To combat the proliferation of low-quality AI-generated images, visual search engine Cosmos is developing in-house AI models trained to predict aesthetic quality. These models are used to re-rank search results and feeds, establishing a quality floor and creating a "refuge" for users seeking high-quality, human-created content and inspiration.
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Creating reliable AI detectors is an endless arms race against ever-improving generative models, which often have detectors built into their training process (like GANs). A better approach is using algorithmic feeds to filter out low-quality "slop" content, regardless of its origin, based on user behavior.
Users are dissatisfied with purely AI-generated creative outputs like interior design, calling it "slop." This creates an opportunity for platforms that blend AI's efficiency with a human's taste and curation, for which consumers are willing to pay a premium.
The term "slop" is misattributed to AI. It actually describes any generic, undifferentiated output designed for mass appeal, a problem that existed in human-made media long before LLMs. AI is simply a new tool for scaling its creation.
Higgsfield's CEO notes a key trend: the best-performing AI-generated ads don't try to pass as real. They lean into a distinct AI aesthetic, suggesting that audiences are not only accepting but are also engaged by this new visual style, prioritizing creativity over photorealism.
As AI-generated 'slop' floods platforms and reduces their utility, a counter-movement is brewing. This creates a market opportunity for new social apps that can guarantee human-created and verified content, appealing to users fatigued by endless AI.
The negative perception of current AI-generated content ('slop') overlooks its evolutionary nature. Today's low-quality output is a necessary step towards future sophistication and can be a profitable business model, as it represents the 'sloppiest' AI will ever be.
The definition of "AI slop" is evolving from obviously fake images to a flood of perfectly polished, generic, and boring content. As AI makes flattering imagery cheap to produce, authentic, unpolished, and even unflattering content becomes more valuable for creators trying to stand out on platforms like Instagram.
To avoid generic, creatively lazy AI output ("slop"), Atlassian's Sharif Mansour injects three key ingredients: the team's unique "taste" (style/opinion), specific organizational "knowledge" (data and context), and structured "workflow" (deployment in a process). This moves beyond simple prompting to create differentiated results.
The best AI models are trained on data that reflects deep, subjective qualities—not just simple criteria. This "taste" is a key differentiator, influencing everything from code generation to creative writing, and is shaped by the values of the frontier lab.
Scott Belsky predicts that as AI-generated content floods feeds, audiences will develop a 'membrane of doubt.' To counter this, brands and artists will use 'proof of craft'—behind-the-scenes content showing the human effort involved—as a powerful tool for advertising and building trust.
