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Joined 2 years ago
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Cake day: July 18th, 2023

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  • Based on what you wrote, it seems like you need to take a step back and look at the whole picture. Why are you at school and what do you want to study.

    Goin to school can help you position yourself for a career, but is usually primarily about becoming educated (and isn’t for everyone).

    If you’re primarily concerned about a career, then focus you’re studies on something you feel capable in. Physics requires a lot of mathematics (and nowadays usually some programming). Programming coursework may have mathematics, but usually relies more on logic than math. Writing is a great way to work on communication skills and analysis, but will have a less direct career path after school (becoming a professional writer is no guarantee).

    On top of all of that, most people won’t even end up working in their field of study.

    At the end of the day, no one really knows where the economy is going long term. That means there isn’t a surefire path to success, and why I recommend you think harder about what you feel good about pursuing.






  • The other thing you didn’t talk about was the size of the market in general.

    As onbaord CPUs were becoming popular the biggest reason for a GPU was games or video processing. Which, while significant markets, isn’t huge.

    Over the past couple decades, GPUs have made headway as the way to do Machine Learning/AI. Nvidia spent a lot of time and money making this process easier on their GPUs which lead to them not only owning the graphics market, but the much bigger ML/AI market. And I say the AI/ML market is bigger is simply that they are being installed in huge quantities in data centers.

    Edit: My point being that the market shrunk before GPUs became so critical. To counteract Nvidias stranglehold, a lot of big tech companies are creating custom TPUs (Tensor processing units) which are just ML/AI specific chips.