AI promises a smarter, faster, more efficient future, but beneath that optimism lies a quiet problem that’s getting worse: the data itself.
When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...
To feed the endless appetite of generative artificial intelligence (gen AI) for data, researchers have in recent years increasingly tried to create "synthetic" data, which is similar to the ...
10don MSNOpinion
Strategic autonomy in AI needs public investment across data, models, talent and governance
India's AI ambitions are hampered by its reliance on global tech giants for foundational models and infrastructure. While ...
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