Why Multimodal AI Is Massively Overhyped
Multimodal AI sits at peak hype on Gartner's 2025 cycle. But 80% of pilots fail to scale beyond testing....
Why AI Can't Count the R's in Strawberry
LLMs confidently say strawberry has two R's because they've never seen letters—only tokens. This tokenization blindness predicts where AI will fail....
The ASR Privacy Paradox
ASR systems need training data. Training data contains sensitive audio. How federated learning solves the conflict between ML requirements and privacy laws....
Speaker Diarization: The Hardest Problem Nobody Talks About
Why Zoom transcripts attribute quotes to the wrong people. The cocktail party problem isn't solved - it's hidden. Multi-device synchronization as a workaround....
Voice to Context to Action: An Operational Framework
From voice to context to action: an operational framework for voice AI that does more than transcribe — it understands and acts....
Voice AI: From Demonstration to an Evaluated Deployment
Evaluate voice AI across capture, speakers, channels, recognition, correction and latency before relying on a demonstration....