Am I going the right way with my CS PhD?

<!-- SC_OFF --><div class="md"><p>I've been using AI extensively for ML research, and I've noticed a bottleneck: brainstorming research directions and generating smoke run

<!-- SC_OFF --><div class="md"><p>Agents are amazing. Harnesses are cool. But the fundamental role of a data scientist is not to use a generalist model in an existing workflow;

<!-- SC_OFF --><div class="md"><p>I did my B.Tech in AI/ML where I learned core machine learning concepts like model training, evaluation, etc., and also completed an ML

<!-- SC_OFF --><div class="md"><p> I could really use some outside perspective.</p> <p>I’m a senior ML/CV engineer in Canada with about 5–6 years across research and industry.

<!-- SC_OFF --><div class="md"><p>Hey everyone, I'm an international student studying in the US. I'm on track to graduate late next year. My research is not exactly ML, it is in

<!-- SC_OFF --><div class="md"><p>I want to make an AI Project or something, I want to know how realistic it is for me to be able to make my own like chatbot or something. I know

<!-- SC_OFF --><div class="md"><p>This wasn't always the case, but now almost any research topic in machine learning that you can imagine is now being done MUCH BETTER in industry

<!-- SC_OFF --><div class="md"><p>I have a degree in information technology, but I didn’t focus enough during my undergrad to really grasp technology as a whole. Now, I work in