With Apple Intelligence in iOS 27, dictation uses an on-device model to improve spelling, punctuation and capitalization. Apple says it’s available in English on “iPhone 17 Pro, iPhone 17 Pro Max, iPhone Air, or later,” and its feature availability page lists nine varieties of English. That device list is narrower than the one for Apple […]
Siri AI is beginning its public rollout as Apple transforms its familiar assistant into a substantially more conversational system built around personal context, onscreen awareness, web knowledge, and the ability to perform actions across apps.
The beta is available first in English on compatible devices running iOS 27, iPadOS 27, macOS 27, watchOS 27, and visionOS 27. French, Japanese, Korean, Portuguese, and Spanish support is scheduled for October. Availability remains more limited in some regions, with Siri AI initially unavailable on iPhone, iPad, and Apple Watch in the European Union and unavailable in China while Apple addresses regulatory requirements.
The release follows several years of gradual Apple Intelligence expansion, but Siri AI represents a more fundamental change. Instead of handling each request largely as an isolated command, the assistant can maintain conversations, find relevant personal information, understand what is displayed on a device, and combine those capabilities to complete multistep tasks.
Image Credit: Apple Inc.
Siri AI can connect personal context with app actions
The system can search across a user’s messages, email, photos, notes, and other information when responding to a request. Apple offers an example in which someone asks what a family member suggested doing during an upcoming visit. Siri can locate the relevant conversation, find a recipe previously sent by email, and then place the ingredients into a Reminders grocery list.
That combination of retrieval and action is central to the new design. Siri AI can draft an email, edit and share photos, create calendar events, manage reminders, control media, and perform other supported actions without requiring users to manually move information between applications.
Third-party apps can participate through Apple’s App Intents architecture. Existing integrations include tasks such as messaging through WhatsApp or playing an audiobook in Audible, with Apple also previewing deeper capabilities in applications including Microsoft Outlook, Notability, and Tripsy.
Onscreen awareness adds another layer. Siri can identify information currently visible on a device and act on it. Someone viewing a sports website, for example, can ask Siri to identify upcoming home games and add them to Calendar without manually copying dates.
Apple has also expanded Siri beyond voice. On iPhone, users can invoke the assistant with the side button, voice command, or by swiping down from Dynamic Island. On iPad and Mac, Siri AI is integrated into Spotlight, while systemwide context menus can send selected files, images, or text directly to the assistant.
Image Credit: Apple Inc.
Siri AI gets its own app and conversation history
Siri AI is no longer confined to a temporary interface that disappears once a request is complete.
Apple has introduced a dedicated Siri app where users can begin new conversations or revisit previous ones. Conversation history can sync privately through iCloud across iPhone, iPad, Mac, Apple Watch, and Apple Vision Pro, allowing a discussion started on one device to continue on another.
Follow-up questions can retain the context of an earlier answer, giving Siri a more conventional conversational interface for longer exchanges.
The assistant also has access to broad web knowledge for questions that cannot be answered through personal information or local device data. Apple says Siri can retrieve current information for topics ranging from sports results to travel planning and nearby businesses.
Visual Intelligence expands alongside the assistant. On iPhone, a dedicated Siri mode inside Camera can identify and respond to objects or information in front of the user. A concert poster, for example, can become the starting point for questions about performance times followed by the creation of Calendar events.
On iPad, Visual Intelligence is integrated with screenshots. Mac users can select content on their displays through a keyboard shortcut, while Vision Pro users can ask Siri about app windows or physical objects simply by looking at them.
Writing Tools are similarly integrated across the system. Siri can generate drafts, revise existing text from natural-language instructions, and provide writing suggestions. In Mail and Messages, Apple says it can take a user’s typical communication style with a particular recipient into account, including tone and punctuation patterns.
Image Credit: Apple Inc.
Siri AI runs across on-device and private cloud models
Siri AI is powered by a new generation of Apple Foundation Models developed in collaboration with Google using Gemini technology, marking a notable shift in Apple’s AI infrastructure.
The architecture divides processing between models running directly on the device and larger models operating through Private Cloud Compute. Apple says requests sent to Private Cloud Compute are processed without personal data being stored or made accessible to the company.
Core resources such as the Spotlight index and Apple’s App Toolbox can remain on-device, allowing Siri to retrieve local information and perform supported actions without sending every request to a remote server.
More capable devices can also use AFM Core Advanced, Apple’s highest-performance on-device model. It powers improvements including more expressive Siri voices and advanced systemwide dictation that automatically handles capitalization, punctuation, and formatting.
Compatibility varies by feature. Apple Intelligence supports iPhone 16 models and later, iPhone 15 Pro and Pro Max, M1 or later iPads and Macs, iPad mini with A17 Pro, Apple Vision Pro, and supported Apple Watch models when paired with a nearby Apple Intelligence-enabled iPhone.
AFM Core Advanced requires newer hardware, including iPhone Duo, the iPhone 18 Pro line, iPhone Air, iPhone 17 Pro models, qualifying M4 or later iPads with at least 12GB of unified memory, M3 or later Macs with at least 12GB, and Apple Vision Pro with M5.
Image Credit: Apple Inc.
Siri AI arrives with limits as Apple expands access
The initial Siri AI release remains explicitly labeled beta, and some of the surrounding Apple Intelligence features are scheduled for later updates.
Apple also confirms that features relying on server-side models can be subject to daily usage limits. That includes Siri AI, cloud-based photo editing, Image Playground, and AFM 3 Cloud models used through Shortcuts. Limits can vary depending on the feature, request complexity, system demand, and other factors.
Apple says expanded access to server-dependent features will eventually be available for a fee, introducing a future paid layer to parts of Apple Intelligence even as the core system remains integrated into supported devices.
Apple will also expand its intelligence capabilities on Apple Watch later in 2026. Planned Audio Intelligence features on Apple Watch Series 12 and Ultra 4 include Live Rewind, which can display text representing the previous 15 seconds of a conversation, and Siri Recap, which generates high-level summaries that can be reviewed later in the Siri app.
Those functions are designed around a hardware-isolated Secure Exclave on the S11 chip, with Apple saying raw audio is processed in isolation and immediately deleted rather than stored as recordings. Live Rewind and Siri Recap are scheduled to enter beta later in 2026, making the current Siri AI launch the beginning of a staged expansion rather than the final form of Apple’s new assistant.
Unforgetful isn’t a new productivity system to learn.
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This is designed for a small number of short-term tasks. What do you need to do today, tomorrow, this week, or this month?
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If you want tagging, folders, archives, or other ways to organize or file away tasks, this isn’t the app you’re looking for.
Unforgetful is for people who know that if they file away a task, it never gets done.
I’m an OmniFocus person. I love tagging, folders, and archives; I never want to see a notification for a to-do item. I prefer pull to push. So this is absolutely not the right tool for me. But I like the fresh thinking behind this app and how the various design choices interact to make it an opinionated tool for the right type of person.
Calendar alarms changed my life. Events without alarms don’t happen.
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Most of my Reminders interaction has always been via Siri and notifications. And that fits me very well, with three major exceptions:
If I say “Remind me to buy milk,” but I forget to specify a time (or Siri misses it), Reminders will never notify me, and I’ll never check the app, so it’ll be lost.
If I inadvertently dismiss a Reminders notification without snoozing it, Reminders will never notify me about it again, so it’ll be lost.
When I do snooze a Reminders notification, which I do a lot, the snooze options suck.
He has good solutions to these and other problems. I’m tempted to try out Unforgetful just for the purported quick capture of dictated reminders, however there’s no watch app.
Listen to Accidental Tech Podcast to hear about unfortunate limitations of EventKit. Reminders itself is interesting to me in that the (private) data model is now so rich, but I’m put off by the UI, the lack of export, and the limited support for driving it from the keyboard.
Apple has finally completed its silicon transition: macOS 27 drops all Intel-based Macs, and iPadOS 27 and watchOS 27 each leave five models by the wayside, whereas the iPhone compatibility list remains unchanged.
One of the key advantages of MacWhisper, as it utilizes the Whisper technology, is its superior accuracy in transcriptions compared to other services I have used. I was an early adopter of Rev.com and eventually switched to Otter.ai, for which I paid approximately $100/year. However, I have since canceled my subscription.
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After comparing the audio transcripts from MacWhisper and Otter, I found that while Otter’s formatting is superior, there is hardly any difference in the transcriptions. I started with the free model, which was sufficient for my needs, and eventually upgraded to the large models. Nowadays, I primarily use MacWhisper to transcribe my voice memos, which I then import into Lex.Page.
Whisper, which is made by OpenAI, has the distinct advantage of allowing you to transcribe audio in almost any language you may ever need to. For the time being, Otter can only transcribe English. The benefits of better accuracy and accurate punctuation that the service already holds over Siri hold up across other languages as well. If you’re looking to transcribe non-English audio accurately, Whisper is definitely the best option available on Mac.
By taking advantage of OpenAI’s Whisper framework, Audio Hijack can now take any audio it’s recording and generate a text transcript. While this process was possible before—see Jason’s lengthy post about his workflow—it required a lot of fiddling and several different tools to accomplish; it’s certainly a lot easier to simply drop Audio Hijack’s block into your existing session. If you record multiple sources, it can even appropriately label each one—though if you record multiple people via one input, say the other end of a Zoom call, it can’t distinguish between the various participants.
Apple’s new SpeechAnalyzer is the most accurate on-device speech engine we tested. It beat every Whisper model we ship, including Whisper Small, on both the clean and the noisy half of LibriSpeech, while running roughly three times faster than Small. And the API it replaces, SFSpeechRecognizer, came last on clean speech: behind even Whisper Tiny, a 40MB model.
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The new API cuts word error rate by 3.5 to 4x on the same audio: from 9.02% to 2.12% on clean speech, and from 16.25% to 4.56% on noisy speech. There is no accuracy trade-off to weigh; the new API wins everywhere we measured, and it produces punctuated, cased text where the legacy engine’s output is rougher.
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All five engines ran comfortably faster than real time: between roughly 12x and 40x on the M2 Pro, meaning an hour of audio transcribes in about 1.5 to 5 minutes on-device. SpeechAnalyzer was about 3x faster than Whisper Small per second of audio while beating it on accuracy.
SpeechAnalyzer’s ReportingOption.fastResults reads like a knob you’d reach for when you want to trade power for latency. That framing is what cost me the afternoon.
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If a recording matters — and in a notes app, a lost meeting is the worst thing that can happen to a user — then the container you write while recording has to be PCM in CAF. Not m4a, and not AAC-in-CAF either.
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AVAudioEngine’s inputNode silently ignores your device selection
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I wanted summarization to run on-device. Everything else in Nib’s transcription path does, the audio never leaves the machine, and it would have been a much cleaner story to tell.
But 4,096 tokens for the Foundation Models isn’t enough.
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