Jack Dorsey’s Block has announced Dessa, an artificial intelligence model developed by training it exclusively on human conversation. This approach differs from models that rely on written text, aiming to replicate how humans learn speech.
The company shared examples of Dessa's interactions, which sometimes exhibit awkward or uncanny characteristics, such as mistaking a speaker for someone else or going on unexpected tangents during conversations.
Dessa is described as a true speech-to-speech model, meaning all its knowledge originates from spoken human language. It is designed to operate locally on devices, specifically noted to run on a MacBook Pro M4 Max or better hardware.
The development team stated their motivations for creating Dessa were curiosity, enhancing understanding between humans and AI, and improving safety in AI interactions.
Block's team highlighted that current voice AI often converts speech to text, losing nuances like human timing and emotion. Dessa seeks to address this by maintaining the richness of spoken interaction.
The model's focus on understanding emotional cues in voices is intended to prevent situations where AI might fail to recognize a user's distress, thereby improving safety in AI-human communication.
Block plans to provide early access to Dessa to a select group of AI safety researchers. This step suggests an emphasis on evaluating and refining the model's safety aspects and its ability to interpret human communication effectively.
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Block's research lab released Dessa, a new voice model trained on human speech that runs locally and exhibits human-like expressions including laughs, pauses, and cries. Dessa is a full-duplex model, capable of simultaneous speaking and listening, and aims to provide more natural interactions by building emotion directly into its speech generation.
Block, led by Jack Dorsey, announced Dessa, an AI model trained exclusively on human conversation to improve speech-to-speech interaction. The model aims to understand human timing and emotion better, running locally on devices like the MacBook Pro M4 Max.