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Adobe’s new Firefly Image 3 adds genAI features to Photoshop
At its Adobe Max event in London, Adobe on Tuesday unveiled its latest Firefly Image generative AI (genAI) model, promising greater realism and improved controls over generated outputs. The next-generation Firefly model will also be integrated into Photoshop, with several new features coming to the image editor later this year.
Adobe Firefly is a set of generative AI models used to create and modify content such as photographic style images, illustrations, and fonts. (A Firefly video-generation model is coming to the Premier Pro video editing tool later this year, with a music-generation algorithm also in the works.) It’s accessible as a standalone app, as well as being integrated into Adobe’s Creative Cloud application suite.
More than a year since launch, Firefly’s Image model is now on its third iteration. Firefly Image 3 improves on the second iteration, which launched at last October, in several ways, said Adobe.
The company highlighted improvements to image quality, particularly for images that feature people. That means more photo-realistic outputs, better lighting and subject positioning, and a wider variety of expressions. Another quality improvement is involves rendering straight lines and structures that help with image coherence.
Adobe Firefly generated image of an artist in studio.
Adobe
The latest model includes the Structure Reference feature that Adobe announced last month; it lets users apply the structure of a reference image to provide more accurate outputs. The same goes for Style Reference, which helps create a consistent image style.
Users can also expect a broader range of output styles for illustrations, photographic art, and vector art for iconography. Firefly Image 3 will have a better understanding of user prompts, too, Adobe said, more accurately reflecting longer and more complex inputs than the previous versions.
“Firefly Image 3 is a considerable level up from the already high-performing Firefly Image 2 model,” said Matt Arcaro, IDC research director for computer vision and AI, with notable improvements to image quality and coherence with user prompts.
Firefly Image 3 also gives users greater control over images produce by the AI model, said Liz Miller, vice president and principal analyst at Constellation Research. “If Firefly Image 1 and 2 focused on the ability to generate, Firefly Image 3 is about focusing and controlling generative AI models to extract the idea in a creator’s mind onto the initial canvas,” she said.
Adobe is one of numerous tech firms that offer genAI image models, including Canva, Midjourney, OpenAI, Stability AI, and others. IDC predicts that global spending on genAI tools (including software and infrastructure) will reach $143 billion in 2027, up from $16 billion in 2023.
“Firefly Image 3 may be in beta, but feels less experimental compared to some of Adobe’s rivals,” said Miller. The latest Firefly model is more photo realistic and addresses some of the problems creators have experienced with generative AI tools around structure, she said – producing images of arms with two hands, for instance.
Firefly Image 3 is available now in beta via the Firefly web app.
New Firefly features in PhotoshopAnother strong point for Adobe’s generative AI capabilities is integration across its products, said Arcaro. “Adobe is all-in on bringing genAI capabilities to users across its product portfolio,” he said.
Adobe said the Firefly Image model and new genAI features will arrive for Photoshop later this year, building on Generative Fill (the mostly quickly adopted feature in ever in Photoshop, according to Adobe) and the Generative Expand tools added to Photoshop a year ago.
The idea is to improve workflow when accessing genAI features in Photoshop.
For example, Reference Image lets users tailor Generative Fill images to a particular style by uploading a reference document. This lets users guide the Firefly’s outputs more accurately and saves time typing out text prompts to create a desired image.
Adobe Firefly makes it easier to manipulate and use reference images with genAI.
Adobe
Another feature, Generate Image, lets users create entire images from scratch in Photoshop documents using text prompts. The intention is to make the image editor more accessible to users of any skill level, said Adobe. The Generate Image tool provides options for content type, effects, and allows users to upload a reference image.
Generate Background makes it easier to replace or create background visuals in an image using natural language prompts. While it’s already possible to generate background images in Photoshop, the new feature is more streamlined and requires fewer clicks, Adobe said.
Generate Background allows users to create background visuals using natural language prompts.
Adobe
Generate Similar provides variations of objects within an image from which users can select, such as the amount or type of fruit in a fruit bowl, allowing for greater fine tuning of results.
Generate Similar using Firefly offers variations of objects within an image.
Adobe
Finally, Enhance Detail lets users increase the sharpness and clarity of generated images.
The features are available in the beta Photoshop app — a separate application that showcases new capabilities — before general availabilty later this year, said Adobe. It will be possible to run the AI processing either on Adobe’s servers or locally on a user’s device, with cloud computation the default.
“These tools are all about efficiency and shifting monotonous work off a creator’s plate,” said Miller. Getting from a brief to a sketch to a draft can be a painful, time-consuming, and costly process, she said.
“The traditional pace of creation takes a toll, especially when the language of creativity can get lost in translation…,” Miller said. “With these tools native in Photoshop, creators can ideate and iterate quickly, collaborating on color tones, shape and structure in a rapid flow.”
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Enterprises want AI PCs, just not yet
While the employee benefits of the AI PC are intriguing, they may not be enough to convince IT buyers to go all in just yet, according to a Forrester report.
Despite the enthusiasm generated by PC vendors and chipmakers at the 2024 Consumer Electronics Show, where advanced AI-driven functionalities were prominently featured, enterprises are expected to adopt a more measured approach over the next year, Forrester said in the report.
The Promise of AI PCsAI PCs are designed to enhance enterprise users’ productivity, cost efficiency, and security. By processing sophisticated AI applications locally, these PCs reduce reliance on costly and often slower cloud services. This could be especially beneficial in sectors such as finance and healthcare, where operations heavily depend on data processing and where data privacy and security are of the utmost importance.
The ability to process data locally on an AI PC minimizes the risk of breaches and helps enterprises comply with stringent regulatory requirements.
Challenges in adoptionDespite the benefits, the adoption of AI PCs among enterprises is fraught with challenges. “CIOs face several barriers when considering AI-powered PCs, including the high costs, difficulty in demonstrating how user benefits translate into business outcomes, and the availability of AI chips and device compatibility issues,” said Andrew Hewitt, Principal Analyst at Forrester Research.
CIOs feel they are struggling to show a return on investment in AI PCs. Limited business use cases for enterprises make it challenging to justify the use of these powerful machines, which are mostly restricted to niches like “gaming or content creation,” said Abhishek Gupta, Dish TV’s CIO.
“AI PCs are still very new with only a handful of options available across brands and at a premium price. The higher prices of AI PCs along with lack of enough use cases, is stopping CIOs from the adoption of AI PCs,” Gupta said.
“Businesses should look beyond impressive hardware specifications—they need genuine, measurable returns on investment,” said Ankush Sabharwal, CEO of CoRover.ai, a human-centric conversational and generative AI platform. “There is no denying that AI platforms are advancing rapidly, and this progress is paving the way for practical, problem-solving AI applications that go beyond mere gimmicks. We already have the necessary technology; the focus now should be on developing AI applications that are tailored for specific devices and industries rather than adopting generic, one-size-fits-all solutions.”
Future projections and enterprise readinessEnterprise readiness to adopt AI PCs often coincides with major OS updates to avoid compatibility issues. Forrester’s 2023 data shows that over half of infrastructure hardware technology decision-makers report that 50% or fewer of the company-issued PCs run on Windows 11. This suggests a broader hesitation towards rapid technological upgrades.
Windows 10’s anticipated end-of-life in October 2025 is expected to coincide with the increased adoption of AI PCs. “Enterprises will likely align their hardware upgrades with the new capabilities offered by the latest operating systems, which will be optimized for NPU technology,” Hewitt said.
Hewitt has predicted a tripling of AI platform budgets in 2024 to accommodate the burgeoning demand for AI applications. This budget expansion is anticipated to catalyze the adoption of AI PCs, especially as enterprise workloads continue to depend on cloud services, which are expected to become more costly. This presents a compelling case for the increased use of AI PCs in digital workplaces.
The next 18 months are crucial for AI PCs, according to CoRover.ai’s Sabharwal. “Instead of just purchasing hardware, shifting the focus towards utilizing AI to address industry-specific challenges is essential. For instance, Small LLMs can be trained to operate efficiently on AI PCs. Startups, particularly cloud-native ones, are the pioneers in adopting this technology. “As chip technology progresses and costs decrease, we anticipate a tipping point where investing in AI-based PCs will become justified.”
Upcoming chipsets with higher processing capabilities will drive further interest in AI PCs across data-intensive sectors such as manufacturing and high-tech, Hewitt said. “Industries that blend creative work with data science are prime candidates for early adoption,” he noted.
Impact on cloud servicesAs AI PC adoption potentially reduces reliance on cloud computing, cloud providers may have to adjust their pricing models. Hewitt suggests a likely shift towards a hybrid model where some processing will continue in the cloud while other tasks move to local AI PCs. This adjustment would balance cost concerns with enhanced security and privacy benefits.
Despite the potential and capabilities demonstrated by AI PCs, 2024 is shaping up to be a year of gradual exploration and tentative adoption by enterprises. As AI technology continues to evolve and more tailored applications become available, the pace of adoption is expected to accelerate, making AI PCs an integral part of enterprise technology ecosystems in the near future. This cautious but steady approach reflects the enterprise’s strategic planning in integrating cutting-edge technologies into its operations.
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