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Hi {{first_name|everyone}},

Microsoft is trying to cut the waiting out of voice AI, and the most interesting part is a transcription model that starts guessing your words before you've finished the sentence.

We've also got a study on whether AI-assisted writing still feels like yours, tools for adding an agent to your product, getting a project online fast, and improving AI-search visibility, plus an animated sci-fi film made with AI.

Let's get right into it.

🤿 DEEP DIVE

The quick take

  • Microsoft introduced three models, and they are available through Microsoft Foundry and MAI Playground, with additional availability through OpenRouter, Vercel, and other platforms

  • MAI-Transcribe-2-Streaming starts partial transcripts just over 100ms after receiving audio

  • It supports 60 languages and ranks first on Artificial Analysis for final and partial transcription accuracy

  • MAI-Voice-2.1 supports 23 languages and 26 locales with the same voice across languages

  • MAI-Voice-2.1-Flash can generate 45 seconds of audio with 150ms end-to-end latency

    ___________________

Transcript Starts Before You Finish Speaking

A lot of voice AI comes down to something pretty mundane.

Waiting.

Waiting for someone to finish talking. Waiting for the transcript. Waiting for the model to think. Then waiting again for the reply to become audio.

Microsoft AI is trying to squeeze that delay from both ends with three new models, and the transcription side is probably the most interesting here.

MAI-Transcribe-2-Streaming doesn't wait until you've finished speaking to start producing text. It begins generating early guesses, called partials, just over 100 milliseconds after receiving audio, then keeps revising them as more context arrives.

That means an agent doesn't necessarily need to wait for the whole sentence either.

It can potentially start reasoning or calling tools while you're still talking.

The transcript keeps changing

Those early words aren't treated as final.

The model produces a partial transcript, updates it as you continue speaking, then commits a stable version. Microsoft says it supports 60 languages with continuous automatic language detection.

On Artificial Analysis, it ranks first for accuracy on both final and partial transcripts. Microsoft also says its internal evaluations found words appeared in the transcript twice as fast as its closest competitor for things like live dictation and subtitling.

The introductory price is $0.54 per hour of audio through the end of the year.

Then the reply has to speak

The other half of the loop is MAI-Voice-2.1 and its faster sibling, MAI-Voice-2.1-Flash.

Both support 23 languages and 26 locales, with a single voice able to switch languages while keeping the same speaker identity and using a native accent in each language.

Flash is the speed-focused version. Microsoft says it can generate 45 seconds of audio with 150 milliseconds of end-to-end latency, with 55% faster model inference and pricing of $15 per million characters. The standard Voice 2.1 model costs $22 per million characters.

Both also support voice cloning from a few seconds of reference audio, with consent guardrails built in.

And I think the bigger idea here is the combination.

A voice agent has to hear, understand, decide and speak fast enough that the interaction still feels like a conversation. Faster transcription gives the system more time to start working. Faster speech generation reduces the delay at the other end.

So the saved milliseconds aren't really the product by themselves. They're extra room for the agent to do everything in between.

🤝 FROM OUR FRIENDS

A quick share we thought you might find useful

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🔥 WHAT’S THE BUZZ

What people are building, sharing, and talking about

What I found interesting is that doing more with AI didn’t necessarily make the writing feel more like your own. Prompting and editing both seem to help with that, just in different ways, but even when people did both, writing without AI still felt more personally theirs.

When does AI-assisted writing ✒️ still feel like _your_ writing? How do interaction choices matter? Our new study examines how 2 everyday choices, iterative prompting and direct editing, shape… | Christian Guckelsberger

When does AI-assisted writing ✒️ still feel like _your_ writing? How do interaction choices matter? Our new study examines how 2 everyday choices, iterative prompting and direct editing, shape psychological ownership of AI-assisted writing: https://lnkd.in/giNtpKui 🤓 We ran a preregistered experiment (N = 273) in which participants wrote short creative stories either (A) entirely without AI, or with (B) AI using single-prompt vs iterative prompting, crossed with (C) whether they could directly edit the generated text afterwards. ❕ Key finding #1 = an interaction: editing strongly increased ownership after single-prompt generation (Δ = 0.89), but much less after iterative prompting (Δ = 0.27). Iterative prompting thus supported psychological ownership mainly when editing was unavailable. This suggests prompting and editing can provide partially substitutable routes to ownership: both let users invest themselves in and exert control over the text, but at different stages of the writing process. More interaction was not simply additive! ❕ Key finding #2: every AI-assisted workflow still produced significantly & substantially lower ownership than writing without AI, even when participants could iteratively prompt and edit. With AI writing tools, one-shot delegation can be particularly harmful when ownership matters. ➕ Bonus finding: participants who were more intrinsically motivated also felt substantially more ownership over their stories. Exploratorily, the prompting × editing effect was strongest at lower intrinsic motivation and attenuated as intrinsic motivation increased. Research at Aalto University together with Niki Pennanen and Pyry Kanerva, supporting and extending previous work by e.g. Fiona Draxler, Nikhita Joshi and Daniel Vogel.

LinkedIn

⚒ TOOL SNAPSHOTS

Futuristic tools within AI, no-code, and productivity

  • Let users just ask your product to do things.

    Why it’s useful: I like this for SaaS teams that want an agent inside their product without, well, having to build the whole agent experience themselves.

  • Probably the quickest way to get a project online.

    Why it’s useful: Handy when you’ve got a folder or ZIP and just need a working URL now, with previews and versioning there if the project turns into something more serious.

  • Do the actual work behind improving your AI-search visibility.

    Why it’s useful: I can see this being useful for smaller marketing teams that know GEO matters but don’t really want another dashboard, or a specialist doing all the research, rewriting, and publishing by hand.

🤖 AI MADE THIS

Interesting and inspiring creations made with AI

Palm Pets imagines genetically engineered animals becoming pocket-sized consumer products

Palm Pets imagines a biotech breakthrough that turns exotic animals into tiny pets you can hold in your hand. K.A. Betancourt built the 14-minute animated sci-fi film with a mix of AI image, video and music tools, creating an entire fictional consumer world around the idea. It’s cute on the surface, but things don't stay cute for long. The film is currently participating in the Higgsfield Global Film Festival.

AI used
Confirmed tools include Higgsfield Cinema Studio and Elements, Higgsfield Soul 2.0 with Moodboards, Nano Banana, GPT Image and Suno for the original soundtrack.

ℹ️ ABOUT US

The Intelligent Worker helps you to be more productive at work with AI, automation, no-code, and other technologies.

We like real, practical, and tangible use-cases and hate hand-wavy, theoretical, and abstract concepts that don’t drive real-world outcomes.

Our mission is to empower individuals, boost their productivity, and future-proof their careers.

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