Dessa AI · Block Deep Learning Research Lab · Speech-Only Foundation Model

Dessa AI — The Full-Duplex Speech Model Trained Only on Sound

Dessa AI is a full-duplex speech-to-speech foundation model developed at Block. Trained from scratch exclusively on raw human conversation audio—with zero text tokens and no pretrained language model—Dessa AI learns language, timing, laughter, interruptions, and emotional prosody directly from sound, using hundreds of times fewer words than text LLMs.

Block Team Dessa researchers testing live full-duplex speech conversations

Block Team Dessa · 1× NVIDIA GB200 NVL72 training · Local MacBook Pro M4 Max inference.

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Training Modality

Trained end-to-end on raw conversational audio without text transcripts or text LLM initialization.

100× Fewer
Word Efficiency

Acquires fluent language and world dynamics from hundreds of times fewer words than text LLMs.

1× GB200 NVL72
Training Compute

Trained on a single NVIDIA GB200 NVL72 rack—orders of magnitude smaller than frontier text clusters.

M4 Max Local
Edge Inference

Runs faster than real-time locally on an Apple MacBook Pro with an M4 Max chip or better.

Architectural Breakthrough

Why Learning Directly From Sound Changes Everything

Conventional voice assistants bolt a speech encoder and TTS vocoder onto a text LLM—stripping away 90% of paralinguistic signal. Dessa AI treats raw sound as its native representation.

Legacy Cascade / Text-Backbone Voice

ASR → Text LLM → TTS Pipeline

  • Collapses timing, breath, hesitation, and overlapping speech into flat text tokens before reasoning.
  • Relies on rigid Voice Activity Detection (VAD) turn-taking, causing awkward pauses or robotic talk-overs.
  • Requires trillions of text tokens and massive datacenter clusters for training and inference.
  • Synthetic laughter and emotion are post-processed style tags rather than emergent conversational dynamics.
Block Dessa AI Architecture

End-to-End Full-Duplex Audio Native

  • Trained from scratch exclusively on human conversation audio—zero text at any stage of pretraining.
  • True full-duplex listening and speaking: backchannels ('mm-hmm', 'yeah'), yields on interruption, and senses awkward silences.
  • Hears non-speech acoustic events natively, such as a coffee machine ding or room echo on a speakerphone.
  • Emergent prosody control: whispers, sighs, laughs, sings, and shifts emotional tone mid-sentence.

Prosody & Stress Test

Explaining CUDA Parallel Programming Across Emotional Extremes

To prove that a pure-audio model retains technical coherence while modulating vocal expression, Block researchers asked Dessa AI to explain NVIDIA CUDA parallel programming under rapid emotional shifts—switching seamlessly between breathless excitement, whispering, sarcasm, and theatrical urgency without losing technical accuracy.

  • Maintains technical explanation of GPU thread blocks, warps, and shared memory while shifting vocal timbre.
  • Demonstrates that semantic knowledge and paralinguistic expression live in a unified acoustic latent space.
  • Zero text prompting or TTS emotion tags—steered purely through conversational voice interaction.

Compute & Silicon Footprint

Trained on 1× GB200 NVL72. Runs Locally on MacBook Pro M4 Max.

1× NVIDIA GB200 NVL72

Single-Rack Frontier Training

While frontier text-and-multimodal models require tens of thousands of GPUs, Dessa AI was trained on a single NVIDIA GB200 NVL72 rack.

MacBook Pro (M4 Max+)

Faster-Than-Real-Time Local Inference

Dessa AI executes full-duplex speech-to-speech inference locally on a laptop with an Apple M4 Max chip or better at faster-than-real-time speeds.

100× Fewer Words

Child-Like Language Acquisition

By modeling prosody, cadence, and social feedback directly, Dessa AI mirrors human developmental efficiency.

Team & Origins at Block

Built by Team Dessa, Reporting to Jack Dorsey

Dessa AI was created by a small deep learning research lab inside Block, Inc., founded by former members of the Toronto machine learning startup Dessa (acquired by Square/Block). The team is led by Ragavan Thurairatnam and reports directly to Block co-founder Jack Dorsey.

Project Lead

Ragavan Thurairatnam (@RagavanThurair)

Executive Sponsor

Jack Dorsey (@jack)

Core Researchers

Louay Hazami · Hashiam Kadhim · Qi (Alex) Liu · Rayhane Mama · Aydin Polat · Marc Tyndel

Research Interns

Cara Ji · Jibran Iqbal Shah · Dvir Zagury-Grynbaum

Former Interns

Aryan Sharma · Olivia Yan

Open Call for Audio AI Safety Researchers

Because a model that sounds indistinguishably human and runs locally on consumer hardware introduces novel safety, impersonation, and emotional-attachment risks, Block has not yet released model weights or a public API. Team Dessa is actively collaborating with external safety researchers.

Safety & Research Inquiries: ragavan+dessa@block.xyz

block.xyz/dessa ↗

Frequently Asked Questions About Dessa AI

What is Dessa AI by Block?

Dessa AI is an experimental full-duplex speech-to-speech foundation model developed by a deep learning research lab at Block, Inc., trained from scratch exclusively on raw human conversation audio with zero text.

Does Dessa AI use a text LLM or speech-to-text under the hood?

No. Dessa AI uses no text transcripts, no automatic speech recognition (ASR), no text LLM backbone, and no separate text-to-speech (TTS) vocoder. It processes and generates audio waveforms directly.

How much compute was required to train Dessa AI, and where can it run?

Dessa AI was trained on a single NVIDIA GB200 NVL72 system and runs faster than real-time locally on an Apple MacBook Pro equipped with an M4 Max chip or better.

Where can I listen to all Dessa AI audio samples?

You can stream all 21 unsteered official recordings with synchronized dual-channel waveforms, Moment markers, and full transcripts directly on this site.