
Block, Jack Dorsey’s fintech company, has released Dessa, an AI model trained exclusively on human speech data rather than text transcripts. The system operates as a true speech-to-speech engine, designed to preserve natural timing and emotional nuance often lost in traditional text-to-speech pipelines. Block claims the model can run locally on devices like the MacBook Pro M4 Max, emphasizing privacy and accessibility. Early access is being granted to a small group of AI safety researchers to evaluate how well the model detects emotional context.
Read originalEarlier coverage that leads up to this article, and what followed. Lines connect each piece to the closest one after it, converging here.
Hugging Face Blog · July 1, 2026 · Background
TechCrunch AI · July 8, 2026 · Background
Hugging Face Blog · July 15, 2026 · Background
TechCrunch AI · July 31, 2026 · Background
Sam Witteveen · August 18, 2026 · Background
WIRED AI · August 27, 2026 · Background
Sam Witteveen · August 31, 2026 · Background
WIRED AI · September 2, 2026 · Background
Ollama Blog · October 24, 2026 · Background
llama.cpp Releases · October 24, 2026 · Background
Block launches Dessa, a speech-to-speech AI model
2 developments
© The Verge AIMeta’s Muse Charm isn’t a finished product; it’s an invitation to hack. A non-coder used Claude Code to transform a $50 Waveshare ESP32-S3 dev board into a fully functional AI companion, adding ElevenLabs voice synthesis, custom Tamagotchi-style minigames, and remote camera controls that Meta’s official firmware lacks. This reveals a critical truth: the value of Meta’s new hardware ecosystem lies not in its out-of-the-box utility, but in its open-source API allowing anyone to rewrite the experience. The gap between Meta’s polished demo and the actual user reality is bridged entirely by third-party AI coding tools.
© The Verge AIApple is finally unlocking its AI suite for Chinese users with the iOS 27.3 beta, marking a significant regulatory milestone after months of approval delays. The rollout relies on Alibaba’s Qwen model rather than OpenAI, integrating features like notification summaries and visual intelligence directly into the OS. By sidestepping the new Siri in favor of established text and image tools, Apple is prioritizing immediate utility over the full generative experience. This move effectively brings Apple’s AI capabilities to a massive new market, albeit with localized constraints that distinguish it from the global release.
© The Verge AISam Altman is pushing back against the local AI trend, arguing that hoarding DRAM in personal devices is a global waste during a severe supply crunch. He points out that consumer hardware sits idle most of the time, whereas cloud data centers achieve the high utilization rates needed to justify the billions invested by players like OpenAI and Stargate. This isn't just an opinion; it's a defense of the centralized infrastructure model against the growing open-source movement. The real-world impact is visible in the locked-up supply from Samsung and SK Hynix, which drives up costs for everyone else.
This release quietly cements llama.cpp as the universal inference runtime by finally supporting NVIDIA's latest CUDA 13 stack alongside AMD's ROCm 10.0. The inclusion of native builds for Linux arm64 with Snapdragon chips, covering CPU, Adreno GPU, and Hexagon NPU, signals a serious push into mobile edge deployment. While Apple Silicon KleidiAI is disabled in this specific build, the broader hardware coverage means developers no longer need to compile from source for most modern accelerators. It’s less about new features and more about removing friction for anyone running local models on bleeding-edge or diverse hardware.
© Matt WolfeGoogle launched Gemini 4 Carbon, a new model variant aimed at providing high performance at a lower cost for inference tasks.
© Lev SelectorGoogle's new model, Gemini 4 Carbon, has taken the top spot on the LMSYS Chatbot Arena leaderboard.