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AI Researcher

Working on evolutionary ML with a focus on adaptive multi-objective functions and perserving weights while add/sub/modifying features parameters. Curious about Riemannian manifolds, chaotic blackbox uncertainty, signal processing, and stochastic calculus.

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Career Updates

26/05 - Void Linux Hell

  • I got pilled into void linux by a homie that does RL x malware because you can set up KVM-based VMs for your workflow and I hated windows so i thought its not that bad. Oh my god was it bad. Its definitely an issue on my end but i quit only to come back 5-10 minutes right after like 4 times. I spent the entire day trying to get hyprland to work. I did and tried to set up an auto booter for hyprland and then fucked up my config to lock myself out since greetd and elogind were trying to login at the same time in TTYn. I tried live USB booting and mounting my partitians but it never seemed to work when i rebooted, so as any sane person would do: i restarted from boot, lol. But i spent enough time getting slapped around that i remembered everything so it wasnt too long. I still havent gotten up to the part where i was before but its ok. Im recharging from my rage quit last night at 3am. But why go through all this pain? I need to learn linux, fuck windows and its shitty account login to use an OS and I want to build a custom VM from scratch to make my AI workflow hyper customisable. Plus its a nice side quest from math. Oh and a company i want to join uses it sooooo
  • Finally im taking the time to actually learn proof writing properly. Its quite enjoyable, the dopamine hits different with each proof. Definitely a deeper understanding of wtf is happening too. All of my books say "prove this" and im just like "ok, well shit" so now im commiting to it properly.
  • I folded and bought Emily's category theory book for after my other two, probabilisitc method book and a measure theory book for after i read spivak's calculus and axlers LA. Now i got all the books i really need and all is left is to grind with proof writing. OH and i got "Proof and the Art of Mathematics" and it's solution book to really commit to proof writing. I find all the dedicated proof writing books are so fucking dry and boring but this covers a lot of different topics so i hope its not dry asf. I found out my fav author is Dmitry N. Kozlov too and got both of his books (they're amazing). And lastly, im quite obsessed with homotopy theory and after the podcast with Ghrist about how cohomology enables feasibly computable homotopy I stumbled across "Cohomology Operations and Applications in Homotopy Theory" for $30AUD so i insta bought, naturally. I find that having all these books is quite useful since i can scan, pick up a few key words and go down some rabbit holes that push my intuition a lot further. I'll obviously read them but this intuition boost is also extremely good for going through the foundations -- a motivation boost and deeper understanding of why everything is the way it is. Im still focusing on discrete math and am thinking of ways to convert all of my continuous learnings into a discrete setting with algebra and combinatorics (hence the addiction). I want to get good at calculus because it appears everywhere (vector calc) in discrete land and measure theory for actually making the system able to learn, which is also why i got "The Probabilsitic Method" which combines stats with combinatorics.
    • Also as a side note, all of these skills ive chosen for 2 reasons: i think they're broken and i have a lot of ideas for how to build some advanced AI stuff and that even if i end up not doing things successfully with my AI journey (short term) i can always get hired since the skills are highly transferable to quant, cyber, etc etc. Like they're highly desirable skills regardless, it just so happens im extremely interested in them. Aint it some shit that things work out like this! I'll show a picture of my book setup when them all come !
  • So then the plan is to write proofs of my ideas to actually formalise them properly and then write a KVM custom VM in C and cater it to my AI workflow for cyber and fuckign shit up. And learning linux and C will be super useful for then writing my own kernal for when i buy some GPUs and design custom hardware.
  • I edited podcasts for literally 2 days straight and my sleep schedule has been fucked because i go to bed at 3am but the sun beams my room (with my blinds closed) so i wake up at 7-8 and get shit all sleep. So im thinking im literally forced to go to bed at 10-11am now...Plus it turns out my frens are actually awake during my wakeup times so fuck it
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Podcast

I host a tecnhical podcast about math, science, crypto, HFT/MEV and infosec. I have experience in these fields which enables me to ask deeper questions than other podcasts with hosts with surface elvel knowledge.

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Talks

Listen to my first ever interview when I was just starting out in my career! I talked about MEV and reverse engineering :)

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