Website / doc improvements to improve user experience

- [x] Update Features and Ecosystems - Remove some of the older ones
- [x] Update all the GPU links
- [x] Separate section: Showcase community projects that have the common models - GeometricFlux, Flux3D, MetalHead, ObjectDetector.jl, Transformers.jl, SciML (DiffEqFlux), TextAnalysis
- [x] Separate section: Showcase some more research-y things that are end applications - Yao, RayTracer, ...
- [ ] Deployment - with PackageCompiler. We know this won't work - but figure out where it breaks and file relevant issues.
- [x] Blog: Can we link to other blogs that are not written by us? Aggregation example: [JuliaGPU](https://github.com/JuliaGPU/juliagpu.org/edit/master/content/post/2020-01-05-itensors.md).
- [ ] Have a table of all available models. Could be model zoo (where you cut and paste) or complete models that you can import (MetalHead). Should this be a table, where models are listed as rows, and then level of availability is checkboxes in columns?
- [ ] Observe some first time users, see where they fall, and make sure we have a quickstart or an FAQ to address common issues
- [x] Update partners. Add CMU, maybe others.
- [ ] Performance comparisons with PyTorch and TensorFlow. This should be front and center, and we should not be shy about admitting where work needs to be done. This will help address the perception that Flux is slow.
- [ ] How can people contribute - improvements, new models, new models with weights. Document that.
- [ ] Docs probably need to be organized for end users and for model builders. Model builders may need to have more information on GPU dev. Common gotchas (like scalar indexing), etc.
- [x] Link all the users of Flux packages: https://juliahub.com/ui/Packages/Flux/QdkVy/0.10.4?t=2 There's the laundry list, but perhaps some can also be classified into domains.
- [ ] What should users install? Torch.jl is optional - so publish blog and mention in docs, etc.
- [ ] Papers
- [ ] Add JuliaAcademy link