According to a recent blog post from Adobe, the company is deeply invested in how agentic AI will transform creative processes. Ely Greenfield, CTO of Adobe’s Digital Media business, emphasized that the goal of this new AI technology is not to replace human creativity but to augment it. This emerging technology is set to enable users, from beginners to seasoned professionals, to work more efficiently by reducing the time spent on repetitive tasks.

For novice users of software like Adobe Express and Photoshop, the AI will streamline access to essential editing tools and templates, facilitating a more intuitive editing experience. Advanced users will benefit from the AI’s ability to minimize time-consuming processes, allowing them to focus on more significant creative elements of their projects. This functionality is highlighted in Greenfield’s statement that AI agents will make it easier for users to navigate through numerous editing options.

One of the standout features of this forthcoming AI integration will be its capability to analyze images in real-time. As Greenfield points out, imagine Photoshop suggesting edits to enhance images, and then performing those actions at the user’s command with a single click. The implications of such functionalities are vast and could potentially change the way photographers and editors approach their craft.

In fact, Adobe has already laid the groundwork for these agent-driven workflows in Photoshop. A prime example is the introduction of the “Distraction Removal” feature, which automatically identifies and removes unwanted elements like power lines or people from backgrounds, streamlining the editing process further than manual operations would allow.

Later this month, during Adobe MAX London, the company will showcase its agentic AI capabilities further, revealing a new Actions panel in Photoshop that can suggest and execute context-aware edits. This will allow photographers to improve aspects of their images, such as enhancing skies or adjusting lighting with just a click. Additionally, users will be able to employ natural language commands to engage with over a thousand one-click actions within Photoshop, making the software even more accessible and user-friendly.

Adobe’s vision for agentic AI extends beyond simply making the editing process faster. The company believes that this technology has the potential to serve as a powerful educational tool, aiding users in mastering Photoshop through just-in-time learning. Not everyone has the time or resources to undergo extensive training in complex software, and the educational angle of agentic AI represents a major development in making these tools more accessible.

In Premiere Pro, Adobe has already launched the Media Intelligence feature, which represents early efforts in integrating AI capabilities. This technology automates video content analysis and enables natural language searching within the software, potentially changing the way editors manage and piece together segments of video footage. Greenfield emphasizes that while AI cannot replace human insight and creativity entirely, it can provide a vital assistive role, easing the burden of finding and organizing substantial amounts of visual content.

As Adobe gears up to unveil this revolutionary AI technology, it asserts that agentic AI will function as a force multiplier for creative industries. The company is eager to share more information at the upcoming event, keeping the art of photo and video editing at the forefront of innovation. The integration of such technology reflects broader trends within the industry, highlighting the essential need for tools that not only enhance user capabilities but also make the creative process more enjoyable and less intrusive.

In conclusion, Adobe’s commitment to developing agentic AI positions the company not just as a software provider but as a leader in the field of creative technology. As this technology progresses, it has the potential to significantly alter workflows and improve productivity for creative professionals. Users eagerly anticipate the details set to be revealed at Adobe MAX, as they consider the possibilities that this transformative technology holds for their future projects.

This transformation in consumer behavior comes as users increasingly turn to AI chatbots for their search needs, abandoning Google’s familiar format of “ten blue links”. Adobe’s analysis incorporated data from over 1 trillion visits to U.S. retail websites, alongside a survey capturing responses from over 5,000 U.S. consumers. The results suggest not only an uptick in referral traffic but also a marked improvement in user engagement metrics. Individuals redirected from AI platforms linger on retail sites 8 percent longer, engage with 12 percent more pages, and demonstrate a 23 percent decrease in bounce rates compared to traditional search sources, indicating that AI could potentially enhance the online shopping experience.

Despite this promising transition, the rollout of generative AI search tools has faced challenges. Google’s early attempts, including its Search Generative Experience, generated mixed feedback, displaying instances of inaccurate suggestions that led to public concern. For example, there were notable errors made by the system, including bizarre food advice and incorrect historical claims. Such missteps raised questions about the reliability of AI in providing accurate and relevant information.

Moreover, the competitive landscape is rapidly changing, with new players like Perplexity making strides in the AI search domain. Valued at $9 billion, Perplexity offers a chatbot-driven search experience that has stirred controversy over allegations of plagiarism related to its content generation features. As the startup navigates legal threats, it underscores the inherent complexities and ethical considerations surrounding AI content generation.

OpenAI has also recently entered the fray by integrating a search feature into its ChatGPT product. This approach, framed as a prototype, aims to limit the erroneous outcomes experienced by other platforms, all while partnering with media organizations to ensure that publishers maintain control over how their content is represented. This strategic move indicates a response to the pitfalls demonstrated by both Google and Perplexity.

Data from Adobe further underscores the growing reliance on AI, with statistics revealing that 39 percent of users utilized AI search for shopping, 55 percent for research purposes, and 47 percent for obtaining product recommendations. Advertisers are paying keen attention to these trends as the traffic from AI-enhanced search indicates a lucrative opportunity for engagement, contrasting with the current ad-laden landscape of traditional search engines.

While players like Google and Perplexity have experimented with embedding advertisements within AI search results, OpenAI has been more cautious, approaching ads as a potential last resort. Current developments suggest a strong consumer preference for ad-free AI tools, raising questions about the future of ad-driven models in the AI space.

As AI search tools carve out a new niche, their ability to circumvent the pitfalls of traditional search may position them as viable alternatives for consumers seeking more relevant, less cluttered browsing experiences. However, the journey ahead will depend on the industry’s ability to mitigate the ethical challenges and accuracy issues that have thus far hampered the evolution of AI in search. As consumers continue to explore this innovative avenue for sourcing online content, these new search paradigms may redefine not just how answers are discovered, but also how advertisers engage with their audiences in a rapidly evolving digital economy.

Comparing this year’s results with previous Black Fridays, Adobe reported a total online spend of $9.8 billion in the U.S. last year, while globally Salesforce indicated $70.9 billion spent. These contrasting figures showcase the growing trend toward online shopping, particularly during significant sales events, emphasizing the shift in consumer behavior.

In the U.S., the growth in e-commerce spending aligns with recent findings from the U.S. Census Bureau, which reported an increase in e-commerce sales in Q3 of over $300 billion, demonstrating a rise of between 6% and 8% compared to the same quarter of 2023. However, the global figures still show relatively lower growth in comparison. This discrepancy may be attributed to varying cultural practices around holiday shopping, especially since Black Friday’s prominence is notably confined to the United States, despite retailers worldwide participating.

Explaining the milestone, Vivek Pandya, lead analyst at Adobe Digital Insights, remarked, “Crossing the $10 billion mark is a big e-commerce milestone for Black Friday, for a day that in the past was more anchored towards in-store shopping. With consumers getting increasingly comfortable with mobile shopping and innovative technologies like chatbots, this sets a promising precedent for future Black Fridays.”

The peak shopping hours during Black Friday were highlighted by Adobe, showcasing a remarkable rate of $11.3 million spent every minute between 10 AM and 2 PM Eastern Time. In a bid to keep up with the rapid pace of sales, Shopify and Stripe introduced engaging animations for real-time analytics, combining high-tech visuals with essential data insights.

Data methodologies differed between Salesforce and Adobe: Salesforce relied on extensive shopping data samples collected from 1.5 billion consumers through their Commerce Cloud, Marketing Cloud, and Service Cloud. In contrast, Adobe utilized metrics from a staggering 1 trillion visits to U.S. retail sites, covering more than 100 million SKUs across 18 categories. This depth of data provides a comprehensive view of consumer trends and preferences in real time.

These groundbreaking figures are pivotal as they typically herald the start of the crucial holiday sales season, a time when retailers generate significant revenue before the year concludes. The interest surrounding these sales reflects an increasing consumer inclination toward e-commerce as a preferred shopping method exacerbated by convenience and enhanced shopping experiences.

Following recent updates that aired at Adobe MAX earlier this month, many users of Adobe Lightroom, Camera Raw, and Photoshop reported a drop in the quality of the generative AI features that they heavily rely on. This sentiment was echoed by various users on forums and platforms, with one user expressing despair over the lack of quality control, stating that the textures rendered previously have been replaced with results that appear smudged or artistic in nature. Some instances featured bizarre artifacts, such as animals appearing unexpectedly in pictures or additional limbs showing up where they shouldn’t.

PetaPixel’s own testing has aligned with these user experiences, highlighting a troubling pattern where Adobe’s generative AI technologies, designed to streamline photo editing, are instead hindering the workflow of many photographers. The generative tools, including Generative Fill and Generative Expand, aimed at enhancing editing speed and precision, have arrived laden with inconsistencies. A professional photographer, who uses generative fill thousands of times each day, lamented that despite previous versions achieving a near-perfect success rate, the updated tool now yields bizarre additions to images, such as unexpected rabbits or letters appearing on people’s faces. Their success rate, they shared, has plummeted to a disheartening 5-10% from the prior 90-95% range.

The photographer’s frustrations resonate with many in the community, who are experiencing similar mismatches in image textures and strange unintended placements of objects. The Generative Remove tool operates under the premise that, when removing pixels from an image, new pixels must seamlessly blend in with the background. In its current state, users report that this transition has become erroneous, leading to distractions being replaced with equally noticeable alterations.

While generative AI tools can drastically reduce the hours spent on labor-intensive tasks, the present experiences of photographers contrastingly illustrate a slowdown, with some users resorting back to traditional editing methods to manage their workflow. Adobe employee Terry White weighed in on the challenges of using Generative Remove, advising users to meticulously brush over the entirety of the object they wish to erase, including shadows and reflections. While this may improve results, the fundamental issues of the tool remain, leaving many users feeling conflicted about the evolving technology.

Despite the discontent, White acknowledged that improvements are still on the horizon. Adobe is actively listening to user feedback and making adjustments, an indication that they recognize the growing pains of integrating advanced AI into creative workflows. However, this inconsistency in results exposes a broader concern: the infancy of generative AI technology itself, which does not follow the linear path of improvement users may expect. This unpredictability poses significant challenges for photographers who place their trust in AI tools to enhance their productivity and creative output.

The situation has sparked conversations around the effectiveness of AI tools in photography; it is clear that while tools like Generative Remove and Fill have the potential to deliver outstanding results, they are not without flaws. As such, the quest for perfection in artificial intelligence-driven editing continues, with many practitioners still relying on traditional methods and acknowledging the limitations of current technology. For now, the journey remains a balance of AI innovation and the hands-on expertise that has characterized the field of photography for generations.

The Clean Up feature in Apple Photos is intuitive, gaining attention for its ability to effectively eliminate distractions in photographs. While users might be more familiar with its capabilities on iOS devices, this latest release brings the cleaning power to the desktop platform. Utilizing advanced AI, Clean Up not only removes unwanted elements but sometimes suggests objects to delete, a feature that diverges from Adobe’s approach, which relies heavily on user input and selection.

In a recent test, I used both platforms to remove various elements from six different photographs to evaluate their effectiveness. For the first image, power lines were removed from a scenic landscape. The results left by Adobe Generative Remove were disappointing, resulting in a noisy, pixelated image that suggested the AI struggled with textures. Conversely, Apple’s Clean Up delivered a flawless removal, presenting a clean, clear picture unmarred by artifacts. Here, Apple decisively took the win.

Next, I tasked both applications with removing two individuals standing at a platform’s edge—a common scenario for an AI tool. Adobe displayed an odd reluctance to leave the area blank, managing to remove one person effectively while mistakenly filling the void with an incongruous post. On the other hand, Apple Clean Up, while creating some visual clutter in the background, accomplished the task without introducing nonsensical elements. Again, a clear victory for Apple.

The third photograph involved removing individuals so that the focus could be shifted to a main subject in a cultural setting. Adobe again faltered, displaying a misunderstanding of the task that hindered the overall outcome. Apple’s approach yielded a better reflection of surrounding elements but showed signs of minor smudging. Despite its imperfections, Apple emerged as the preferred choice.

A more complex challenge presented itself when I attempted to erase a boat from a river scene. Here, the results resulted in a tie. Adobe managed an acceptable output, yet the pixels were smudgy and less distinct. On the contrary, Apple created sharper details, albeit with odd pixel duplication. Neither company came out squarely on top in this particular instance.

When I concentrated on a challenging subject—a person on an escalator—results were again favorable for Apple. Clean Up generated an accurate replication of the background, though a shadow remained where the person had stood. Adobe, however, showcased significant errors, including floating artifacts and chaotic sections that rendered the result unusable without additional editing.

Lastly, a test was performed using Adobe’s Generative Fill tool, which operates differently from Generative Remove. The outcome was dismal; the AI produced bizarrely unacceptable suggestions, emphasizing a fundamental issue with Adobe’s generative abilities. In contrast, Apple’s Clean Up recognized the prompt efficiently, reestablishing its advantage.

In light of the results, it appears Adobe’s recent updates to its AI-driven features may result in unsatisfactory outputs that do not meet user expectations. The inconsistency of Adobe’s results raises questions about the effectiveness of its updates, despite reassurances from the company regarding their commitment to improving performance. Meanwhile, Apple’s Clean Up feature demonstrates a solid understanding of its role and delivers predictable results—each operation yielding the same high-quality output without unnecessary complications.

As Apple continues refining its photo editing features, the call for a resurgence of programs like Aperture could grow stronger among creative users. The stark contrast in performance between these two tools indicates not just a competitive edge for Apple but also a cautionary tale regarding the implementation of AI technology in software products. For users looking for a reliable and effective tool for object removal in photography, Apple’s Clean Up appears to be a compelling option that outshines Adobe’s currently unreliable offerings. With the added benefit of being free for macOS users—a stark contrast to Adobe’s subscription model—the momentum appears to be in Apple’s favor at this juncture.

The first among these offerings is “Project Scenic,” which seeks to empower users by providing more granular control over the images produced by Adobe’s Firefly model. Unlike traditional methods that rely exclusively on text prompts, Scenic enables users to build a comprehensive 3D scene where they can adjust the positioning, size, and presence of various objects. Once the 3D landscape is established, the tool then generates a 2D image that reflects the user’s design intentions, allowing creatives a distinct layer of involvement in the content creation process.

Next in line is “Project Motion,” a two-part solution aimed at simplifying graphic animation. The initial phase acts as an intuitive animation builder, equipping users to add motion to text and basic images without needing extensive animation skills. Once users have crafted their animated video, the second phase enhances this output using text prompts and reference visuals, introducing elements such as color, textures, and rich background sequences, effectively elevating the quality and creativity of the animations.

Furthermore, the “Project Clean Machine” tool tackles one of the most common hurdles in video editing—the removal of distractions. This tool automatically eliminates unwanted elements from both images and videos, such as abrupt camera flashes or extraneous individuals in the frame. Functioning like an improved content-aware fill, Clean Machine not only removes undesired features but also rectifies any adverse visual effects left in their wake, ensuring consistent color grading and lighting throughout the footage, even after significant alterations are made.

Adobe’s new tools, referred to as “Sneaks,” illustrate the company’s commitment to pushing the envelope in creative technology by showcasing potential innovations still in development. While there’s no guarantee that these features will make it to a public release, Adobe has a history of refining successful Sneaks into full-fledged functionalities, as seen in past iterations like Photoshop’s Distraction Removal and After Effects’ Content-Aware Fill.

As creatives eagerly await further demonstrations and explorations of these products, Adobe highlights that none are available for public access at this moment. However, the excitement surrounding their possible integration into Creative Cloud applications is palpable, and the company is keen to gauge-interest from the creative community.

Overall, these advancements signify Adobe’s ongoing efforts to empower creators by alleviating the burdens of traditional content production, fostering an environment where imaginative projects can prosper unencumbered by technical constraints. As the future unfolds in the realm of creative technologies, these AI innovations from Adobe are set to redefine the standards of animation and video creation, heralding a new era of endless creative possibilities.