Difference between revisions of "Evaluation of JAX in AI/ML software engineering"
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|Summary=Analysis of the benefits of JAX (and/or similar solutions) in terms of performance, development time, module reusability, etc. | |Summary=Analysis of the benefits of JAX (and/or similar solutions) in terms of performance, development time, module reusability, etc. | ||
| − | |TimeFrame=Fall | + | |TimeFrame=Fall 2023 |
|Supervisor=Veronica Gaspes, Slawomir Nowaczyk | |Supervisor=Veronica Gaspes, Slawomir Nowaczyk | ||
|Level=Master | |Level=Master | ||
Latest revision as of 08:09, 30 August 2023
| Title | Evaluation of JAX in AI/ML software engineering |
|---|---|
| Summary | Analysis of the benefits of JAX (and/or similar solutions) in terms of performance, development time, module reusability, etc. |
| Keywords | |
| TimeFrame | Fall 2023 |
| References | |
| Prerequisites | |
| Author | |
| Supervisor | Veronica Gaspes, Slawomir Nowaczyk |
| Level | Master |
| Status | Open |
Many new tools are being created with the goal of making it easier to build AI/ML solutions. One such tool is JAX:
https://jax.readthedocs.io/en/latest/
This thesis is about the evaluation of JAX, taking multiple different perspectives into account. One aspect is of course performance, but there are also "bigger" software engineering questions: can it be used to express things in a more familiar (mathematical) way than e.g. TensorFlow? And thus allow for shorter development time, more reusable modules, the possibility of exploring different methods for the same problem, etc.?
Please note: this topic is just an early idea, not fully developed. If you are interested in it, contact Veronica & Slawomir before the deadline to discuss how to make it more concrete.
