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The harder the task, the smaller the first step should be.
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The harder the task, the smaller the first step should be.
43 followers · 735 following

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Achievement: Pair ExtraordinaireAchievement: QuickdrawAchievement: Pull Sharkx2Achievement: Arctic Code Vault Contributor

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Achievement: Pair ExtraordinaireAchievement: QuickdrawAchievement: Pull Sharkx2Achievement: Arctic Code Vault Contributor

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OccupyMars2025/README.md

6

7, 8

9, 10, 11, 12

At Harvard, knowledge enters my mind at a terrifying rate every day.

Current progress:

2025/5/30 7:00 - 6/3 23:00 : study the paper of AlphaFold 3: Accurate structure prediction of biomolecular interactions with AlphaFold 3

2025/5/31: {"push ups + Mountain Climbers": 400}, {"cartwheels": 100 meters}, {"running": 5km}
2025/5/31 6:46-7:37: section "Network architecture and training"
2025/5/31 7:37-10:12: section "Accuracy across complex types"
2025/5/31 10:12-13:08: section "Predicted confidences track accuracy"
2025/5/31 13:08-14:29: section "Model limitations"
2025/5/31 14:29-14:57: section "Discussion"

Let’s tackle the hardest part now—this is the core and most challenging section of the paper.
2025/5/31 14:57-: section "Methods"
2025/5/31 14:57-: Full algorithm details, Supplementary information(https://static-content.springer.com/esm/art%3A10.1038%2Fs41586-024-07487-w/MediaObjects/41586_2024_7487_MOESM1_ESM.pdf), 45 pages in total
2025/5/31 14:57-15:50: 1 Notation
2025/5/31 16:30-17:00: run 5km in 28min

Goals 2025/5/30 - 6/20:

0. Run 10km in 40 minutes, run a half marathon in 1 hour and 30 minutes, do 300 push-ups in a row, do 50 pull-ups in a row

1. Complete the study of all papers and source codes related to AlphaFold 2&3

https://gostanford.com/

https://www.youtube.com/@GoArmyWestPoint

https://www.paralympic.org/

https://www.olympics.com/

Go Navy, Beat Army !

Go Army, Sink Navy !

Every Engineer is an Athlete

An engineer who doesn’t aspire to be an Olympic champion isn’t a qualified engineer.

Eat when hungry, sleep when tired, work when awake.

Pinned Loading

  1. ColabFold ColabFold Public

    Forked from sokrypton/ColabFold

    Making Protein folding accessible to all!

    Jupyter Notebook

  2. alphafold3-pytorch alphafold3-pytorch Public

    Forked from lucidrains/alphafold3-pytorch

    Implementation of Alphafold 3 from Google Deepmind in Pytorch

    Python

  3. openfold openfold Public

    Forked from aqlaboratory/openfold

    Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2

    Python

  4. google-deepmind-alphafold3 google-deepmind-alphafold3 Public

    Forked from google-deepmind/alphafold3

    AlphaFold 3 inference pipeline.

    Python

  5. evo2 evo2 Public

    Forked from ArcInstitute/evo2

    Genome modeling and design across all domains of life

    Jupyter Notebook

  6. Protenix Protenix Public

    Forked from bytedance/Protenix

    A trainable PyTorch reproduction of AlphaFold 3.

    Python