https://www.inceptionpoint.ai

LLMs are good at plainly summarizing from the public knowledge base. Scientists should invest their time in contributing new knowledge to public base instead of doing the summarization.

ISYE 8803 Topics on High-Dimensional Data Analytics

``` index-DpuJbHxC.js:40 TypeError: Cannot read properties of undefined (reading '0') ```

On day 1 I realized my work was to deal with several excel sheets of 10~50MB, with huge amount of VBA scripts, rule-based highlighting, charts... They even wrote an internally used extension for those files. Numbers could not handle and crashed.

I need Excel. I asked if I could borrow a PC laptop from the company, no, that's not for interns. I need to bring my own device. I asked if they would pay for Microsoft Office to get installed on my personal MacBook. The answer was obvious, what are you thinking? I had to manage to get Excel for myself, while the full salary they paid me was not enough to cover a license.

I left consulting after that experience and end up working as a "real" data scientist. Nothing like that happened ever. I collaborate with colleagues using different IDEs/editors everyday. If an accountant joins us and tells me notepad is all you need, I would highly respect his choice and continue with my editor. We don't need to argue, our codebase is not locked in any tools.

BTW, I was thinking "it must be a German project" when I saw the name xxxx24 and it turns out to be true :)

Getting into the "higher math" world was really painful for me actually. Seeing how some "modern" techniques (which has already existed for ~400 yrs, not literally modern at all) have solved the problem I struggled with in such an ultimate way made me feel overwhelmed. I felt like a track athlete, gloating over how fast I was running, realizing how modern transportation has revoluted - people no longer move long distances with human power. The quality a good driver needs is attention - on the road and the car simultaneously - not a pair of sporty legs.

The transfer from high school math olympics towards "higher math" requires not only practically a major upgrade in knowledge and toolsets, but also some shift of thinking paradigm - the task is not looking for an elegant and ingenious shortcut to a particular problem, but a highway that is general and inspiring to a fully new field (like how equations opened the door to linear algebra and everything subsequent). I pushed myself to embrace the transition, but it didn't seem to work. I managed to pass the exams and obtained a higher degree, with some expertise in a particular field of application. Still, I always have the feeling that my mathematic understanding is like house built on sand and lack a solid foundation. There is some sort of chasm that I failed to break through...

I agree with the part about mental skills, partially. Experience with math competition improved my concentration and persistence. I found piano practice more contributing in this means.