Jason Antic

Income strategies to support your ML research: 1. Github Sponsors / Patreon @calebporzio is making $100k/yr by having a free open source project. He gives access to video tutorials for users who sponsor him. https://calebporzio.com/i-just-hit-dollar-100000yr-on-github-sponsors-heres-how-i-did-it …

2. Production Maintenance Fees Spend a few months getting really good at turning Colab notebooks into APIs in Kubernetes. Spend a year putting models in production, and then charge a monthly fee to maintain the clusters.

3. Stock market returns If you get a high-paying SWE or ML job and save $120k, and put it in the S&P 500 - which on average has ~10% yearly returns - you'll earn $1k/month for the rest of your life to support your research.

4. Content Marketing There are hundreds of companies looking for ML content marketing. You can reproduce papers, write about it, and sell it. Rates vary between $250-4k per article.https://twitter.com/EmilWallner/status/1162289417140264960 …

5. Productionize Freelancer posts To reduce the risk of making something that's not useable and monetizable. Create a list of 100-500 ML project posts on e.g. Upwork. Find a recurring pattern, and build a product to solve it. The authors of the posts are your first customers.

6. Productionize ML models Create a startup around an ML model, say Transformers(@huggingface) or Colorization (@deoldify). Either raise cash upfront like the former, or bootstrap it by selling access to the model like the latter.

7. Bootstrap your food and housing Many large cities have thriving squat and dumpster diving communities. You'll meet a bunch of interesting people and have great adventures, but sometimes it can be distracting from your research endeavors.