Podcast Summary: Hands-On Mac 166 – Apple's New AI Clean Up Tool
Release Date: January 23, 2025
Host: Micah Sargent
Podcast: All TWiT.tv Shows (Audio)
Introduction
In episode 166 of Hands-On Mac, hosted by Micah Sargent, the focus is on Apple's latest artificial intelligence feature introduced in macOS Sequoia: the Cleanup tool. This innovative feature is designed to help users effortlessly remove unwanted distractions from their photos, enhancing the overall visual appeal with minimal effort.
Overview of Apple's Cleanup Tool
Micah begins by introducing the Cleanup feature within the Photos app, emphasizing its integration with Apple Intelligence. The tool leverages on-device machine learning models to identify and remove selected elements from photographs, ensuring user privacy and security by processing data locally.
"Cleanup is a feature for macOS Sequoia and for devices that support Apple Intelligence that will attempt to remove the toy." [01:48]
Demonstration and Examples
Removing Distractions from a Pet Photo
Micah demonstrates the Cleanup tool using a photo of his dog, Henry. The image initially contains a distracting toy in the background. Instead of cropping the photo, Micah opts to use Cleanup to remove the toy, aiming to keep the focus solely on Henry.
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Selection Process:
- Navigates to the Edit menu in the Photos app.
- Chooses the Cleanup option, which initiates a download of the necessary on-device model.
- Utilizes the brush tool to circle the unwanted toy.
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Result:
- The toy is successfully removed with minimal impact on the surrounding textures.
- Some minor alterations, like the slight removal of pillow folds, are noted but deemed acceptable.
"It did a pretty good job of removing the toy without making it look too much like there was an edit there." [04:10]
Attempting to Remove a Person from a Building Photo
In a more challenging scenario, Micah attempts to remove a small person from the foreground of a building photograph. The initial attempt leads to unintended alterations in the stair steps, where the tool erroneously extends lines beyond their natural termination points.
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First Attempt:
- Selects the person directly.
- Observes that the Cleanup tool improperly continues the stair steps, distorting the image.
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Second Attempt:
- Brushes more precisely around the person.
- Despite closer selection, the result remains unsatisfactory with continued inaccuracies.
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Feedback Mechanism:
- Utilizes the report feature to provide feedback on the tool's performance.
"Apple's cleanup tool is just not there yet. It is one of many features that are available as part of Apple Intelligence and some of them do a pretty good job. This one still needs some work." [10:25]
Cleaning Up a Spatial Photo
Micah explores the Cleanup tool on a spatial photo featuring himself, which includes additional objects like an iPhone and a keyboard on a table.
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Object Removal:
- Attempts to remove the iPhone and keyboard.
- Notices partial success but identifies loss of texture and incomplete removal of elements.
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Final Assessment:
- Decides to reset the Cleanup tools for the photo due to subpar results.
"It did an okay job of removing the iPhone, but you'll notice that some of the texture is lost from the table with the removal of that iPhone." [08:50]
Performance Analysis
Micah provides a balanced evaluation of the Cleanup tool, highlighting both its strengths and areas needing improvement.
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Strengths:
- Effective in simple scenarios, such as removing large distractions from a photo.
- Maintains overall image texture and quality in less complex edits.
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Weaknesses:
- Struggles with intricate details and smaller objects, leading to unnatural alterations.
- Limited by the on-device processing power, which restricts the complexity and accuracy of edits compared to server-side solutions.
"Apple's commitment to privacy and security run contrary to the tools that we see in use by other companies." [10:45]
Comparison with Other Tools
Micah contrasts Apple's Cleanup tool with Google's Magic Eraser, noting significant differences in performance due to their respective processing approaches.
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Google Magic Eraser:
- Utilizes server-side technology with substantial processing power.
- Achieves more accurate and seamless object removal, especially in complex images.
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Apple Cleanup:
- Relies on on-device models to ensure user privacy and data security.
- While promising, it currently lacks the sophistication of its competitors, resulting in less reliable outcomes.
"It gives you an idea of the difference between a company like Google, which has a fantastic magic eraser tool that relies in part on server-side technology and a lot more processing power to properly remove something from a photograph versus on-device training." [10:30]
Conclusion and Future Developments
Micah concludes that while Apple's Cleanup tool is a commendable addition to the Photos app, it is still in its nascent stages and requires further refinement. He remains optimistic about Apple's ongoing efforts to enhance the feature, anticipating improvements in future updates.
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Availability:
- Currently available on macOS Sequoia, iOS, and iPadOS devices supporting Apple Intelligence.
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User Feedback:
- Encourages users to provide feedback through email for potential feature enhancements.
"The good news is Apple is still working on these tools, working on improving them, and so hopefully we should see some improvements over time." [10:50]
Final Thoughts
The Cleanup tool exemplifies Apple's dedication to integrating artificial intelligence in user-friendly applications while upholding strong privacy and security standards. Although not yet matching the capabilities of some competing tools, its development signals a promising direction for AI-driven photo editing within the Apple ecosystem.
For listeners interested in experimenting with the Cleanup tool or providing feedback, Micah invites them to reach out via email for future discussions and feature evaluations.
This summary encapsulates the key discussions and insights shared by Micah Sargent in the episode, providing a comprehensive overview of Apple's new AI Cleanup tool, its functionalities, performance, and future potential.