With the advent of LLMs, multimodality and “general purpose” AIs which seat on unimaginable amounts money, computing power and data. I’m graduating and want to start a PHD, but feel quite disheartened given the huge results obtained simply by “brute-forcing” and by the ever-growing hype in machine learning that could result in a bubble of data scientists, ML researchers and so on.
I mean there are plenty of major areas in ML that LLMs cannot even begin to address (e.g. processing time-series data - XGBoost still reigns supreme, edge ML, etc.). Also, keep in mind that most of the people at major LLM groups are PhD so chances are if you wanna work even on LLMs, having a PhD will help. Afterall, scaling is good but if your research shows more efficient training pathways, the difference can be 9-figure sums for these companies.