Learning Resources

Here are some learning resources that I find valuable:

My neurons basically dream/repeat like a stochastic parrot with content from these channels..few Science Educators i love and support! will recommend for first principles thinking. Shoutout for making complex math intuition easy!

• StatQuest with Josh Starmer
• 3Blue1Brown
• These two above: alone will basically spoon-feed you the intuition for Calculus (slopes aka derivatives and areas aka integration). Toss in some Linear Algebra for matrix wrangling and equations, and boom—you're also on your way to understanding that mind-bending higher dimensional latent space stuff!
• Great intuition on higher dimensional latent space: Visualizing high-dimensional data, as humans are restricted by duality 2D(max 3D (2D+ depth maps))
• Artem Kirsanov
• Veritasium
• PBS Space Time
• The Science Asylum (Nick Lucid) It's okay to be little crazy!
• ElectroBOOM
• Kurzgesagt – In a Nutshell
• Vsauce
• LLM 101 Playlist by Andrej Karpathy
• bycloudAI
• Fireship
• ByteByteGo
• exurb1a
• Steve Brunton
• Anton Petrov
• How To Be Successful by Sam Altman - insightful guide on achieving outlier success
• Naval Ravikant on Lex/JRE podcasts - few great guests/conversations on how to calm the mind
• Arvin Ash - Great channel with summaries on complex physics/math concepts.

Compute Focus:

• Linux internals TechTalk by Ken Guyton at google dallas office i think - A 6-video playlist from 2008 covering kernel 2.x. While dated, it provides valuable insights into low-level primitives (which dint change much even today with 5.x) and the thought processes of early developers in meeting workload demands of that era.
• Viacheslav Biriukov's Blog - An excellent summary for SREs (who are lazy to go through linux kernel code and need a kickstart) or dev dealing with terminals/console/shell. The blog provides amazing summaries on shell-related internals such as file descriptors, pipes, terminals, user sessions, and process groups. It also includes good summaries on the Linux Page Cache and DNS resolvers which is crucial for understanding system performance.
• Software 2.0 by Andrej Karpathy - Insightful 2017 article about how neural networks/gradient descent is becoming better "programmer" than humans for certain(or 90% of program space?) tasks. Great perspective on the future of software development/design and hardware accelerators.
• Inference Parallelism in LLMs - Comprehensive overview of different parallelization strategies (Data, Tensor, Pipeline, Expert) for deploying large language models across multiple GPUs. Great resource for understanding the tradeoffs between latency, throughput and hardware configurations when scaling AI inference.

BioHacking Focus:

• Biohacking Lite by Andrej Karpathy - Decent 101 exploration into basic molecules/cells that help our gears run.
• Tracking calories is the important part (bomb calorimeter is the living proof that weight and calorie burn-rate matter ~ Calories ~= joules ~= energy ~= mass ~= weight ~= fat ? Do the math! Can't beat the quantum foam ..only way is tracking calories)
• Bryan Johnson's Blueprint Protocol - Even if the protocol gives some American psycho sigma bale vibes lol..there's few valid stuff to learn on some of the optimal thresholds (meaurements) of the most often-ly done clinical trials

Add LLMs like gpt4 speech to text whisper api.. should be able to learn basically anything by mostly just speaking without running into Carpal tunnel syndrome or needing to type

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