Explore the power of machine learning and Apple Intelligence within apps. Discuss integrating features, share best practices, and explore the possibilities for your app here.

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Max 16k images for Image Classifier training????
I'm hitting a limit when trying to train an Image Classifier. It's at about 16k images (in line with the error info) - and it gives the error: IOSurface creation failed: e00002be parentID: 00000000 properties: { IOSurfaceAllocSize = 529984; IOSurfaceBytesPerElement = 4; IOSurfaceBytesPerRow = 1472; IOSurfaceElementHeight = 1; IOSurfaceElementWidth = 1; IOSurfaceHeight = 360; IOSurfaceName = CoreVideo; IOSurfaceOffset = 0; IOSurfacePixelFormat = 1111970369; IOSurfacePlaneComponentBitDepths = ( 8, 8, 8, 8 ); IOSurfacePlaneComponentNames = ( 4, 3, 2, 1 ); IOSurfacePlaneComponentRanges = ( 1, 1, 1, 1 ); IOSurfacePurgeWhenNotInUse = 1; IOSurfaceSubsampling = 1; IOSurfaceWidth = 360; } (likely per client IOSurface limit of 16384 reached) I feel like I was able to use more images than this before upgrading to Sonoma - but I don't have the receipts.... Is there a way around this? I have oodles of spare memory on my machine - it's using about 16gb of 64 when it crashes... code to create the model is let parameters = MLImageClassifier.ModelParameters(validation: .dataSource(validationDataSource), maxIterations: 25, augmentation: [], algorithm: .transferLearning( featureExtractor: .scenePrint(revision: 2), classifier: .logisticRegressor )) let model = try MLImageClassifier(trainingData: .labeledDirectories(at: trainingDir.url), parameters: parameters) I have also tried the same training source in CreateML, it runs through 'extracting features', and crashes at about 16k images processed. Thank you
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Apple please respond with any information (Image Playgrounds access)
Apple, I speak for the majority when I say that we are frustrated, not exactly from the fact that we are unable to access features and test them and submit feedback and etc. but because of the fact that you are not communicating. If you may, please let us know right here if this is a server bug or if it is initial strategy to rollout the generative features to a small and limited amount of people on IOS18.2 DB1 Thank you!
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Tapping Take Photo reloads Image Playground sheet on iOS
I integrated the image playground sheet in my app, however when I select Take Photo on the iOS version of my app it just reloads the sheet. After several attempts I get the below error message. This issue doesn’t occur on the macOS version of my app, where it first requests camera permission before allowing me to take the photo. I’m not sure if this is happening because I don’t request the camera permission anywhere in my app. My app doesn’t use the camera at all apart from the Take Photo feature which is part of the image playground sheet. Feedback ID: FB15591786
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iOS 18 @AssistantIntent's marked with @available crashing on older OS's
Is anyone else seeing their apps crash on iOS/macOS 17.4/14.4 and newer when building a project that simply just includes the iOS 18 @AssistantIntent Macro? The beta 4 releases still have this problem. There are no notes about this that I have seen in the beta release notes. Crash message shown in console when trying to run on 17.4, 17.5, 17.5.1, etc: dyld[21935]: Symbol not found: _$s10AppIntents15AssistantSchemaV06IntentD0VAC0E0AAWP Referenced from: <F7A1FEF0-F3B0-379C-A914-D1FB0BA7C693> /Users/jonathan/Library/Developer/CoreSimulator/Devices/CA308F47-BCA8-4429-8599-1BB1CCEAB5B6/data/Containers/Bundle/Application/D7DC8E16-90DB-406A-A521-20F18326E4A7/IntentDemo.app/IntentDemo.debug.dylib Expected in: <88E18E38-24EC-364E-94A1-E7922AD247AF> /Library/Developer/CoreSimulator/Volumes/iOS_21F79/Library/Developer/CoreSimulator/Profiles/Runtimes/iOS 17.5.simruntime/Contents/Resources/RuntimeRoot/System/Library/Frameworks/AppIntents.framework/AppIntents Obviously, the new Apple Intelligence AssistantIntents only work on the 2024 OS releases. However, even when these new App Intents are marked with @available(iOS 18, macOS 15, *), the app crashes on any earlier OS version. But it runs just fine on iOS 18 and macOS 15... I would love for me to just have done something wrong but I don’t think I have… Here is the sample project: https://github.com/JTostitos/FB14323923 Maybe it's a compiler issue thats failing to strip out the macro when building for older OS's or an Xcode issue - I have no idea. I just would like to know why its not working and how to resolve it. Thanks in advance for anyones help...
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Jul ’24
Question about Apple Intelligence
I downloaded the RC beta version on my Macbook and joined the waitlist so far I haven't received any message or any kind of notifications that I'm in but I have a question kinda silly but just want confirmation. By joining the beta and AI on my MacBook, whenever the official version is released, am I gonna have AI on my iPhone since already joined AI through my MacBook in the beta version? Kinda curious about it.
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Oct ’24
switching region from China to US, Apple Intelligence still unable to use
Originally when Apple Intelligence launched there are some T&C for using and activate this Apple Intelligence. For activating Apple Intelligence at China first of all purchased iPhone must be non-Chinese iPhone means that the iPhone aren’t purchased in China not include Hong Kong and Macau. Also if use this Chinese Apple account are also unable to activate the Apple Intelligence. To activate the Apple Intelligence, I have travel to Hong Kong and purchase iPhone 16 pro Max. To reach the requirement of activating Apple Intelligence, I’ve decided to switch my region from China to United States. I’ve started to switch my account from October 19, CST 2:00am, Shanghai time 3:00pm. Till now CST time 8:30am October 24, Shanghai Time 9:30pm I still can’t join the Apple Intelligence waitlist. I’m also upgraded my phone to iOS 18.2. I’ve contacted the Apple support using my Chinese phone number and it transferred to me Philippines Apple support team. It seems like the Philippine Apple support team doesn’t help me get anything. The Philippine Apple support team keeps saying that the beta version iOS right now in my phone has some problem on it. But when I log out this Apple ID, and changed to another Apple ID that is UK ones. I can successfully enable the Apple Intelligence. What does this say?! This shows that my Apple account has a problem on it. It doesn’t switch successfully to United States server! And the Philippine Apple support team keep asking me to restore my iPhone like crazy! I’ve told them that I have used several Apple account that is from United States and United Kingdom that can successfully enable the Apple Intelligence. But the Philippine Apple support team said that my Apple account doesn’t have any problem! Apple please solve the problem! Anyone who have facing this kind of problem please share to us!!! Cheers!
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Apple Intelligence missing Image features released in 18.2 today
I'm using an iPhone 15 Pro Max and running developer beta 18.2 released today. I've already been an 'Apple Intelligence' user and now have been able to link it with my PAID ChatGPT account. HOWEVER; I'm searching for these Image features everyone seems to be posting about and cannot find them anywhere. I'm apparently supposed to sign up for beta access to the Image features through some new Apple natively released app that was supposedly included in this build update, which I cannot find. What gives??!!
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Oct ’24
Integer arithmetic with Accelerate
Almost all the functions in Accelerate are for single precision (Float) and double precision (Double) operations. However, I stumbled upon three integer arithmetic functions which operate on Int32 values. Are there any more functions in Accelerate that operate on integer values? If not, then why aren't there more functions that work with integers?
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Oct ’24
New Vison api - CoreML - "The VNDetectorProcessOption_ScenePrints required option was not found"
I'm trying to run a coreML model. This is an image classifier generated using: let parameters = MLImageClassifier.ModelParameters(validation: .dataSource(validationDataSource), maxIterations: 25, augmentation: [], algorithm: .transferLearning( featureExtractor: .scenePrint(revision: 2), classifier: .logisticRegressor )) let model = try MLImageClassifier(trainingData: .labeledDirectories(at: trainingDir.url), parameters: parameters) I'm trying to run it with the new async Vision api let model = try MLModel(contentsOf: modelUrl) guard let modelContainer = try? CoreMLModelContainer(model: model) else { fatalError("The model is missing") } let request = CoreMLRequest(model: modelContainer) let image = NSImage(named:"testImage")! let cgImage = image.toCGImage()! let handler = ImageRequestHandler(cgImage) do { let results = try await handler.perform(request) print(results) } catch { print("Failed: \(error)") } This gives me Failed: internalError("Error Domain=com.apple.Vision Code=7 "The VNDetectorProcessOption_ScenePrints required option was not found" UserInfo={NSLocalizedDescription=The VNDetectorProcessOption_ScenePrints required option was not found}") Please help! Am I missing something?
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Oct ’24
Keras 3 and Tensorflow GPU does not have support on apple silicon
hi, I am currently running LSTM on TensorFlow. However, when i switched from keras2 to keras3. code running time has increased 10 times -- it seems there is no GPU acceleration. Here is my code: batch size = 256 optimiser = adam activation = tanh _______________________________________________ Layer (type) Output Shape Param # ============================================= input_1 (InputLayer) [(None, 7, 16)] 0 bidirectional (Bidirection (None, 7, 320) 226560 al) bidirectional_1 (Bidirecti (None, 7, 512) 1181696 onal) bidirectional_2 (Bidirecti (None, 256) 656384 onal) dense (Dense) (None, 1) 257 ============================================== Total params: 2064897 (7.88 MB) Trainable params: 2064897 (7.88 MB) Non-trainable params: 0 (0.00 Byte) ______________________________________________ This is keras 3.6.0 + tensorflow 2.17.0 + tensorflow-metal 1.1.0 training status: Training------------ Epoch 1/200 28/681 ━━━━━━━━━━━━━━━━━━━━ 8:13 756ms/step - loss: 0.5901 - mape: 338.6876 - mse: 0.8591 This is keras 2.14.0 + tensorflow 2.14.0 + tensorflow-metal 1.1.0 training status: Training------------ Epoch 1/200 681/681 [==============================] - 37s 49ms/step - loss: 3.6345 - mape: 499038.7500 - mse: 34.4148 - val_loss: 3.5452 - val_mape: 41.7964 - val_mse: 32.0133 - lr: 0.0010 Is that because keras3 has no GPU support on macos? Apart from that, if I change LSTM activation from tanh to sigmoid in keras2, it does not have GPU support as well. My system is 15.0.1 and the code was running on python3.11 I am not sure why these happen. Thanks
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Oct ’24
CreateML
I'm trying to use the Spatial model to perform Object Tracking on a .usdz file that I create. After loading the file, which I can view correctly in the console, I start the training. Initially, I notice that the disk usage on my PC increases. After several GB, the usage stops, but the training progress remains for hours at 0.00% with the message "About 8hr." How can I understand what the issue is? Has anyone else experienced the same problem? Thanks Diego
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Oct ’24
Seeking Feedback on an Idea: Real-Time Siri Running Coach for iOS
Hello everyone, I hope you’re all doing well. I’m not a developer, but I have an idea for an iOS app that I’d love to get your thoughts on. I wanted to share it here to gather feedback from this knowledgeable community and to learn from your expertise. Idea Overview: Real-Time AI Running Coach for iOS The concept is an iOS application that provides personalized, real-time running coaching by leveraging on-device data sources and Apple’s latest technologies. The app aims to offer an adaptive and motivating running experience while ensuring user privacy through on-device processing. Key Features: • Personalized Coaching: • Utilize real-time biometric data and personal insights to deliver AI-driven coaching tailored to the user’s mental and physical state. • Analyze health metrics, activity data, mood check-ins, and more to provide context-based motivational feedback. • Privacy First: • All data processing occurs on-device using Apple’s frameworks like Core ML, ensuring no personal data leaves the device. • Adaptive Motivation: • Implement Natural Language Processing to analyze user inputs like journal entries or mood check-ins. • Generate personalized coaching cues based on historical performance and mood trends. • Performance Enhancement: • Offer dynamic adjustments to pace, route, and strategy in real time to help improve running performance. • Seamless integration with Apple Watch for real-time data collection and haptic feedback. Technologies and Frameworks Involved: • HealthKit: Access health metrics such as heart rate, distance run, VO₂ max, sleep patterns, etc. • Core ML: On-device machine learning for real-time data analysis without latency. • Natural Language Processing: Analyze personal inputs for better coaching personalization. • Core Motion & Core Location: Track motion data and location services for runs. • AVFoundation & Speech: Provide real-time voice feedback and coaching cues. • SiriKit Integration: Allow users to initiate workouts and receive updates via Siri. Target Audience: • Runners of all levels seeking personalized coaching that adapts to their mental and physical states. • Users who prioritize privacy and want AI-driven insights without their data leaving the device. • Tech-savvy fitness enthusiasts who use iOS devices and Apple wearables. Questions for the Community: 1. Feasibility: Is this idea technically achievable using current iOS frameworks and technologies? 2. Data Access: Are there limitations in accessing and processing the necessary data on-device, especially regarding privacy and permissions? 3. Potential Challenges: What hurdles might developers face in creating such an app, and how could they be addressed? 4. Advice: As someone without a technical background, what steps would you recommend I take to move this idea forward? I truly appreciate any feedback or insights you can provide. I’m excited about the potential of this idea but also aware there may be complexities I’m not considering. Thank you for taking the time to read this! Best regards, Paul
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Oct ’24