You're right, I wasn't clear. But I'm a full-time ML researcher. In terms of advancing the field, my contributions so far have been modest, but they're there. S

You're right, I wasn't clear. But I'm a full-time ML researcher. In terms of advancing the field, my contributions so far have been modest, but they're there. Some of my favorite ideas were swarm training (https://battle.shawwn.com/swarm-training-v01a.pdf https://battle.shawwn.com/swarm-training-v01a.pdf), stop loss for stabilizing GAN training (https://twitter.com/search?q=from%3Atheshawwn%20stop%20loss&src=typed_query https://twitter.com/search?q=from%3Atheshawwn%20stop%20loss&...), and getting GPT to play chess (https://www.theregister.com/2020/01/10/gpt2_chess/ https://www.theregister.com/2020/01/10/gpt2_chess/) back when that was a shocking idea. And in terms of cited research, https://arxiv.org/abs/2101.00027 https://arxiv.org/abs/2101.00027 has been the most impactful. There's significant overlap between ML research and ML dev. If I can do it without most of that list, it should give people here some hope of joining the field without needing to immerse themselves in theory.