GoKawiil
Tech News
Meta has moved its agentic AI assistant, Muse, into a limited closed testing phase, according to Testing Catalog, gating access through a waitlist and invite codes. An App Store listing reveals the app can connect to Gmail, Google Calendar, health apps, and even users' bank accounts and cards to track spending and suggest canceling unused subscriptions.
Meta introduced a new pricing tier for its Muse Spark model, built for coding and other agentic tasks, that slashes token costs by roughly 95% for developers who agree to let their prompts and outputs be used to train future versions. Standard pricing runs $1.25 per million input tokens and $4.25 per million output tokens, compared to just 10 cents and 20 cents respectively under the data-sharing plan. The move follows a scrapped internal program at Meta that tracked employee computer activity for training data, which was shelved in June after backlash.
Meta released Muse Spark 1.3, an upgrade to its AI coding and agent model, touting benchmark scores that mostly come from a 'max' reasoning configuration still undergoing safety testing and unavailable through any API provider. The version actually shipping to developers via Muse Code and the Meta Model API uses the older 'xhigh' reasoning setting, which scores meaningfully lower on tests like GDPval-AA v2, OSWorld 2.0, and JobBench. Meta disclosed both sets of results in its evaluation report, but its marketing emphasized the higher, currently inaccessible numbers.
Meta Superintelligence Labs has released Muse Voice Transcribe, a real-time speech-to-text model that streams transcription, detects sentence endpoints, and identifies more than 20 distinct speakers without a separate processing step. Trained on over 70 languages (25 thoroughly validated), the model handles long recordings beyond an hour and supports code-switching between languages, all offered via API at $0.18 per hour of audio.
Meta unveiled Muse Voice Transcribe, its first real-time audio perception model, capable of transcribing over 20 speakers simultaneously while switching between more than 20 validated languages, including mid-sentence code-switching. CEO Mark Zuckerberg demoed the tool on X, noting it uses adaptive delay to balance speed and accuracy. The model is now available through Meta's Mac AI app, Muse Code, and its Model API at $3 per 1,000 audio minutes.
Meta Superintelligence Labs has released Muse Voice Transcribe, a streaming speech recognition model that combines transcription, speaker diarization for over 20 voices, and endpointing in a single pass. It supports more than 70 languages, with 25 validated at launch, handles recordings over an hour long, and allows mid-sentence code-switching between languages. The model is live now in Meta AI for Mac, Muse Code, and via the Meta Model API at $3 per 1,000 audio-minutes.