Dear friends,
AI has an Instagram problem. Just as Instagram’s parade of perfect physiques makes many people feel they don’t measure up, AI’s parade of exciting projects makes many people feel their own projects are lacking. Just as pictures of people’s perfect lives in the media aren’t representative, pictures of AI developers’ postings of their amazing projects also aren’t representative.
I’m here to say: Judge your projects according to your own standard, and don’t let the shiny objects make you doubt the worth of your work!
Over the years, I’ve occasionally felt this way, too, and wondered if I was working on a fruitful direction. A few years ago, when reinforcement learning (RL) made progress on Atari games, Alpha Go was in the headlines, and RL videos using OpenAI Gym circulated on social media, I was still focused on supervised learning. Part of me wondered if I was missing out. It certainly did not help when friends kept asking me about the cool RL work they read about in the news. Fortunately, I ignored the feeling that the grass might be greener on the other side and stuck to what I was excited about.
AI develops so quickly that waves of new ideas keep coming: quantum AI, self-supervised learning, transformers, diffusion models, large language models, and on and on. Some, like quantum AI, have had essentially no impact in applications so far. Others have already had a huge impact. Because our field evolves, it is important to keep learning and ride the waves of change. For the record, I think large language models (LLMs) like ChatGPT (and, to a significant but lesser extent, diffusion models, best known for generating images) will have a transformative impact on AI, but they are far from the only things that will be important.
Someone else’s sculpted physique does not take away from your beauty. And the emergence of a hot new technology doesn’t mean your current project isn’t also valuable, assuming it’s technically sound, has a reasonable expectation of impact, and isn’t made obsolete by newer technology (which doesn’t happen very often). Projects of all shapes and sizes can be wonderful, and what’s buzzy today is only one of the many things that will prove valuable in the future.
I'm not advising you to ignore the news. Paying attention to new developments in AI not only helps you stay on top of the field but also can inspire you. Being inspired by Instagram is fine, but changing your life because of FOMO is less helpful.
So, if what you’re working on makes sense to you, maintain your faith and keep going! Maybe you’re training XGBoost on a structured dataset and wondering if you’re missing out on ChatGPT. You may well be onto something even if XGBoost isn’t in the news.
After all, think about how all the LLM researchers must have felt a few years ago, when everyone was buzzing about RL.
Keep learning!
Andrew