todayWTF 4.8via r/MachineLearning
I moved from network training to deployment optimization and am starting to think that was a right decision [D]
"PhD realization: Being the guy who makes it run > being the guy who fails to train it."
Explain Like I'm Normal
A veteran researcher argues that the industry is shifting from training obsession to deployment optimization. As model architectures stabilize, the real value is moving toward people who can squeeze performance out of hardware and handle massive-scale inference. This reflects a broader trend of 'AI engineering' becoming more lucrative than speculative research.
#career#inference#hardware#optimization
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