John Doe 2

I looked through the profiles of PhD students at top 4 ML PhD programs (BAIR at Berkeley, SAIL at Stanford, CSAIL at MIT and CMU ML at CMU) and it seems PhD students in these programs are mostly from Berkeley, Stanford, MIT, CMU, Harvard, Princeton, Tsinghua or IITs. Is it just because students from these schools are just smart and hard-working or is it because undergrad/masters prestige matters in ML PhD admissions? I have been admitted to Georgia Tech for Spring 2023 as a transfer and I am going to major in math(statistics concentration) and CS there. But after looking through the profiles of the ML PhD students at these programs, I am starting to wonder if I have to stay one and a half year more at my current community college in California and try to transfer to Berkeley EECS instead of transferring out asap from community college... Do you think it's a good idea for me to sacrifice up to one and a half year to get into Berkeley EECS or should I just transfer asap to GT (if I am interested in pursuing ML PhD)? I also got into Columbia GS btw Many people advise me to get out of community college as soon as possible since there aren't much things I can do in CC, but after looking through the profile and finding only one GT graduate in CMU ML PhD program, I am starting to wonder if I really need to try to transfer to Berkeley.. Should I just transfer asap and go for masters if I get rejected from top ML PhD programs? (Like apply to PhD programs for Berkeley and MIT but for Stanford apply to masters and for CMU, apply to both masters and PhD + MSCS at Princeton and Cornell)