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Practical insights on scaling speech pipelines and reinforcement learning for multilingual multimodal models—based on 30+ projects across 50+ languages
VLMs perform well on academic benchmarks—but struggle in business and STEM workflows. Learn why real-world reasoning challenges remain unsolved.
Technical brief from Turing AGI Advancement on real-world multimodal data pipeline design, covering annotation frameworks, calibration, QA, and ethical considerations for instruction tuning.
Speech alignment across 50+ languages depends on structured calibration—here’s how leading teams align transcripts, audio quality, and phonetic diversity.