Does your app store/platform support AI apps is there any difference in the submission to review process for AI apps vs non AI apps Can you share any documentation supporting the above

So, I've declared an AppIntent that indicates my app can "Open files" that conform to UTType.Image. I've got a @AssistantEntity(schema: .files.file) and a @AssistantIntent(schema: .files.openFile) declared. So I navigate to the files app, quicklook an image, and open type-to-siri. I tell siri "open this in " and all it does is act like "open ". No breakpoint is hit in my intent's perform method. Am I doing something wrong? How can I test these cross-app behaviors? Are they... not actually possible? Does an "OpenIntent" only work on my app's own URLs and not on file URLs from other apps?

I have seen a lot of tutorials on pytorchvision models being able to be converted to coreml models but I have not been able to google or find any tutorials for torchaudio models. Is converting to a torchaudio to coreml model even possible? Does anybody have links that show how to do it?

Trying to get on the waitlist for the above and the computer is saying: “Apple Intelligence is not available when Mac is set to English (Singapore)”. When just a few more bullet points below my Language selection shows “English (United States)”. That’s the only thing I can see, of course you guys are the experts. I would like to be part of this AI experiment/experience. Thanks for any help you can give to this 35+ year Mac user. Lee W

On 25 Oct I I updated and Requested Early access for Image Playground feature, Still its got stuck on the same for 10 days, Now new 18.2 beta 2 is available still am not get access for 1 version Old feature

I recently upgraded my Ipad(M4) pro to ios18.1 and the apple intelligence waitlist option popped up. I‘ve been trying to click join waitlist but nothing happens and the apple intellignece pop up menu just dissapears each time I clicked join waitlist. I made sure my region is in the States.

I’ve had the beta and been signed up since October 23rd. Still sitting on early access requested. It’s a 16PM. My son has my old 15PM he downloaded the 18.2 beta 4 days ago and requested access and he already has it. So is it a lottery system or only certain phone models at a given time? Anyone else have the same issue? Thanks in advance, Jeremy

What are the major differences in review process for AI based apps vis a vis normal apps for Apple store?

I've been eagerly awaiting access to the Playground app since its launch day. Is anyone else still stuck on the waitlist?

I recently updated my iPhone to iOS 14.2 and the playground app came and then I couldn't open it because I hadn't released it yet. Today it released it and I rediled the notification but I went to look for it to test it and I couldn't find it anymore. How do I make the PLAYGROUND app come back from Apple smart. Como faço para baixar novamente o app?

I have requested early access for more than 10 days why still haven’t get access to it? Is there any problem on the system? Why granting access to Image playground take so long?

I have an existing photo generation app that i was looking to switch to this new api, to create specific images. How are people finding it to develop with in terms of ease of implementation?

Am I the only one still waiting for the waitlist? I enrolled 2 days after the release but I didn’t think it would take this long and seems like everyone else is getting in but me

On the October 10/28 release day of Apple Intelligence I opted in. My iPhone and iPad immediately went to "waitlist" and within 2 to 3 hours were ready to initialize Apple Intelligence. My MacBook Pro 14" with M3 Pro processor and 18 GB or RAM has been stuck on "preparing" since release day (6 days now). I've tried numerous workarounds that I found on forums as well as talking to Apple support, who basically had me repeat the workarounds that I found on forums. I've tried changing region to an area that does not have Apple Intelligence and then back to the US, I've changed Siri language to an unsupported one and back to a supported one, and I have tried disabling background/startup Apps, I've disabled and reenabled Siri. Oh, I've restarted a bunch and let the Mac alone for hours at a time. I've noticed that my selected Siri voice seems to not download. Finally, after several chats and calls with Apple support, I was told that it's Beta software, they can't help me, and I should try the developer forums.... so here I am. Any advice?

I’ve found that I can’t generate any faces of people in playground (and in genmoji, to a lesser extent) that aren’t smiling with the biggest Tiger Woods/Diddy teeth. It’s annoying. Even when you expressly ask for frowns, or angry faces, you get these big goofy smiles. Any help would be much appreciated.

So recently i updated from 18.1 to 18.2 beta on 15 pro max. I lost my access to apple intelligence. I was excited to see the use the image playground in 18.2 update but it need apple intelligence to use that app but it went back to older siri version. what are tye solutions now because i do not have any access to apple intelligence even though i have ios 18.2?

I downloaded iOS 18.2 the day it came out and requested early access for Image Playground, but it's been more than a week and the early access request has still not been accepted. I've seen some people get accepted within a day. This problem is starting to get annoying.

I downloaded IOS 18.2 dev beta to try out some of the features, on my iPhone 15 Pro, iOS 18.1’s features took about 3 hours, but this one, ITS BEEN 8 DAYS. 8 DAYS APPLE. STILL. NO. NEW. FEATURES!

Hello All, I'm developing a machine learning model for image classification, which requires managing an exceptionally large dataset comprising over 18,000 classes. I've encountered several hurdles while using Create ML, and I would appreciate any insights or advice from those who have faced similar challenges. Current Issues: Create ML Failures with Large Datasets: When using Create ML, the process often fails with errors such as "Failed to create CVPixelBufferPool." This issue appears when handling particularly large volumes of data. Custom Implementation Struggles: To bypass some of the limitations of Create ML, I've developed a custom solution leveraging the MLImageClassifier within the CreateML framework in my own SwiftUI MacOS app. Initially I had similar errors as I did in Create ML, but I discovered I could move beyond the "extracting features" stage without crashing by employing a workaround: using a timer to cancel and restart the job every 30 seconds. This method is the only way I've been able to finish the extraction phase, even with large datasets, but it causes many errors in the console if I allow it to run too long. Lack of Progress Reporting: Using MLJob<MLImageClassifier>, I've noticed that progress reporting stalls after the feature extraction phase. Although system resources indicate activity, there is no programmatic feedback on what is occurring. Things I've Tried: Data Validation: Ensured that all images in the dataset are valid and non-corrupted, which helps prevent unnecessary issues from faulty data. Custom Implementation with CreateML Framework: Developed a custom solution using the MLImageClassifier within the CreateML framework to gain more control over the training process. Timer-Based Workaround: Employed a workaround using a timer to cancel and restart the job every 30 seconds to move past the "extracting features" phase, allowing progress even with larger datasets. Monitoring System Resources: Observed ongoing system resource usage when process feedback stalled, confirming background processing activity despite the lack of progress reporting. Subset Testing: Successfully created and tested a model on a subset of the data, which validated the approach worked for smaller datasets and could produce a functioning model. Router Model Concept: Considered training multiple models for different subsets of data and implementing a "router" model to decide which specialized model to utilize based on input characteristics. What I Need Help With: Handling Large Datasets: I'm seeking strategies or best practices for effectively utilizing Create ML with large datasets. Any guidance on memory management or alternative methodologies would be immensely helpful. Improving Progress Reporting: I'm looking for ways to obtain more consistent and programmatic progress updates during the training and testing phases. I'm working on a Mac M1 Pro w/ 32GB RAM, with Apple Silicon and am fully integrated within the Apple ecosystem. I am very grateful for any advice or experiences you could share to help overcome these challenges. Thank you! I've pasted the relevant code below: func go() { if self.trainingSession == nil { self.trainingSession = createTrainingSession() } if self.startTime == nil { self.startTime = Date() } job = try! MLImageClassifier.resume(self.trainingSession) job.phase .receive(on: RunLoop.main) .sink { phase in self.phase = phase } .store(in: &cancellables) job.checkpoints .receive(on: RunLoop.main) .sink { checkpoint in self.state = "\(checkpoint)\n\(self.job.progress)" self.progress = self.job.progress.fractionCompleted + 0.2 self.updateTimeEstimates() } .store(in: &cancellables) job.result .receive(on: DispatchQueue.main) .sink(receiveCompletion: { completion in switch completion { case .failure(let error): print("Training Failed: \(error.localizedDescription)") case .finished: print("🎉🎉🎉🎉 TRAINING SESSION FINISHED!!!!") self.trainingFinished = true } }, receiveValue: { classifier in Task { await self.saveModel(classifier) } }) .store(in: &cancellables) } private func createTrainingSession() -> MLTrainingSession<MLImageClassifier> { do { print("Initializing training Data...") let trainingData: MLImageClassifier.DataSource = .labeledDirectories(at: trainingDataURL) let modelParameters = MLImageClassifier.ModelParameters( validation: .split(strategy: .automatic), augmentation: self.augmentations, algorithm: .transferLearning( featureExtractor: .scenePrint(revision: 2), classifier: .logisticRegressor ) ) let sessionParameters = MLTrainingSessionParameters( sessionDirectory: self.sessionDirectoryURL, reportInterval: 1, checkpointInterval: 100, iterations: self.numberOfIterations ) print("Initializing training session...") let trainingSession: MLTrainingSession<MLImageClassifier> if FileManager.default.fileExists(atPath: self.sessionDirectoryURL.path) && isSessionCreated(atPath: self.sessionDirectoryURL.path()) { do { trainingSession = try MLImageClassifier.restoreTrainingSession(sessionParameters: sessionParameters) } catch { print("error resuming, exiting.... \(error.localizedDescription)") fatalError() } } else { trainingSession = try MLImageClassifier.makeTrainingSession( trainingData: trainingData, parameters: modelParameters, sessionParameters: sessionParameters ) } return trainingSession } catch { print("Failed to initialize training session: \(error.localizedDescription)") fatalError() } }

Hello Guys does anybody know how long this request need to get approved? I am waiting now since beta 1 of 18.2 is out