Portfolio of approaches¶
Supplemental reference · Browse supplements · Current report
Candidates for investigation, not selected investments. Combine approaches when useful; compare their support and recurring obligations as carefully as their technical benefits.
| Approach | Opportunity | First useful test | Main dependency |
|---|---|---|---|
| Improve use of campus resources | Reduce duplicate purchases and onboarding friction | Map one research and one teaching workflow to documented campus routes | Eligibility, headroom, support and class-use terms |
| Shared RSE and technical support | Pool scarce expertise and reusable environments | Estimate a few tasks and trial a bounded support window | Named staff, existing commitments and funding; no new appointment assumed |
| Shared data and software stewardship | Reuse datasets, metadata and environments safely | Review a dataset/license and test a portable workflow | Rights, permissions, accessibility and renewal ownership |
| Allocation-backed compute service | Support larger CPU/GPU work without relying only on free tiers | Benchmark components and validate a target route | An award, operations capacity and provider terms; ACCESS pilot remains conditional |
| Efficient models and workflows | Lower unnecessary compute and improve reproducibility | Compare a smaller model, retrieval approach or checkpointed job against a quality baseline | Task-specific evaluation; savings must be measured |
| Partnerships and shared infrastructure | Connect compatible college, campus and external efforts | Define a small joint use case with an interested partner | Agreed responsibilities, access and sustainable support |
| Reusable teaching and evaluation tools | Avoid rebuilding assignment environments and grading workflows | Test exports and a synthetic class before adoption | Maintainer continuity, account terms and separate compute quotas |
Planned ORAI proposal¶
Greg will draft a bounded AI Innovation Pilot next, showcasing ORAI tools alongside his infrastructure components in an AI-native classroom. A separate proposal will be drafted next. His capacity is four hours/week total. The program offers a potential eight-week proof-of-concept route after assessment; acceptance, RSE assignments and infrastructure must be confirmed. Ongoing maintenance and classroom operations need their own plan.
Use one comparison standard¶
For each candidate, document instructional/research benefit, users served, accessibility, data suitability, required effort, recurring costs, funding status, ownership and a reversible test. Do not rank options using invented cost savings or unmeasured capacity.
Draft recommendations · Resource inventory · Supporting compute pilot
Drafting support¶
The resource tool prepares a local brief and sourced request template. Optional Luna drafting needs explicit consent for public/synthetic material. Technical assessment, limits and model trials are supplementary.