard research workflows including training, fine-tuning, or evaluating machine learning or generative models as part of research projects are permitted on RC resources.

Please note that models trained or fine-tuned on sensitive or highly sensitive data may allow aspects of that data to be extracted. Therefore, model weights of any model trained or fine-tuned using research data should be protected in accordance with the applicable [data protection standard](https://security.virginia.edu/data-protection).

- - -

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