--- title: "Apple’s AI timeline: from Siri in 2011 to Siri AI and Foundation Models in 2026" description: "Every step in Apple's AI story, from Siri in 2011 to Siri AI in 2026, with an Apple source on each entry." url: https://mactoreality.com/apple-ai-timeline published: 2026-11-08T21:45:22Z updated: 2026-11-08T21:45:22Z author: "Martin" category: Guides publisher: Mac to Reality apple_heat_impact: 0 --- # Apple’s AI timeline: from Siri in 2011 to Siri AI and Foundation Models in 2026 *Every step in Apple's AI story, from Siri in 2011 to Siri AI in 2026, with an Apple source on each entry.* Apple has worked on machine learning for far longer than the phrase Apple Intelligence has existed. This timeline follows that story from Siri on the iPhone 4S in 2011 to the third generation of Apple Foundation Models and Siri AI in 2026. Every entry has a date and links to an Apple source: Newsroom, developer.apple.com, Apple Support or Apple’s Machine Learning Research site. Milestones are product and platform moments. Research entries are Apple Machine Learning Research highlights, each with a short summary written by us. You can filter by year and type, search the entries, and expand or collapse them. Every entry has its own link, so you can share a single moment. ## 2011 ### Siri launches on iPhone 4S *4 October 2011 · Milestone* Apple announces iPhone 4S with Siri, an intelligent assistant you control by asking. This is the starting point of Apple's consumer AI story. [Apple source](https://www.apple.com/newsroom/2011/10/04Apple-Launches-iPhone-4S-iOS-5-iCloud/) ## 2017 ### Core ML brings on-device machine learning to developers *5 June 2017 · Milestone* With iOS 11, Apple introduces Core ML, a framework that lets developers add machine learning to apps with all processing happening locally on the device. [Apple source](https://www.apple.com/newsroom/2017/06/ios-11-brings-new-features-to-iphone-and-ipad-this-fall/) ### Improving the Realism of Synthetic Images *7 July 2017 · Research* Apple researchers show how to make simulator-generated images look more realistic, so that models trained on cheap synthetic data generalise better to real photos. It is an early example of Apple publishing its own computer-vision work. [Apple source](https://machinelearning.apple.com/research/gan) ### Improving Neural Network Acoustic Models by Cross-bandwidth and Cross-lingual Initialization *1 August 2017 · Research* The Siri team explains how it reuses data from existing acoustic models when Siri launches in a new language or handles a different audio bandwidth, because labelled speech data is scarce for every new launch. [Apple source](https://machinelearning.apple.com/research/cross-initialization) ### Inverse Text Normalization as a Labeling Problem *2 August 2017 · Research* Explains how Siri turns spoken words into tidy written forms, so that 'October twenty third twenty sixteen' appears as 'October 23, 2016'. The team treats it as a labelling problem and uses a compact statistical model. [Apple source](https://machinelearning.apple.com/research/inverse-text-normal) ### Deep Learning for Siri’s Voice: On-device Deep Mixture Density Networks for Hybrid Unit Selection Synthesis *6 August 2017 · Research* Describes how Siri's voice moved to deep learning from iOS 10 onwards, using on-device deep mixture density networks to pick and join speech units so the voice sounds smoother and more natural. [Apple source](https://machinelearning.apple.com/research/siri-voices) ### A11 Bionic brings the Neural Engine to iPhone *12 September 2017 · Milestone* iPhone X ships with the A11 Bionic and a dual-core neural engine that Apple says performs up to 600 billion operations per second. It is built for machine-learning tasks such as Face ID. [Apple source](https://www.apple.com/newsroom/2017/09/the-future-is-here-iphone-x/) ### Real-Time Recognition of Handwritten Chinese Characters Spanning a Large Inventory of 30,000 Characters *12 September 2017 · Research* How Apple built real-time handwriting recognition for up to 30,000 Chinese characters that runs on iPhone, iPad and Apple Watch (Scribble mode), using deep learning on the device. [Apple source](https://machinelearning.apple.com/research/handwriting) ### Hey Siri: An On-device DNN-powered Voice Trigger for Apple’s Personal Assistant *1 October 2017 · Research* Apple explains how 'Hey Siri' works: a very small neural-network speech recogniser runs all the time, scores how likely it is that you said the phrase, and only then wakes the rest of Siri. [Apple source](https://machinelearning.apple.com/research/hey-siri) ### An On-device Deep Neural Network for Face Detection *16 November 2017 · Research* Apple says it began using deep learning for face detection in iOS 10. The article covers the privacy and efficiency challenges of running that network on the device and the Vision framework that opened it to developers. [Apple source](https://machinelearning.apple.com/research/face-detection) ### Learning with Privacy at Scale *6 December 2017 · Research* Sets out the architecture Apple uses to learn from usage patterns, such as typing and websites visited, with local differential privacy so that individual data does not leave the device in readable form. [Apple source](https://machinelearning.apple.com/research/learning-with-privacy-at-scale) ## 2018 ### Personalized Hey Siri *16 April 2018 · Research* Recounts that 'Hey Siri' arrived with iPhone 6 (iOS 8) and describes how Apple adapts the trigger to the person speaking, so that it responds to the owner and is less likely to wake for others. [Apple source](https://machinelearning.apple.com/research/personalized-hey-siri) ### Finding Local Destinations with Siri’s Regionally Specific Language Models for Speech Recognition *9 August 2018 · Research* Siri struggled with names of small local businesses. Apple describes adding regional knowledge to the speech-recognition language model so that local places are recognised more accurately. [Apple source](https://machinelearning.apple.com/research/regionally-specific-language-models) ### A12 Bionic gets an eight-core Neural Engine *12 September 2018 · Milestone* iPhone Xs and Xs Max launch with the first 7-nanometre smartphone chip, the A12 Bionic, with a next-generation eight-core Neural Engine. [Apple source](https://www.apple.com/newsroom/2018/09/iphone-xs-and-iphone-xs-max-bring-the-best-and-biggest-displays-to-iphone/) ### Can Global Semantic Context Improve Neural Language Models? *27 September 2018 · Research* Looks at word embeddings, the numerical maps of words behind typing, news and answers, and tests whether adding wider semantic context improves neural language models. [Apple source](https://machinelearning.apple.com/research/can-global-semantic-context-improve-neural-language-models) ### Optimizing Siri on HomePod in Far‑Field Settings *3 December 2018 · Research* HomePod hears you from across a room, with echo, reverberation and noise. Apple describes the multichannel audio processing and speech work needed to make Siri reliable in that far-field setting. [Apple source](https://machinelearning.apple.com/research/optimizing-siri-on-homepod-in-far-field-settings) ## 2019 ### Bridging the Domain Gap for Neural Models *15 June 2019 · Research* Neural networks often fail when real data differs from their training data. Apple presents a domain-adaptation method that uses task-specific decision boundaries to close that gap. [Apple source](https://machinelearning.apple.com/research/bridging-the-domain-gap-for-neural-models) ### Language Identification from Very Short Strings *24 July 2019 · Research* Explains how Apple's keyboard and language features decide which language a very short piece of text is in, which matters more as people type in several languages. [Apple source](https://machinelearning.apple.com/research/language-identification-from-very-short-strings) ## 2020 ### M1 brings the Neural Engine to the Mac *10 November 2020 · Milestone* M1 includes a 16-core Neural Engine that Apple says can perform 11 trillion operations per second, with up to 15x faster machine learning than the previous generation of Mac. [Apple source](https://www.apple.com/newsroom/2020/11/apple-unleashes-m1/) ## 2021 ### Making Mobile Applications Accessible with Machine Learning *20 May 2021 · Research* Apple describes using machine learning to make mobile apps usable for people with disabilities, for example by understanding what is on screen for people who are blind or have low vision. [Apple source](https://machinelearning.apple.com/research/mobile-applications-accessible) ### Leveraging ML Compute for Accelerated Training on Mac *8 June 2021 · Research* With M1 Macs and the ML Compute framework in macOS Big Sur, neural networks can be trained directly on the Mac. The article also points to the tensorflow-metal plug-in for GPU training. [Apple source](https://machinelearning.apple.com/research/ml-compute-training-on-mac) ### Recognizing People in Photos Through Private On-Device Machine Learning *28 July 2021 · Research* How the Photos app recognises people privately on the device: a pipeline of face and body models that powers curation, search and memories without sending the library to Apple. [Apple source](https://machinelearning.apple.com/research/recognizing-people-photos) ### Learning to Generate Radiance Fields of Indoor Scenes *12 August 2021 · Research* A research paper on learning to generate 3D radiance fields of indoor scenes, building a model of what rooms tend to look like so new viewpoints can be predicted from few observations. [Apple source](https://machinelearning.apple.com/research/learning-to-generate-radiance-fields) ### Improving Neural Network Subspaces *10 September 2021 · Research* Explores why some minima that a neural network converges to generalise better than others, and how training subspaces of networks can improve accuracy. [Apple source](https://machinelearning.apple.com/research/improving-neural-subspaces) ### On-device Panoptic Segmentation for Camera Using Transformers *19 October 2021 · Research* Describes the transformer-based model that gives the Camera app pixel-level understanding of a scene, which supports features such as Portrait mode and semantic rendering. [Apple source](https://machinelearning.apple.com/research/panoptic-segmentation) ### Interpretable Adaptive Optimization *7 December 2021 · Research* Statistical learning methods that help Apple teams measure which user experiences work best from noisy, privacy-protected feedback, including differential privacy and delayed data. [Apple source](https://machinelearning.apple.com/research/interpretable-adaptive-optimization) ## 2022 ### Modeling the Impact of User Mobility on COVID-19 Infection Rates Over Time *3 February 2022 · Research* A health-research paper that models how user mobility affected COVID-19 infection rates over time during the first phase of the pandemic. [Apple source](https://machinelearning.apple.com/research/modeling-covid-mobility) ### Deploying Transformers on the Apple Neural Engine *6 June 2022 · Research* Apple open-sources a reference PyTorch implementation of the Transformer architecture, tuned for the Apple Neural Engine, and explains how Transformers already power several Apple features. [Apple source](https://machinelearning.apple.com/research/neural-engine-transformers) ### A Multi-Task Neural Architecture for On-Device Scene Analysis *7 June 2022 · Research* Instead of one model per feature, Apple describes a single multi-task network that produces shared scene-analysis signals used for photo search and Memories. [Apple source](https://machinelearning.apple.com/research/on-device-scene-analysis) ### 3D Parametric Room Representation with RoomPlan *4 October 2022 · Research* How RoomPlan uses LiDAR and machine learning to turn a scan of a room into a parametric 3D model with walls, doors, windows and furniture. [Apple source](https://machinelearning.apple.com/research/roomplan) ## 2023 ### Improved Speech Recognition for People Who Stutter *18 May 2023 · Research* Describes work on making speech recognition perform better for people who stutter, for both voice assistants and dictation. [Apple source](https://machinelearning.apple.com/research/speech-recognition) ### Fast Class-Agnostic Salient Object Segmentation *5 June 2023 · Research* Explains the on-device network behind the 2022 feature that lifts the subject out of a photo or removes the background in Photos, Preview, Safari, Keynote and other apps. [Apple source](https://machinelearning.apple.com/research/salient-object-segmentation) ### Learning Iconic Scenes with Differential Privacy *21 July 2023 · Research* Shows how Apple uses differential privacy to learn which kinds of photos people take at popular places, used to choose key photos in Memories and Places in iOS 17, without personal data leaving the device. [Apple source](https://machinelearning.apple.com/research/scenes-differential-privacy) ### Voice Trigger System for Siri *11 August 2023 · Research* An overview of the voice-trigger system for Siri, designed to run entirely on the device with tight limits on power, memory and false triggers. [Apple source](https://machinelearning.apple.com/research/voice-trigger) ### Advancing Speech Accessibility with Personal Voice *18 December 2023 · Research* Describes Personal Voice, which lets people at risk of losing their speech, for example after an ALS diagnosis, create a synthesised voice of their own. Apple introduced it in May 2023 and shipped it in iOS 17. [Apple source](https://machinelearning.apple.com/research/personal-voice) ## 2024 ### Deploying Attention-Based Vision Transformers to Apple Neural Engine *5 January 2024 · Research* Explains how to deploy attention-based vision transformers on the Apple Neural Engine efficiently, building on the 2022 Transformers work. [Apple source](https://machinelearning.apple.com/research/vision-transformers) ### Humanizing Word Error Rate for ASR Transcript Readability and Accessibility *7 March 2024 · Research* Proposes a way to judge speech-to-text transcripts by how readable they are for people, not just by raw word error rate, motivated by Apple Podcasts transcripts and accessibility. [Apple source](https://machinelearning.apple.com/research/humanizing-wer) ### Enhancing Paragraph Generation with a Latent Language Diffusion Model *15 March 2024 · Research* Presents a latent diffusion approach to generating paragraphs of text, as an alternative to autoregressive models that can become repetitive. [Apple source](https://machinelearning.apple.com/research/latent-language-diffusion-model) ### Personalizing Health and Fitness with Hybrid Modeling *15 March 2024 · Research* A hybrid modelling approach that personalises heart-rate predictions from wearable data to a person's own context, such as activity. [Apple source](https://machinelearning.apple.com/research/personalized-heartrate) ### Apple Intelligence announced at WWDC24 *10 June 2024 · Milestone* Apple introduces Apple Intelligence, built on a roughly 3-billion-parameter on-device model and a larger server model running on Private Cloud Compute. [Apple source](https://machinelearning.apple.com/research/introducing-apple-foundation-models) ### Private Cloud Compute introduced *10 June 2024 · Milestone* Apple describes PCC as a cloud intelligence system built with custom Apple silicon and a hardened operating system for private AI processing. [Apple source](https://security.apple.com/blog/private-cloud-compute/) ### Improving How Machine Translations Handle Grammatical Gender Ambiguity *7 October 2024 · Research* Explains how the Translate app lets users choose the grammatical gender of ambiguous words when translating from English into Spanish, French or Portuguese. [Apple source](https://machinelearning.apple.com/research/gender-alternatives) ### Combining Machine Learning and Homomorphic Encryption in the Apple Ecosystem *24 October 2024 · Research* Describes how Apple combines machine learning with homomorphic encryption, for example private nearest-neighbour search for Enhanced Visual Search in Photos, to keep processing private. [Apple source](https://machinelearning.apple.com/research/homomorphic-encryption) ### First Apple Intelligence features ship *28 October 2024 · Milestone* iOS 18.1, iPadOS 18.1 and macOS Sequoia 15.1 bring the first set of Apple Intelligence features to users. [Apple source](https://www.apple.com/newsroom/2024/10/apple-intelligence-is-available-today-on-iphone-ipad-and-mac/) ### On Device Llama 3.1 with Core ML *1 November 2024 · Research* A technical walkthrough of optimising and running Llama 3.1 on Apple silicon with Core ML, for developers who want large language models on the device. [Apple source](https://machinelearning.apple.com/research/core-ml-on-device-llama) ### iOS 18.2 adds Image Playground, Genmoji, ChatGPT and visual intelligence *11 December 2024 · Milestone* Apple Intelligence gains Image Playground, Genmoji, Writing Tools enhancements, ChatGPT support in Siri and visual intelligence. It also begins language expansion with localised English for Australia, Canada, Ireland, New Zealand, South Africa and the UK. [Apple source](https://www.apple.com/newsroom/2024/12/apple-intelligence-now-features-image-playground-genmoji-and-more/) ### Accelerating LLM Inference on NVIDIA GPUs with ReDrafter *18 December 2024 · Research* Apple brings its Recurrent Drafter (ReDrafter) speculative-decoding method to NVIDIA GPUs to speed up LLM inference for production use. [Apple source](https://machinelearning.apple.com/research/redrafter-nvidia-tensorrt-llm) ## 2025 ### Controlling Language and Diffusion Models by Transporting Activations *10 April 2025 · Research* Introduces a technique to steer language and diffusion models by transporting their activations, giving finer control over outputs and helping reduce misuse. [Apple source](https://machinelearning.apple.com/research/transporting-activations) ### Understanding Aggregate Trends for Apple Intelligence Using Differential Privacy *14 April 2025 · Research* Explains how Apple uses differential privacy to understand aggregate usage trends in Apple Intelligence without seeing individual users' data. [Apple source](https://machinelearning.apple.com/research/differential-privacy-aggregate-trends) ### An LLM-Based Approach to Review Summarization on the App Store *24 April 2025 · Research* Describes the multi-step LLM system behind the review summaries on the App Store in iOS 18.4, designed to be inclusive, balanced and faithful to reviewers. [Apple source](https://machinelearning.apple.com/research/app-store-review) ### Foundation Models framework opens the on-device model to developers *9 June 2025 · Milestone* At WWDC25 Apple introduces a new generation of foundation models designed to support 15 languages, plus a framework that gives developers direct access to the on-device model. [Apple source](https://www.apple.com/newsroom/2025/06/apple-intelligence-gets-even-more-powerful-with-new-capabilities-across-apple-devices/) ### FastVLM: Efficient Vision Encoding for Vision Language Models *23 July 2025 · Research* Presents FastVLM, a vision encoder designed to make vision-language models faster. Apple later released the models, including MLX checkpoints. [Apple source](https://machinelearning.apple.com/research/fast-vision-language-models) ### The “Super Weight:” How Even a Single Parameter can Determine a Large Language Model’s Behavior *21 August 2025 · Research* Finds that a single parameter in a large language model, the 'super weight', can be essential: removing it makes the model produce gibberish. [Apple source](https://machinelearning.apple.com/research/the-super-weight) ### Live Translation arrives with AirPods Pro 3 *9 September 2025 · Milestone* AirPods Pro 3 launch with Live Translation in beta for in-person conversations, powered by computational audio and Apple Intelligence. [Apple source](https://www.apple.com/newsroom/2025/09/introducing-airpods-pro-3-the-ultimate-audio-experience/) ### Exploring LLMs with MLX and the Neural Accelerators in the M5 GPU *19 November 2025 · Research* Shows how MLX takes advantage of the Neural Accelerators in the M5 chip on recent macOS beta, to run language models faster on a Mac. [Apple source](https://machinelearning.apple.com/research/exploring-llms-mlx-m5) ## 2026 ### ParaRNN: Large-Scale Nonlinear RNNs, Trainable in Parallel *23 April 2026 · Research* ParaRNN makes recurrent neural networks trainable in parallel, which for the first time makes it practical to scale them to billions of parameters. [Apple source](https://machinelearning.apple.com/research/large-scale-rnns) ### WWDC26: next-generation Apple Intelligence and Siri AI *8 June 2026 · Milestone* Apple previews iOS 27 and its siblings with the next generation of Apple Intelligence and Siri AI, described as an entirely new version of Siri. [Apple source](https://www.apple.com/newsroom/2026/06/apple-unveils-next-generation-of-apple-intelligence-siri-ai-and-more/) ### Third-generation Apple Foundation Models *8 June 2026 · Milestone* A family of five models built in collaboration with Google: AFM 3 Core (3B dense), AFM 3 Core Advanced (20B sparse, activating 1 to 4B parameters), AFM 3 Cloud, ADM 3 Cloud (Image) and AFM 3 Cloud Pro. [Apple source](https://machinelearning.apple.com/research/introducing-third-generation-of-apple-foundation-models) ### Private Cloud Compute expands to Google Cloud *8 June 2026 · Milestone* Apple, Google and NVIDIA extend PCC to run the most demanding Apple Intelligence workloads on Google Cloud, with PCC privacy commitments kept. [Apple source](https://security.apple.com/blog/expanding-pcc/) ### Siri AI arrives in beta in English *14 September 2026 · Milestone* Apple releases the next generation of Apple Intelligence with iOS 27 and its siblings. Siri AI rolls out in beta in English, with personal context, onscreen awareness and more app actions. It is not initially available in the EU on iOS, iPadOS and watchOS. [Apple source](https://www.apple.com/newsroom/2026/09/siri-ai-a-profoundly-more-capable-and-personal-assistant-is-here/) ### Siri AI adds French, Japanese, Korean, Portuguese and Spanish *26 October 2026 · Milestone* With the 27.2 updates, Siri AI expands to five more languages. Apple says Chinese (Traditional), Norwegian, Turkish and Vietnamese will follow by the end of the year. Apple Intelligence itself supports 16 languages, including Danish, but Siri AI does not yet list Danish. [Apple source](https://www.apple.com/newsroom/2026/10/siri-ai-is-available-in-more-languages-starting-today/) ### Faster Retrieval for Better, More Efficient RAG *5 November 2026 · Research* Proposes faster maximum inner product search, the retrieval step at the core of recommendation and retrieval-augmented generation (RAG), so that large databases can be searched more cheaply. [Apple source](https://machinelearning.apple.com/research/faster-retrieval) ## How we built this We use Apple’s own pages as the only sources. The list is not complete: Apple has published more than 1,100 research papers, and we have so far included the highlights Apple chose to feature. We add entries as Apple announces them. Siri AI language support, for example, is taken from Apple Support and changes over time, so check Apple’s page for the current list.