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docs(srs): problem statement (#81)
Signed-off-by: Aaron Pham <[email protected]> --------- Signed-off-by: Aaron Pham <[email protected]>
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docs/content/Checklists/SRS-Checklist.md

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title: SRS and CA Checklist
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---
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This checklist is specific to the Smith et al template [@SmithAndLai2005; @SmithEtAl2007] for documenting requirements for scientific software, but many of the points can be abstracted and applied to other templates.
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This checklist is specific to the Smith et al template [@SmithAndLai2005] [@SmithEtAl2007] for documenting requirements for scientific software, but many of the points can be abstracted and applied to other templates.
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- Follows writing checklist (full checklist provided in a separate document)
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- [ ] LaTeX points

docs/content/DevelopmentPlan/DevelopmentPlan.md

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- design work: The team will collaborate on general design works for interfaces, lead by [Aaron Pham](https://aarnphm.xyz).
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- web-based editor: [Nebras Khan](https://github.com/nebrask).
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- ML inference server: [Waleed Malik](https://github.com/waleedmalik7)
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- ML attention intervention: Lead by [Aaron Pham](https://aarnphm.xyz), with [Lucas Li](https://github.com/lucas-lizhiwei)
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- SAE intervention: Lead by [Aaron Pham](https://aarnphm.xyz), with [Lucas Li](https://github.com/lucas-lizhiwei)
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Reviewers will be assigned automatically based on the project they champion.
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#### External Goals
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Take a step back, my goal for `tinymorph` is to imagine what machine-assisted interfaces would look like for creatives, specifically for writing[^1].
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Take a step back, our goal for `tinymorph` is to imagine what machine-assisted interfaces for creative writing would look like[^1].
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[^1]: [[ProblemStatementAndGoals/ProblemStatement#Problem|problem statement.]]
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companies that build AI systems to amplify our abilities to create and improve efficiency for our work. Companies such
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as [Runway](https://runwayml.com/), [Cohere](https://cohere.com/), etc belongs to this paradigm. ^intelligence
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My interests lie firmly on the second group, where we build tools that amplifies our agency. `tinymorph` is the
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manifestation of these beliefs.
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Our interests lie firmly on the second group, where we build tools that amplifies our agency. `tinymorph` is the manifestation of these beliefs.
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Additionally, during the journey of prototyping `tinymorph`, I hope to use it as a playground to delve into the field
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of [[glosar#mechanistic interpretability|mech interp]], as a pure research interests.
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Additionally, during the journey of prototyping `tinymorph`, we hope to use it as a playground to delve into the field of [[glosar#mechanistic interpretability]] as a pure research interests.
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#### Attendance
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What process will team members follow if they have an emergency and cannot attend a team meeting or complete their individual work promised for a team deliverable?
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Please let everyone know through Teams, email Dr.Smith about this specific incident so that the others members can
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cover the team deliverable.
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Please let everyone know through Teams, email Dr.Smith about this specific incident so that the others members can cover the team deliverable.
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#### Accountability and Teamwork
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We encouraged everyone to be open to new ideas and collaborate on features work. We should use constructive critism with regards doing review work.
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Should any conflict arise, please discuss your concern and display your reasoning with the whole team, asynchronously
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or synchronously. At the end of the day, we are all humans 😀
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Should any conflict arise, please discuss your concern and display your reasoning with the whole team, asynchronously or synchronously. At the end of the day, we are all humans 😀
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##### Stay on Track
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docs/content/ProblemStatementAndGoals/ProblemStatement.md

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author: aarnphm
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date: "2024-09-16"
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title: Problem Statement and Goals
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titleTransclude: false
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---
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See also: [[Checklists/ProbState-Checklist|checklist]] and
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users of all ages to explore and learn. More than just a portable computer, the Dynabook was envisioned as a dynamic, interactive medium for
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learning, creation, and self-expression, that could adapt to users' increasing skills and need.
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As we progress into the $21^{\text{st}}$ century, software has become comoditised, serving as the engine of transformations that transcend every corner of our life.
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Fast forward to the $21^{\text{st}}$ century, software has become comoditised and transcend every aspect in our life.
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Simultaneously, we've seen exponential growth in machine learning (ML) systems'[^1] capabilities, largely due to a general push of large language models (LLMs) into the mainstream.
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As these systems exihibit emergent properties of [[DevelopmentPlan/DevelopmentPlan#^intelligence|intelligence]], how should we craft interfaces that amplify
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users' [[glossary#agency|agency]] and encourage a sense of personalisation through interactions, rather than providing a mere tool for automation?

docs/content/References.bib

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howpublished = {\url{https://github.com/InternLM/lmdeploy}},
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year={2023}
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}
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@misc{rajamanoharan2024improvingdictionarylearninggated,
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title={Improving Dictionary Learning with Gated Sparse Autoencoders},
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author={Senthooran Rajamanoharan and Arthur Conmy and Lewis Smith and Tom Lieberum and Vikrant Varma and János Kramár and Rohin Shah and Neel Nanda},
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year={2024},
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eprint={2404.16014},
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archivePrefix={arXiv},
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primaryClass={cs.LG},
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url={https://arxiv.org/abs/2404.16014},
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}

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