Julia looks like it is pointed towards ML programming and is fast, but I don't see the same level of potential in a few years that Rust and Swift seem to have.
Rust seems to generating a lot more buzz and I've been seeing posts about Swifts ML libraries that look interesting. My crystal ball seems to be saying that Rust will follow a similar arc that Python took and gain some serious ML creds through libraries built by community/industry. I think Swift will also gain some credible ML capabilities too because it has the Apple behemoth behind it.
One of the things that I'm struggling with on Python is the very poor support for AMD GPU's, which are in Macs. I'm sure Swift will do a better job of using the hardware capabilities better.
Thanks, this makes some sense. I've started a few tutorials for Swift, and I added the Rust plugin/module to Visual Studio Code, but neither felt intuitive to me.
Python actually isn't my first language, just my current choice. I've programmed in Basic, Pascal, Fortran, PL-SQL, Prolog and C at various times in the past. My question was more about which is likely to scale over time to be the more popular ML language.
Python also sucks for MacOS gui apps, so I was contemplating building MacOS/iOs apps for myself as a side quest.
I think ML is probably going to require a lot of people in the future and I'm looking to build a digital nomad skill set for the future that pays well. While I've done a postgrad subject on ML and have a STEM degree, but I'm inclined to use existing libraries as that's just easier.
The seven habits of highly effective people. Sounds like a get rich quick book but it’s actually a very profound book about what it means to be authentic to yourself and in your interactions with others. This book completely changed my life.
Thinking fast and slow. This book will give you insights into your own mind that are science based and actually explain so much of what we observe in the behaviour of ourselves and others.
From: Verma, S., Dhanak, M., & Frankenfield, J. (2020). Visualizing the effectiveness of face masks in obstructing respiratory jets. Physics of Fluids, 32(6), 061708. https://doi.org/10.1063/5.0016018
TABLE I.
A summary of the different types of masks tested, the materials they are made of, and their effectiveness in impeding droplet-dispersal. The last column indicates the distance traveled by the jet beyond which its forward progression stops. The average distances have been computed over multiple runs, and the symbol “∼” is used to indicate the presence of high variability in the first two scenarios listed.
Mask type Material Threads/in. Average jet distance
Uncovered … … ∼8 ft
Bandana Elastic T-shirt material 85 ∼3 ft 7 in.
Folded handkerchief Cotton 55 1 ft 3 in.
Stitched mask Quilting cotton 70 2.5 in.
Commercial maska Unknown Randomly assorted fibres 8 in.
Bluetreefrog @ Bluetreefrog @lemmy.world Posts 58Comments 372Joined 2 yr. ago
Julia looks like it is pointed towards ML programming and is fast, but I don't see the same level of potential in a few years that Rust and Swift seem to have.
Rust seems to generating a lot more buzz and I've been seeing posts about Swifts ML libraries that look interesting. My crystal ball seems to be saying that Rust will follow a similar arc that Python took and gain some serious ML creds through libraries built by community/industry. I think Swift will also gain some credible ML capabilities too because it has the Apple behemoth behind it.