The Hallway Track
Apple's iOS 27 Siri, powered by Apple Intelligence, can access app entities, take actions via App Intents, and understand on-screen context.
“This year, Siri becomes more powerful in three key ways. Siri can now access your app's entities, the real meaningful content inside your app.”
Apple's latest Foundation Models are now built with Google, leveraging Gemini technology to power Apple Intelligence.
“Working together with Google and leveraging the technologies behind their Gemini family of models, we created the latest Apple Foundation models to power our Apple intelligence experiences”
Apple releases beta versions of multiple operating systems and Xcode 27.2.
Apple introduces Core AI, a suite for optimizing, converting, and deploying models including LLMs on Apple Silicon.
“It includes a Swift package for running LLMs in your app. But at its core, it's an open-source repository of models that are ready to go, including generative architectures like cutting-edge large language models.”
Apple's WWDC26 session details advanced App Intents APIs letting developers deeply integrate apps with Siri and Apple Intelligence.
“Each donation is a hint that a person took a specific action in your app's UI.”
Apple's Shortcuts now integrates more capable Apple Intelligence models with web access, transcript debugging, and persistent storage.
“The Use Model action lets you tap into the power of large language models, directly within your shortcuts.”
Apple's WWDC26 code-along shows developers how to make app content and actions available to Siri via the App Intents framework.
“This is how Siri can make everyday things effortless simply with a conversation.”
Nativ is a new macOS desktop app for running AI models locally via MLX
Apple rebuilt Apple Intelligence on Google Gemini technology to power its new Foundation Models.
“Working together with Google and leveraging the technologies behind their Gemini family of models, we created the latest Apple Foundation Models for our integrated Apple Intelligence experiences.”
Sonnet 5.5 is 5x cheaper than Fable while matching frontier-level quality
“similar intelligence keeps getting possible in smaller and smaller systems”
Shopify is returning to native app development with Swift and Kotlin.
“[...] agents can now do enough of the implementation, translation, testing, and review work that it’s no longer the deciding factor it was in 2020.”
Apple introduces View Annotations API for enhanced app interactions.
“Hey Siri, send this photo to Kevin and say, 'Rachel got us some paper to practice our folds. What color would you like?'”
Apple launches Core AI framework for on-device model inference across iOS and macOS.
Apple unveils integrated AI platform at WWDC26 with Xcode 27 agentic coding and new on-device frameworks.
“At Apple, AI isn't a layer you bolt on. It's integrated into our platforms.”
Apple opens its Foundation Models framework to Private Cloud Compute and third-party models like Gemini and Claude.
“This year, we're offering developers access to our Private Cloud Compute as well. So you'll have access to a very powerful server model, the one that actually powers our Apple Intelligence features, as well as access to third-party models like Gemini and Claude from Anthropic.”
Apple's new Core AI framework lets developers run advanced AI models entirely on-device in their apps.
“With Core AI, you can build app experiences where user's data never leaves their device.”
Apple opens its Foundation Models framework to nearly any LLM via a new open-source Language Model protocol.
“Anthropic and Google will soon extend the Foundation Models framework with Swift packages of their own, making state-of-the-art Claude and Gemini models available to all Swift developers.”
Apple opens Core AI, its on-device inference framework powering Apple Intelligence, to all developers.
“Core AI is the inference framework powering on-device Apple Intelligence. And now, it's available for you to use, bringing that same power to your app's own intelligence.”
Apple is open-sourcing the Foundation Models framework and adding cloud reasoning models plus third-party model access from Anthropic and Google.
“The Foundation Models framework, including many of the brand new APIs that we're announcing today, is going open source!”
Apple opens its Private Cloud Compute server LLM to third-party developers via the Foundation Models framework at WWDC26.
“And now, by changing just one line of code, you can switch to the new server model on PCC.”
Apple is restricting Full Disk Access in macOS, citing rising risks from autonomous AI agents
“As AI agents become increasingly capable and autonomous, the risks associated with this level of access will grow substantially.”
Apple launches zero-cost server LLM for developers via Private Cloud Compute with no API keys
“there are no token costs to you, the developer”
Qwen 3.8B runs on consumer laptops while matching frontier model performance
“if we wait a bit, we might get frontier level systems running on our laptops”
Memory harnesses for local models can solve context rot in long-horizon research agents.
“that makes this issue of dealing with context rot a priority”
Apple positions AI as fully platform-integrated, not a bolt-on layer across silicon to tools
“At Apple, AI is just not a layer that you bolt on. It's fully integrated into our platforms.”
Google launched Gemini 3.5 Live Translate, a speech-to-speech model interpreting 70+ languages in near real time, now available via API.
“Developers can now build experiences that preserve speaker's tone, pitch, and pacing, resulting in more natural-sounding experiences than voice translation apps of the past.”
Google's on-device Gemma 4 models hit 5 million AI Edge Gallery downloads within one month of launch.
“Within one month of the launch, we see more than 5 million downloads”
Google's Gemma models run entirely on-device on phones, enabling multimodal AI, agent skills, and offline use.
“And what's also important to remember is that this is running entirely on the device. So, it will work offline or in areas of low connectivity.”
Apple's Core AI lets developers run cutting-edge AI models on-device for private, offline, zero-cost inference.
“Inference happens on device so data stays private, AI features can be readily available and work offline, and there is no per inference cost to you or your users.”
Apple announced new Core AI and evaluations frameworks, foundation model updates, and open-sourced Core ML models at WWDC26.
Apple's Foundation Models framework adds a language model protocol letting developers plug in third-party inference backends.
“We've got a Google package that just went live. Anthropic released theirs this morning.”
Apple's Foundation Models framework now offers frictionless frontier-model access via Private Cloud Compute, plus agentic coding in Xcode.
“the ability to now just access one of these frontier models in Private Cloud Compute with basically no setup or friction at all”
Apple's WWDC26 Foundation Models framework adds DynamicProfile APIs and an open-source Utilities package for building agentic app experiences.
“You can think of this as swapping hats, or switching agents.”
Apple is adding an fm command-line tool and Python SDK to access on-device Foundation Models at WWDC26.
“We're introducing a new command line tool called fm, and a new Foundation Models SDK for Python.”
Apple's new Evaluations framework lets developers hill-climb and align model judges to reduce drift in AI features.
“This discrepancy between model and human is known as drift, and it is a problem faced by all developers trying to evaluate intelligent features.”
Apple's new Evaluations framework lets developers measure quality of generative-AI features powered by on-device models.
“These models break a contract that is fundamental to software testing.”
Apple's MLX now supports distributed LLM inference and training across multiple Macs via RDMA over Thunderbolt 5 and the new JACCL library.
“JACCL is an open-source collective communication library built by Apple. It leverages RDMA over Thunderbolt and gives you collective communication primitives for sending data between machines and combining results across the group”
On-device AI inference on Intel Panther Lake NPUs eliminates per-token cloud cost and latency for agentic systems.
“every token has a round trip. It has latency. It is a cost item associated with it.”
Google launches Gemma 4 open model family with four sizes from 2B to 31B parameters
“Our Gemma model, here evaluated on L M Arena, are scoring as well as model 20X the size.”
Gemma 4's per-layer embeddings boost model performance without increasing compute parameters
“It's a very nice way to increase the performance of the model without actually increasing parameters because these parameters are stored on flash storage.”