The most effective thing you can do as a software engineer is to contribute to applied machine learning research and implementation in bio/chemoinfomatics. Solve protein folding, and entire classes of such diseases would be curable. DeepMind has given computational biology its ImageNet moment, but there is still a large amount of room to improve for production level use (beyond merely as a research tool). Truly talented ML engineers willing to work on biology are very rare.
> Is it possible that some company with deep pockets forks Firefox and hires what it's left from its development team to further develop Firefox and improve its market share?
One reason is because medical and clinical training is tied to the outdated apprenticeship system. There is no Khan academy for medicine. Train doctors at scale like software engineers and this sort of problem will naturally go away. Decouple medical school admissions from residency. Residency is not that important if your focus is on research. The unfortunate state of things in the biomedical field is that without the magical M.D. title next to your name, you are not taken seriously as an subject domain expert.
It's called a FPGA; a software defined microprocessor (most higher tier processors can be reprogram to a certain extent through microcode, but a FPGA is a specialised chip designed specifically for this). You can get ridiculously high performance for your specific application, but it will never excel at general purpose computing. Good enough for Forth, great for ML, DSP, and number crunching, bad for running random apps from GitHub.
Would you prefer CS algorithms in papers to be written in English prose rather than pseudo code? Would you notice if your neural network diagram has its arrows reversed? I do not understand HN's superiority complex when it comes to notation. Every thread on music in this forum devolves to complaints about music notation rather than the essence of the art itself. It is disappointing.
First party UI toolkit implies no bias. You are the one being biased by suggesting that open source/Linux-originated UI kits are somehow superior. The inability of the open source operating system ecosystem to deliver a coherent GUI is no fault of Microsoft or Apple. Ubuntu is going with Flutter, Google's answer to the GUI problem. The Linux foundation is to blame for the kernel not prioritising standardized systemland support for a consistent GUI. In commercial operating systems, the UI server/shell is not an after thought.
The hardest part of CUDA is getting it installed and recognised by the linker without bricking the machine or throwing strange version conflict errors. Many machine learning engineers can attest to this.
That is not a fair take. Windows has multiple first party UI toolkits, Win32 simply being one of the oldest and most well known. The Windows ecosystem places a greater emphasis on binary and dependency level backwards compatibility compared to Unix style systems.