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Over the past few years, business leaders have lived through a masterclass in volatility. A global pandemic, supply chain breakdowns, surging cyberattacks, economic whiplash, and now the rapid acceleration of artificial intelligence have reshaped markets in unpredictable ways. For many executives, resilience once meant little more than business continuity planning: extra servers, backup systems, and insurance policies. But the world we lead in today demands more. Resilience is no longer just about defenseits about growth. The organizations that thrive amid disruption are not those with the strongest walls, but those with the most flexible foundations. They are able to absorb shocks, pivot quickly, and find opportunity where others see only risk. In a landscape defined by constant change, resilience has become the ultimate competitive advantage. From Recovery to Reinvention When the pandemic forced millions of people to work remotely overnight, some companies stumbled, scrambling to rewire systems and processes on the fly. Others adapted seamlessly, scaling their infrastructure, safeguarding data, and even uncovering new business opportunities. The difference wasnt foresightit was resilience. Resilient companies dont wait for crises to test their systems. They build for adaptability from the start. This means modern digital infrastructure that can flex with demand, decision-making processes that prioritize speed and clarity over bureaucracy, and leadership cultures that empower teams to act quickly. Crucially, it also means a mindset shift: The goal is not to return to a normal that no longer exists. Its to reinvent faster than your competitors. Resilience Across Three Dimensions Leaders often ask where to start. My experience points to three dimensions that define organizational resilience today: infrastructure, decision-making, and culture. 1. Infrastructure that bends, not breaksDigital infrastructure is the invisible backbone of every modern business. If it is brittle, the business is brittle. Legacy systems that cant scale or integrate force organizations to spend more time fixing problems than creating value. By contrast, companies with modern, cloud-enabled infrastructure can adapt quicklywhether to reroute supply chains, scale up for surges in customer demand, or safeguard data against emerging cyber threats. For example, when ransomware attacks spiked during the pandemic, companies with strong cyber resilience strategiescombining secure storage, rapid recovery, and smart automationwere able to restore operations in hours, not weeks. They didnt just avoid losses; they preserved customer trust. And when AI applications exploded onto the scene, those with flexible, well-governed data environments could test and deploy faster than rivals still wrestling with fragmented systems. 2. Decision-making at the speed of changeIn uncertain environments, resilience depends as much on how decisions are made as on the data that informs them. Traditional hierarchies slow response times, with insights stuck in silos and approvals delayed by bureaucracy. Resilient organizations create clarity about who decides what and empower people closest to the action to act. They ensure data flows across departments so that leaders at every level have a shared picture of reality. This approach marries speed with accountability. In my conversations with executives, I often hear stories of how front-line empowerment made the difference in moments of disruptionretail managers adjusting inventory strategies in real time, or manufacturing supervisors reconfiguring production on the fly. These shifts didnt happen because the CEO dictated every move; they happened because the organization trusted its people to act on data-driven insights quickly, and ensured the data they rely on is accessible, reliable, and available where and when its needed. 3. Culture as the engine of resilienceInfrastructure and processes matter, but ultimately resilience is human. It is defined by how people respond under pressureand whether they feel empowered to adapt and innovate. Resilient cultures are built on trust and psychological safety. Employees who feel trusted are more willing to experiment. Teams that feel supported are more likely to take ownership. Leaders who model adaptability create a ripple effect that normalizes flexibility across the organization. This human dimension is often overlooked, but it is what allows resilience to scale. Without it, even the most advanced systems and strategies will falter. With it, organizations can turn volatility into a proving ground for growth. Why Resilience Now Means Growth It may sound counterintuitive to equate resilience with offense, not just defense. But the connection is real. When uncertainty is constant, the ability to adapt faster than competitors is itself a growth strategy. Consider how cloud transformation, once viewed as a cost play, is now enabling new digital business models. Or how investments in cyber resilience not only prevent losses, but also unlock customer confidencea critical differentiator in trust-sensitive industries. Or how AI adoption, grounded in resilient data strategies, is enabling companies to innovate while others struggle with integration challenges. In each case, resilience doesnt just protect the enterpriseit expands its possibilities. It shifts the narrative from How do we recover? to How do we reinvent? The Leadership Imperative The challenge for leaders is to stop treating resilience as an insurance policy and start treating it as a core strategy. That requires moving beyond siloed initiativesone group working on cybersecurity, another on supply chains, another on cultureand instead weaving resilience into every layer of the business. The most effective leaders Ive seen approach resilience as a flywheel: Modern infrastructure supports faster decisions; faster decisions empower people; empowered people innovate in ways that strengthen the system further. Over time, resilience compounds into sustainable advantage. Resilience used to mean survival. Today, it is the strategy that separates those who stumble from those who soar. For leaders, the priority is no longer defense against disruption; it is building resilience as the engine of growth.
Category:
E-Commerce
The difference between OpenAI and Anthropic has never been clearer. OpenAI is constantly in the news with a new consumer app or feature, and is being billed as the next great consumer tech platform. Most recently it made news by offering a social network around its Sora image generator, and even says it plans to allow NSFW content on ChatGPT. Anthropic, meanwhile, has chosen a different path. The company stresses that because it gets most of its revenues from businesses and developers, its not trying to capture the mass market, and its not terribly concerned about how long users spend on its platform every day. We are interested in our consumer users to the degree they are doing work, solving problems in their life, says Anthropic design chief Joel Lewenstein during an interview with Fast Company this week. Because we’re not interested in passive consumption and image generation and video generationwe just sort of have ruled those out from a mission perspective . . . Anthropic was famously founded by a group of OpenAI execs who defected in 2021 to found a more safety-focused AI lab. That focus hasnt changed. Our interests are in making things that are beneficial while minimizing the risks of those same products because everything has a double-edged sword, Lewenstein says. We see . . . helping people grow and expand and create and solve problems as being the right risk-reward tradeoff. The San Francisco-based startup believes that work-first focus will ultimately win out as AI eventually shows its profoundest effects in the lives of businesses, not consumers. At a conference Wednesday, Anthropics cofounder and policy director Jack Clark says Anthropic will eventually overtake OpenAI because of its enterprise focus, its strong technological roadmap, and because its research is accelerating faster than its rivals. All of this is reflected in the look and feel of its Claude chatbotthe main entry to access Anthropics powerful modelsbut also in its attitude. Not warm and fuzzy When it comes to work, Claude is pleasant, even empathetic, but seriousand it comes with a free BS detector. Sycophancy in AI models, after all, has become a serious problem. OpenAI recently admitted having to push an update to its GPT-4o model to fix its sycophantic behavior. And its CEO Sam Altman stated in a post on Oct. 14 that users will be able to reintroduce that personality if they liked it. The model reportedly had a habit of praising or validating user statements even when they were delusional or concerning (one user claimed a divine identity). Some analysts believe that such behavior in a model is more than a bug, but a choice made by the model maker in the interest of getting people to use the platform more. A sycophantic chatbot in a work setting can act something like a yes-man, embracing and offering to further develop even the worst business ideas. This can lead to a range of reputational and financial harms, not to mention seriously damaging trust in the AI. Sychophantic AI could be especially dangerous to Anthropic, which wants its user to use Claude not just for quick content generation, but as a collaborator or thinking partner to do serious work. In order to do that, the user needs to build confidence and trust in the reasonableness of the AI. So Anthropic trained the models behind Claude to push back on logically suspect thoughts from the user. Lewenstein says his company worked especially hard to train this into its newest model, Claude Haiku 4.5, which it says is the most sycophancy-resistant model available in its size. The artifacts shift The idea of Claude as collaborator has directly impacted the chatbots user interface. With the introduction of Artifacts last year, Anthropic added a highly functional workspace around the chatbot. The idea of the Artifacts UX is to show a working draft of the project the user and the AI are working on in real time, within a panel at the right side of the interface. This might be a document draft, a chart, or a code preview, which the user can inspect, click, highlight, and suggest changes. The user can tell Claude to write something in a new way, or integrate a new idea from an uploaded PDF or text file. I cannot overstate how big of a shift that is, and [it] anchors a lot of the way that we think, Lewenstein says. By this he means that Artifacts encourages the user to think of Claude as a smart work companion, rather than just a content generator. It creates this sense of you’re making something alongside Claude, Lewenstein says. We’re not just giving you the answer. We’re not having you just download it and we’re done . . . Rather, the human and chatbot enter a dialog where they gradually shape the output into what the user wants. Lewenstein acknowledges that while AI tools have a growing number of power users, a significant percentage of users have yet to scratch the surface of whats possible. He says a major challenge of the user interface design is to invite people to Claudes features more fully. Artifacts can show users their options so that they can proceed in an experimental way, learning as they go. And, as of last month, Claude now can automatically remember past chats, so it might proactively ask if the user wants to include some theme or piece of data (perhaps a relevant piece of proprietary product research or a business plan) its encountered before. I think the more things that Claude is able to doClaude can now make PowerPoints and make Excel documentsthe more things that it makes, the more important it is that there is some space that you can actually see and engage with that content, Lewenstein says. The reason Claude can make presentations and spreadsheets is because of skills, or packets of knowledge that Claude can call up when the user needs them. On Thursday, a day after announcing its new Claude Haiku 4.5 model, the company announced that Claude users can now make their own agent skills.” If a user worked with Claude to create a presentation, for example, and called in a number of style sheets and marketing guidelines to do it, they can package all that work up in a skill and use it again the next time they need to do a presentation. In essence, Claude is enabling a user to create a kind of agent that has expertise and experience working with the user on a specific task. Agents AI agents can reason and act autonomously to do things like fetch data, perform actions, create plans. OpenAI recently announced a new tool called Agent Builder that provides a simple, graphical interface to create agents, define their workflows, and pull in tools the agent can use (a safety guardrail tool, for example). OpenAI says this could speed up the process for developers, and reduce the need to build agents from scratch. Anthropic believes that the right UX for building and managing agents depends on the type of user and their level of expertise. When developers within businesses build agents, Lewenstein explains, they write them as code, and Anthropic provides them a number of governance and security ools to help manage them. Theres no abstraction layer that represents the parts as objects that can be dragged around on a screen (at least not yet). Lewenstein says consumers, prosumers, and average knowledge workers usually just want to describe a goal they want the agent to achieve, then let the AI carry out the necessary functions behind the scenes to make it happen. That’s the direction Anthropic is pursuing now. Whether users even want to think about agents as a concept remains an open question, he says. Still, Anthropic is exploring several different kinds of agent approaches within Claude, some of them tightly integrated with chat, some of them less so. The focus is on what people are trying to accomplish, Lewenstein says. Anthropic will provide whatever is needed in any form factor to achieve that, and the company isn’t wedded to any particular UX paradigm yet. He cites the old marketing adage: Users dont really want a quarter-inch drill bit, they want a quarter-inch hole. Claude of the future Right now, users are still trying to understand how AI agents can fit into their overall workflows. In a work setting they may be skeptical that the agent will produce reliable, actionable work. They will naturally want to know a lot about how the agent is doing its work, how it’s getting from a directive to a result. Lewenstein says that Claude now lets users click to see all the steps the agent (powered by the model) took to reach a result. Building that into the UX, he says, wasnt a terribly challenging problem. But, over time, Claude will become more autonomous and capable of working unsupervised for longer periods of time (already the Claude Sonnet 4.5 model can work by itself for 30 hours). This could create challenges for the UX, which will have to show an audit of every step in the work that was done. We have these components in the UI which we’ve been working on for the last couple of years, which is a short little summary and then if you expand it, it actually shows you, Here’s everything I did for the last X hours, so that you can really build up an understanding but also a trust. In the first phases of AI agents being used within enterprises, users will have to think through what tasks they can delegate to agents, and what tasks to keep for themselves. Future versions of Claude, Lewenstein says, might help the user understand this. I think this is the future of where a lot of these products need to gounderstanding someone’s workflow enough, [and] its own capabilities enough, to proactively say, I will take this work off your plate and I will leave you with this thing, and that should feel very empowering to people, Lewenstein says. An AI for work Even for its consumer users, Anthropic is interested in helping them do work, not pass the time. So the same Claude user interface works pretty well for both personal and business use cases, Lewenstein says. He says consumers use Claude for a lot of personal things that might as well be work thingscomplex problems like planning a vacation or navigating a complicated renovation. We see consumers or people who are not doing it for their employer finding a lot of benefit in basically all the same basic features that we have [in Claude] for work. Eighty percent of Anthropics revenues come from enterprise customers. After crossing $1 billion a year in annualized revenue run rate (ARR) at the beginning of 2025, the company expects to hit $9 billion in ARR by the end of the year, Reuters reports, and then $26 billion in 2026. While OpenAI doesnt usually talk about its revenue mix, its CFO Sarah Friar said in 2024 that the company made 75% of its money from consumer subscriptions. As of June 2025, OpenAIs ARR was reportedly $10 billion (excluding licensing revenue from Microsoft and large one-time deals). Analysts expect OpenAI to reach about $12.7 billion in total revenue in 2025.
Category:
E-Commerce
Layoffs might make headlines, but the real measure is how leaders support the remaining employees. Layoffs are undeniably challenging for good reason. However, its what leaders do in the aftermath that determines whether a culture fractures or recovers. Ive led workforce complex reductions at Amazon, Microsoft, startups, and PE-backed firms. While every situation was unique, the same pattern appeared each time. It wasnt necessarily the layoff that broke the culture. It was the leadership response. Layoffs disrupt the culture and impact more than just headcount. Ive watched talented, engaged employees turn quiet and withdrawn after layoffs. Not because they stopped caring, but because they stopped feeling safe. The aftermath of layoffs can be unsettling for those who remain. Organizations expect survivors to absorb heavier workloads while they navigate shaken trust and mixed emotions. Layoff survivors often experience relief, guilt, grief, and anxiety about whats next. This is the leadership moment too few prepare for. Post-layoff culture recovery isnt automaticits intentional. In these moments, they need to communicate. Its a make-or-break opportunity to rebuild confidence, reinforce values, and heal a companys culture. Culture recovery hinges on many factors. Leadership must step up to manage the aftermath. Heres how to approach it: Lead with candor, not corporate speak Layoffs are typically a financial decision, but culture recovery is a leadership decision. Dont miss your moment. Layoffs dont kill culture. Neglect does. Leaders who avoid the hard conversations, hide behind jargon, and pretend its business as usual are the ones who lose the trust of their employees. After all, silence creates speculation. Thats why its important that leaders directly address and over-communicate early. I’ve introduced pulse checks, frequent town halls, and open forums. You cant rebuild morale through Slack updates or pizza parties. You need to do this in an authentic way. When my company had to conduct layoffs several years ago, it was a stressful experience. As the HR leader, I carried a significant emotional burden in conversations with employees who were impacted as well as those with those who remained. Our executive team met with staff to answer tough questions and provide updates. The first few sessions were a bit tense for both me and our leaders, as we faced some tough questions. We stumbled at first with too much corporate speak, and employees saw right through it. The room was tense. But eventually, that discomfort became a turning point when leaders stopped with the jargon and started showing real vulnerability. After that, the dynamic shifted. Acknowledging the emotional climate is important because it helps us reclaim performance and commitment. If we wanted to show our support for employees, we needed to address these issues head-on. Many companies carefully plan their layoff process, including announcements and severance packages. However, they often neglect what comes next. People don’t remember the slide decks or talking pointsthey remember how you showed up at this moment. Empty buzzwords do more harm than good. Speak to people on a human level and create space for honest conversations about what is certain and whats unknown. Be open about changes involving the business, team structure, available headcount resources, or ongoing uncertainties. Reaffirm what hasnt changed. At the same time, you also need to be clear about the path forward. Create safe spaces for emotion After layoffs, the workplace feels different, and pretending otherwise only deepens the sense of unease that employees feel. Leaders who acknowledge this reality set the stage for recovery. To help teams reengage, you need to take the time to listen to your employees. When you give people this kind of face, theyre more likely to adapt more quickly and regain momentum. Validating emotions doesnt weaken performanceit accelerates it. Employees who feel like youve heard them are far more likely to reengage, contribute, and collaborate. Weekly check-ins become vital for building connections. These conversations are not always easy, but theyre necessary for healing. Over time, that openness strengthens collaboration and restores trust. Rebuild culture from within Rebuilding from within starts with clarity. Employees need contextwhy you made certain decisions, and what resources are available moving forward. People want details that help them understand whats ahead and how their work fits the bigger picture. This is also the moment to reenergize the team. Reaffirm the mission and values so employees can reconnect to a shared purpose. Even in uncertainty, knowing the why behind the work helps people stay motivated. Leaders need to act. Retaining key talent, ensuring workloads are sustainable, and recognizing the additional effort required of those who remain all demonstrate that leadership is paying attention. A common mistake leaders make is assuming that the remaining team members will just pick up the slack. This assumption can lead to increased burnout or, even worse, the loss of valuable talent. A better approach is prioritizing tasks, eliminating low-value work, and having an honest conversation about the short-term trade-offs that are involved. Recognize that this is a cultural moment Layoffs test culture. They dont automatically destroy itwhat damages culture is indifference, silence, or meaningless lip service. When leaders respond with honesty and care, disruption can become a catalyst for renewal. You shape culture through daily choices: the courage to answer tough questions, the discipline to maintain consistent communication, and the humility to admit when youve compromised trust. Employees notice whether leadership avoids the hard truths or embraces them. Moments of disruption invite reflection. Leaders can use this time to reassess values, address blind spots, and strengthen practices that they might have overlooked. Openness about what needs to change prevents damaging back-channeling and reinforces inclusivity. Culture is the foundation on which every company rests. If it fractures, performance and morale follow. But a stronger culture can emerge when leaders step into this moment with honesty and courage.
Category:
E-Commerce
OpenAI has announced that starting in December, ChatGPT will allow the generation of erotic content for verified adult users. At the same time, Elon Musks xAI has launched Grok Imagine, an image-generation system that already includes an NSFW mode for producing explicit imagery. None of this should surprise anyone. Desire, fantasy, and pornography have always been powerful engines of technological adoption. Photography, video, the internet, and even online payments all grew, in part, because of it. The interesting question is not about sex: its about what these decisions reveal about the kind of humanity Big Tech companies are shaping. Desire as a managed service This is not about prudishness or panic. Sexuality will, of course, find its digital expressions. Whats unsettling is not the presence of eroticism in technology, but its industrialized management. The difference between eroticism and algorithmic consumption is the same as that between experience and dopamine: one is built through relationship; the other is dosed from the outside. By integrating sexuality into large language models and visual generators, platforms are not liberating desire: they are administering it. They decide which fantasies are acceptable, which bodies exist and which dont, what limits imagination deserves, and which ones are preemptively censored. The promise is freedom; the result is regulation of pleasure. From exploration to domestication When excitement, tenderness, and curiosity are mediated through an interface, our relationship with our bodies and with others changes. This isnt moralism. Its behavioral architecture. Algorithms learn what attracts us, replicate it, reinforce it, and turn it into dependence. Users stop exploring desire; they repeat it. And repetition, safe, comfortable, and risk-free, becomes a form of domestication. Theres no need to manipulate people with ideology when you can condition them with pleasure. Constant stimulation is a far more effective form of control than censorship ever was. A new vector of capture Its no coincidence that this expansion arrives just as large language models mature and corporations compete to keep users inside their closed ecosystems. Sex, in this context, becomes just another vector of attention capture, a way to deepen the emotional bond between humans and machines. The goal is no longer for AI to respond, but to accompany, excite, soothe, and replace. The fantasy isnt companionship: its containment. An artificial partner designed never to challenge, never to refuse, never to feel. This is not technological liberation. Its the automation of comfort. From entertainment to managed desire As I said a couple of weeks ago, weve been here before. From social networks to gaming, digital entertainment has followed the same logic of permanent stimulation. What changes now is the terrain: its no longer about free time: its about desire itself, that core where emotion and biology meet. Turning desire into a managed service run by algorithms is the final step toward a docile humanity, one in which even intimacy becomes a subscription. Digital sex vs. algorithmic sex The point is not to moralize about pornography: its to understand what it means to hand over control of erotic imagination, one of humanitys most powerful creative forces, to closed systems that do not explain how they learn, what they filter, or whom they serve. The problem is not digital sex. Its algorithmic sex. Not pleasure, but control. Once these systems learn to measure, adjust, and stimulate desire, free will becomes just another optimization parameter. The new anesthesia Behind this apparent liberalization of content lies a simpler, more effective strategy: keep us busy, satisfied, and distracted. Not indoctrinated: anesthetized. A form of emotional livestock, fed by impulses engineered on distant servers. Algorithmic sheep: artificially happy, productive, and unable to tell the difference between genuine desire and manufactured stimulus.
Category:
E-Commerce
A new music startup created an instrument that can turn your microwave, electric toothbrush, and baby monitor into hauntingly beautiful music. Its branding converts all of those fascinating outputs into an infinite series of Victorian-inspired patterns. Eternal Research is a brand founded by musician Alexandra Fierra, and its dedicated to unlocking the existing music hidden in everyday things,” per its website. The companys debut product is called the Demon Box. This fully analog device uses an intricate array of sensors to detect the electro-magnetic fields (EMFs) of almost any electronic device around it, and then turns those EMFs into music. The brand hit its funding goal on Kickstarter in a matter of hours, and the first Demon Boxes (which cost $999 a pop) are set to ship in November. The Demon Box blends the study of music-making with modern technologyand for its launch it needed a brand to match. The New York-based agency Cotton Design was tasked with creating a visual identity that an infinitely audio-reactive generative model that transforms sound into historically accurate Victorian patterns. Like the instrument itself, the brand eschews convention to create something unique. [Image: courtesy Cotton Design] A music brand inspired by vampires, high fashion, and the Victorian era When Talia Cotton, founder and creative director at Cotton Design, first met with Fierra, she felt as if Fierra was on another frequency than the rest of the world. Fierras approach to music is all about craft, experimentation, and the intricacy of the sound that exists in the everyday world. Her vision for Eternal Researchs branding combined that attention to detail with a mysterious, almost vampiric visual sensibility. [Image: courtesy Cotton Design] She kept on sending us these examples, Cotton says. She sent us an empty unboxing experience for YSL, because she said there was something special about that unboxing experience. There was a box, that held an envelope, that held a scarfall these different layers of the brand that she thought were very thoughtful. She also sent us an old collectors edition VHS tape of [Bram Stokers] Dracula in a coffin-shaped box. These small pieces of Fierras inner world slowly started to piece together for Cottons team, which included coder Noah Schwadron and project manager Sewon Bae. But there was one source of inspiration that became a kind of north star for the brand. [Image: courtesy Cotton Design] [Fierra] is a collector of old books from the Victorian era, Cotton says. She has a very deep appreciation for the craft that is associated with that period in time, which is defined by ornamentation, and by the careful, slow process of making these outputs. Each Victorian pattern was unique. Eventually, Cotton realized that Fierras fascination with Victorian design sensibilities was the perfect basis for Eternal Researchs brandthe challenge was to figure out how to pull off an identity for a modern music brand company based on inspiration from the 19th century. [Image: courtesy Cotton Design] How Eternal Research pulled brand inspiration from A24 Cotton describes Eternal Researchs brand as geared toward two different consumer bases: one who is just discovering the brand, and another who is an avid follower prepared to pay the sizable $999 cost of the Demon Box. To appeal to both of those consumer segments, Cottons team needed to balance a strong element of personalization with a sense of approachability. This was really tricky for us, because on one hand there was the ornament, the detail, the special-feeling experience, and on the other hand, [Fierra] was very gung ho about making this feel open; like anybody could understand it, Cotton says. For consumers that are just discovering Eternal Research, Cottons team took inspiration from brands outside the music tech space with cult followings, like the movie studio A24which Cotton says pulls some of its mystique from seeming almost unbranded. Similarly, Eternal Researchs most frequently used assets, including its logo and sans serif wordmark, are kept simple and unornamented to invite new customers to learn more. [Image: courtesy Cotton Design] But as fans of the brand dig deeper, the branding storypulls them into a more and more expressive world. That world is anchored by a generative model, coded from the ground up by Schwadron, that turns any sound input into a Victorian-inspired ornamental design. These patterns, which can be made in an infinite array of combinations, appear everywhere from the brands social media content to its website, letterheads, and packagingand the model is available online for anyone to use. [Image: courtesy Cotton Design] A brand that turns sounds into Victorian patterns Cotton Designs audio-reactive design relies on historical sources to create period-accurate Victorian patterns. The team sifted through hundreds of vintage book covers, illustrations, and re-creations to understand how these patterns were constructed and which motifs recurred most commonlydown to the angles of individual curves and the kind of floral patterns that were most popular. The base of the generative model can be understood as a kind of map. Each map is composed of a grid and a series of circles, which tell the model where the patterns lines should go. Every time the model is reloaded, it creates a random base map. From there, it takes in a sound input and interprets not only the inputs volume, but also its frequency, texture, and timbre. These sound qualities are digested by the model and correlated to more than 30 different pattern parameters, like line density, length, animation speed, the number of floral accents, and more. With all of these layers stacked on top of each other, the outcome is a model that can literally make an infinite number of sound-based Victorian illustrations. While audio-reactive designs have become more popular in recent years, this project is perhaps one of the most expressive, detailed applications of the technique to date. Paired with the music generated by the Demon Box, the brand is like an otherworldly symphony for both the ears and eyes.
Category:
E-Commerce
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