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Achievement: Pull Shark

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Achievement: Pull Shark

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@IBM

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nataxcan/README.md

Welcome

I'm Nathan Axcan, current intern @ IBM Research Zurich

💪Working on

  • (systems work) implementing "span semantics" a.k.a. parallel prefill, independent caching, etc on IBM's official vllm fork
  • (DL research work) researching independent caching opportunities of hybrid-architecture LLMs
  • (DL foundational work) researching rendered LLMs

🙋‍Lateralizations

Three things about me:

  1. I love to talk about interesting code, ideas, dig deep, think as deep as humanly possible
  2. Love the entrepreneurial/economics/incentives aspects of most topics
  3. In love with technology, philosophy, but my biggest love of all is deep learning

🔫 Lexigraph

Shoot an email over at nathanaxcan@gmail.com and I'll be happy to hear what you have to say. Who knows, maybe we can help eachother out!

📚 Previous work

  • startup analysis @Plug&Play Tech Center
  • messing around in python (finetuned a chatbot before ChatGPT came out)
  • former data scientist @Cortexter
  • podcasted about motivation and productivity @Slim Radio
  • co-led development for EU-funded VR + holograms ed-tech research project Hololearn
  • strategic advising (startups, projects)

Popular repositories Loading

  1. AEGNN_reproduction AEGNN_reproduction Public

    Jupyter Notebook 1

  2. Aff-Wild-models Aff-Wild-models Public

    Forked from dkollias/Aff-Wild-models

    Python

  3. nataxcan nataxcan Public

    Config files for my GitHub profile.

  4. Inverse-Reinforcement-Learning Inverse-Reinforcement-Learning Public

    Forked from MatthewJA/Inverse-Reinforcement-Learning

    Implementations of selected inverse reinforcement learning algorithms.

    Python

  5. graph2nn graph2nn Public

    Forked from facebookresearch/graph2nn

    code for paper "Graph Structure of Neural Networks"

    Jupyter Notebook

  6. specrepair-mod specrepair-mod Public

    Forked from sen-uni-kn/specrepair

    SpecRepair is a neural network repair algorithm. This is a possible improvement upon it.

    Python