J0-nas

Are you concerned about the state of AMD GPUs?

They couldn't compete in terms of high end performance for a long time. But nowadays they even lose the price-performance ratio of entry->mid level GPUs.

No idea.

I can only speak for myself. But in now 7 years I never connected a keyboard or mouse to my 2011 MBA. It's keyboard+Touchpad is just so good that I don't need it. Even when I connect to an external display.

I'd say no. In my experience other Companies aren't even able to recreate the smooth surface + 'clicking feel' of the Apple touchpad, which is what I value the most. I suspect that they can, but aren't legally allowed due to patterns.

I wouldn't care about the touch bar if the esc+(sleep key) were still regular hardware keys. Those are the only ones that I actually use.

But an even bigger problem for me is the price increase. The base TB version costs 200€ more (or 400€ if you'd buy the nTB 128gb version). With ne nTB version not getting the update, the updated MBP is too expensive compared to non Apple machienes.

How advanced are those student in their studies when they take this course?

Their work is probably good but I can't help but think many of the reports/posters seem underwhelming. I doubt they would be accepted at the universities I know.

I also tried it, and it didn't work for me. I asked about the error message in the swift forum and got no response...

Using the prebuilt binary for ubuntu with the WSL is WAY more userfriendly.

Another problem problem is proper tooling. So far my experience with the LSP implementation is a bit dissapointing..

I agree, I just had in mind that Apple just now added/announced support for external GPUs. Besides Image+Video edditing, I though general computing tasks is a use case they had in mind. It's not like Gaming is big on MacOS.

I like both Swift and Tensorflow. But how is that going to work?

As far as I understand MacOS has no official Nvidia support (=> no Cuda), which is (at least) advised if you want to use a GPU for computing. Using OpenCL instead of CUDA would require building Tenfowlow from source. The OpenCL support is not as mature as with CUDA, so I imagine you could run into unexpected (performance) problems.

On windows, you have an excelent CUDA but lackluster Swift support.

Will they add OpenCL as a "first class backend" for Tensorflow or rather expect a "first class" support of Swift on Linux and Windows? Otherwise who is going to use it?

I don't think the last sentence is fair to trensorflow. Torch has been around for ~15 years compared to the 3 of TF. You'd expect TF to catch up in terms of performance in the future.

> A forward() function gets called when the Graph is run.

Isn't that almost exactly the same in tensorflow? You'd run your model to generate an output, or/and run your optimization operation t optimize the model.

> Based on some reviews, PyTorch also shows a better performance on a lot of models compared to TensorFlow.

Citation needed. How good are the examples optimized? What does performance mean? Precision or learning iterations per second?

If it's the later, in which environment? CPU/GPU/distributed computing?

To be fair, while they are "richer than god" most of their money is either in some non-us bank to avoid taxes or invested...

Thank you

Thanks

I read this and it doesn't answer my questions

Totally of topic but could someone explain Elixirs syntax to me?

In the following code (from the linked site): What is embeds_many? Are :string and :map type information or Atoms? What happens to :changes, Change, primary_key? Does the code between do and end just call the field function twice?

embeds_many :changes, Change, primary_key: false do

    field :field, :string

    field :value, :map

end