Vision Language Models (Better, faster, stronger)

everyone keeps shouting 'better, faster, stronger.' it's marketing fluff. the actual engineering reality is that 'better' means needing exponentially more data and compute just to keep the weights aligned. speed improvements are mostly achieved through aggressive distillation and pruning, not just architectural magic.

we're still wrestling with the context window limits and the sheer computational cost of visual reasoning. trying to shove massive visual context into current transformer architectures is fundamentally inefficient and memory hungry.

don't get blinded by the hype. if a model costs $500k to fine-tune and takes 48 hours to run inference on an enterprise setup, it's 'stronger' only for the rich labs, not for us.