Photos’ Extend tool in iOS 27 can expand your images


Apple Intelligence is once again helping photographers add to their images in Photos for iOS 27. So long as you’re fine with it guessing what you didn’t include in the original shot.

The Photos app has been the beneficiary of a number of generative AI-based tools that use Apple Intelligence. All to try and make your photographs look great.

It all started with Clean Up, which let you eliminate unwanted and unsightly elements from your images, and then intelligently fill in the missing pixels. This is also part of Spatial Reframe, which adds elements when you move the camera and show things that were not originally caught.

In another new AI-based tool, Extend, Apple uses the same concept but thinks bigger. It’s now generating elements that are outside of the frame.

Extending the crop

Editors working on images have a few choices when it comes to changing the composition of the shot. At its most basic level, this can be a simple crop of the image.

That is, lopping off edges from the shot so that a smaller part of the overall frame occupies more of the finished picture. Think of trimming the side of a photograph to get a thumb or an annoying bit of the photo off-frame.

Three smartphone screens show a photo editing app expanding a photo of a black cat peeking from behind a red curtain, gradually filling blank space with generated background.

Extending an image in Photos for iOS 27

However, if you felt that the image needed to be wider than what you actually shot, it’s a different type of problem. You could create a composite, using imagery from elsewhere to fill in the newly created and blank space.

Extend in Photos is the same concept. It’s just that it comes up with the imagery that fills that blank space.

Apple Intelligence looks at the surrounding pixels and the rest of the image to determine what goes into the empty space. It then creates its best guess and fills the void, using its knowledge base.

Educated AI guesses

The main point of extending the frame is to create something aesthetically pleasing to the user. It has to work out what could be there and create some form of realistic element to fit into the space that could plausibly exist.

This is not the same as generating pixels showing something that does actually exist in that space. Without looking at other reference material, no AI will be able to accomplish that without a high amount of luck.

Handily, most people who would use this will look for generations that are good enough to work. Not necessarily absolute reality.

Black cat peeking through a gap between pink curtains from outside a window, green plants and dried flowers on the windowsill, soft daylight illuminating the scene

Original shot [left], AI-extended version [right]

In a test image of a cat on a windowsill, it neatly created an extra curtain to one side, more dead plants to the other. It even made more window above the cat’s head, complete with condensation.

However, I know full well that the painted window frame on the left of the shot is completely incorrect. It should be plastic frames, but instead, it’s deteriorating painted wood.

This certainly doesn’t mean the resulting expansion of the image is ugly. Far from it.

Nighttime city street with cars and motorcycles, bright streetlights, a glowing blue-lit stone wall in the background, traffic signs, and tiled sidewalk in the foreground

Late night in Cardiff original [left] and expansion [right]. Note the left pole’s position and odd-shaped sign.

Another shot of a street corner and a castle late at night is decently enlarged too. Bollards, poles, and other traffic are all generated well, and most of it fits the scene.

That said, a visible back of a road sign seems off, in part because it seems like a slightly incorrect shape. The pole’s placement also doesn’t quite line up with the road layout either.

Wide marble staircase in a modern building, flanked by glass and white walls, with metal railings and a dark vertical sign glowing at the top landing

The original shot in an Apple Store in Rome [left], the extended version [middle], and a real shot of what’s actually in the expanded bit [right]

A shot of a real Apple Store staircase in Rome was used to try and compare the AI’s guesswork with reality. The resulting expansion simply added more stairs and glass to the shot, which again looked appropriate.

In reality, there were doors and no extra steps, but Photos didn’t know about that.

Hallucinations are possible

Don’t misunderstand the testing here. We are more interested in Extend coming up with a plausible way to add extra scenery and objects to a photograph.

Plausible and looking good without errors is the game here. And overall, it does quite well.

But even so, it is still susceptible to the occasional misstep.

Two airport ground crew in orange uniforms walk on the tarmac near a white van, baggage carts, and terminal buildings with jet bridges under a clear blue sky

An airport in Rome [left], and the generated expansion [right]. Note the floating truck…

In one shot of an airport in Rome, the initial result seems plausible. The buildings extend sensibly into the background, and at first glance, everything seems plausible.

That is, until you check out the yellow and red vehicle on the right-hand side. It appears that the AI decided that the weird tire and metal siding of something was an oddly short truck.

It would’ve been a good guess, had it not been rendered to be floating about a foot off the ground.

Airport service vehicles on a tarmac, including small yellow and red tow trucks and equipment carts, with safety barriers, gas cylinders, and industrial buildings in the sunny background

A close-up of the generated truck [left], and the real-world vehicle that was actually there [right]

Searching for other shots from the time reveals it is a movable conveyor used to load luggage on and off aircraft.

To be fair to it, the original image only had a small section of a vehicle showing, and it does look like the back of a truck if you ignore the shadows. It does have to generate based on what information it has available, no matter how small the item fragment is.

This does mean that, if you have unusual elements sticking in from the sides of your original shot, you may want to fix that first. You could use Clean Up to get rid of the oddity before extending the frame, otherwise you’re leaving it all up to chance.

Overall, Extend is a logical continuation of the generative AI tool that Apple had before, and one that works reasonably well.

It has the potential to go wrong, just like the nightmare fuel generated by Spatial Reframe if you’re not careful. So long as you aren’t expecting perfect reality and just want the elements to be “good enough,” then Extend is up to the task.



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ZDNET’s key takeaways

  • Staff who use AI can end up with more to do, not less.
  • Think carefully about the tools you’re using and why.
  • Adopt a set of standards and refine your outputs.

The promise of productivity boosts from AI can come with an unwelcome side order of stress. Harvard Business Review found that AI doesn’t reduce work; it intensifies it, leading to cognitive fatigue and unsustainable hours.

While the common perception is that AI can help reduce workloads, allowing employees to focus more on higher-value and more engaging tasks, HBR’s research found that staff using AI worked more quickly and often ended up with more to do, not less.

Also: Forget productivity: Here are 5 strategic shifts that drive real AI value

While we’ve written about how some professionals are finding ways to turn AI’s time-saving magic into a productivity superpower, we’ve also recognized that some employees have started to become tired with the low quality of AI outputs.

Ankur Anand, group CIO at tech recruiter Harvey Nash, said professionals who want to avoid cognitive fatigue must understand how to use AI effectively and its potential risks.

“That focus will help to reduce the noise around the workload that AI creates,” he told ZDNET, suggesting that many people have unrealistic expectations about the productivity boost that AI will provide.

Also: Why I ditched Copilot for Claude in Word, Excel, and PowerPoint – and how you can, too

“Many organizations are telling their people, ‘We want to understand how you’re making an impact with AI,'” he said. “But these professionals are not empowered, which means that using AI adds a lot of pressure, because they need to prove themselves on their own terms.”

If you’re going to make the most of AI at work, then you’re going to have to find an effective balance between completing tasks quickly and producing high-quality work. 

Here’s how the experts believe professionals can ensure they reap the benefits, not the problems, of AI — and they suggest that you’ll need to focus on three core areas: tools, guidelines, and outputs.

Limit your toolset

Alex Read, senior enterprise product manager for data at energy provider EDF UK, told ZDNET that the best way for professionals to reap the benefits, not the challenges, of AI is to be uber-focused on tools that help you produce value in your roles.

While there are thousands of potential AI-enabled services on the market, Read said sensible professionals limit their horizons.

Also: How this travel company’s AI rollout drove a 73% satisfaction boost: A 5-step playbook for your business

In his own role, for example, Read focuses on how AI can help him build a data platform and update information accurately, efficiently, and productively: “Anything outside of that scope is noise for me.”

That sentiment resonated with Nick Pearson, CIO at technology specialist Ricoh Europe, who told ZDNET it’s important to take a step back and think carefully about how an AI tool can help you produce value in your role.

“If you think about the phrase ‘gen AI,’ the tech is very good, by definition, at generating outputs,” he said. “I could go to bed in the evening, set the model to work, and we could have four new IT strategies produced overnight.”

Also: Worried AI agents will replace you? 5 ways you can turn anxiety into action at work

However, quantity doesn’t necessarily mean quality. Pearson suggested it’s important to focus on AI’s blind spots, particularly as most models are trained on preexisting content.

“AI can’t inspire people, per se; it can’t naturally create something new, because it’s actually quite recursive,” he said.

“And the judgment you have to put in sometimes, on top of everything else, whether it be an ethical or a capability judgment, is not there automatically in the technology.”

It’s in this gap, said Pearson, that human experts play a critical role: “We’re toying with that concern as an organization and saying, ‘Where does AI really play an important role, versus where are we upskilling people in areas that AI probably won’t play for a long time?'”

Work to the guidelines

HBR’s research found that an initial productivity surge when AI is adopted can lead to lower-quality work, turnover, and other problems as people work harder rather than smarter.

To correct this issue, HBR said companies need to adopt an “AI practice,” or a set of norms and standards around AI use that help professionals ensure they use AI in a constrained but productive manner.

Also: 90% of AI projects fail – here are 3 ways to ensure yours doesn’t

At EDF UK, Read is part of an internal AI Center of Excellence in enterprise IT, which enables policy for the effective use of AI across the wider organization. 

In addition to Read, who contributes input from a data-use perspective, the group includes other tech representatives, such as the firm’s senior manager of AI, principal software engineer, and principal solution architect.

“The remit of this center is to make sure that, when the federated business units are looking to build, develop, and deploy AI services, they have platforms, guidance, best practices, architectural assets, and materials to guide them on how to safely and efficiently adopt AI and operationalize it at scale,” he said.

Some of the key themes the center considers when assessing AI tools are scalability and reusability, ensuring a proposed service doesn’t replicate one already in use.

Also: 5 ways to use AI when your budget is tight

“All new tools and services related to AI will go through that hopper and funnel to understand scope and ensure the security, regulatory, and ethical side of things are understood,” he said, suggesting that all professionals should use their organization’s pre-existing guidelines to foster an appropriate exploitation of emerging tech.

“The benefit that guided approach brings is that it allows us to be clear in our messaging around what AI services can be used, how they’re used from a use-case perspective, and ultimately, what personas are allowed to use them.”

Refine your outputs

Even when tools are assessed and considered acceptable, there can still be an overreliance on AI outputs. Worse, some professionals can drown in the insights they receive, leading to higher stress and fewer benefits.

Louise Newbury-Smith, head of UK&I at technology specialist Zoom, told ZDNET that one way to ensure your outputs are constrained is to focus on prompting.

“Use simple amendments to be specific, such as ‘Give me the top three things with the biggest impact.’ That approach should guide your prompt, rather than saying, ‘Give me everything you know about this topic.'”

Also: 5 ways to fortify your network against the new speed of AI attacks

Newbury-Smith said the successful use of AI is all about being smart about how it’s exploited, and that effectiveness comes down to enablement and engagement. If a prompt yields too much information, refine it until you get what you need. She said this should still be faster than trying to get answers without AI.

The basic message for professionals is that effective applications of AI are all about you staying in the loop, said Bernhard Seiser, vice president of digital, data, and IT at AOP Health.

Think before you use AI, and think again before you push your outputs around the organization.

“It doesn’t help the business if you get AI-generated emails that are many pages long, and then you need ChatGPT to summarize the text,” he told ZDNET.

Seiser said that while there are certain tasks generative AI is good at and worth using for, in the end, “you need to use your brain.”





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