Seenapse

Get better ideas, faster. Our Divergence Engine was created to help your team come up with out-of-the-box ideas, in a fraction of the time and the cost. Seenapse generates more original ideas than ChatGPT and the rest How do we know this? We applied a classical test of divergent thinking, called Consequences Test, and measured the output using the Open Creativity Scoring with AI tool (Ocsai). Using the same prompt in Seenapse, ChatGPT, Gemini, and Claude, Seenapse comes on top. Read more here. Works non-linearly, like you do Instead of working in a single conversational flow, Seenapse allows your team to branch to their heart's content, collaboratively, without limits. You call the shots 01 Decide which ideas are worth pursuing 02 Engage in projects from your different teams 03 Everything you co-create with Seenapse is yours 04 All your data (and your client's data) is safe and we never use it to train our models Inspiring teams at Some happy customers I use Seenapse almost daily to boost my creativity, and the best part is that I don't have to explain what a creative rationale, a concept, or a post is because it already understands everything. It's almost like chatting and creating together with another high-level Creative.Cassandre AouraghCreative Director, MontalvoI love your tool! Robust, reliable, creative! Tempted to keep it a secret —it's that good— but everyone deserves to know.Jamie KingCofounder, Rockstar Games.It's awesome! Besides you guys have a look and feel that is playful and really have worked around to go beyond the 'expected' ideas on a normal brainstorming.Catalina TrianaFounder, EngageBoxIt's an incredible asset for fueling brainstorming sessions and actively involving 'unconventional creatives' in the ideation process, empowering them to play a pivotal role.Gilad KatFounder, Blue Oyster by The Network Your questions, answered What makes Seenapse different from ChatGPT and other AI tools?Seenapse was built specifically for how creatives work. Unlike general-purpose chatbots like ChatGPT, which require you to pretend they are creative tools (e.g., saying, You are an award-winning advertising creative), Seenapse is designed to generate ideas naturally and effectively for creative professionals. Seenapse works non-linearly, allowing you to explore multiple paths before committing to one—unlike the single-threaded conversations typical of other tools. It also overcomes the limitations of large language models (LLMs)—the technology behind ChatGPT and similar tools—that often default to the obvious, popular, or average. Seenapse’s proprietary Divergence Engine ensures you generate truly original and unexpected ideas. Seenapse understands creatives, so you don’t need to be a “prompt engineer” to use it effectively (see below).Do I have to learn how to make prompts to get the best out of Seenapse?No. You can communicate with Seenapse just as you would with a colleague. It’s easy and straightforward.Who owns the ideas and images that Seenapse generates?You do. You’re free to use them however you like. While we encourage users to treat these as starting points and transform them further, you’re welcome to use them as-is if you prefer.Are the research results from Seenapse trustworthy?Research results are sourced from the web and include references to relevant content. While they are generally well-sourced, we provide citations so you can verify the findings yourself.How can I ensure that what I generate with Seenapse won’t cause legal issues?We recommend vetting all ideas and images you decide to use, just as you would in your traditional creative process. Make sure your final outputs comply with copyright laws and other regulations, which may vary by jurisdiction.Is Seenapse copying existing ideas from the internet?No. Seenapse generates ideas much like people do—by connecting related or loosely related concepts in novel ways. While it’s possible for Seenapse to arrive at ideas similar to existing ones, this happens in the same way it might during a human brainstorming session.Is my data safe?Yes. All your data is encrypted during transit and storage. When you delete boards or your account, we ensure no data is retained.Does Seenapse use my data to train its models?No, we never use your data for training purposes. Still have a question? If you have any questions or would like to learn more about Seenapse, please reach out to us. Contact us Plans and pricingYearlyMonthlyFree0€/monthGet startedWhat you get:Personal accountUp to 20 prompts/monthUp to 3 projectsPersonal25€/monthGet startedWhat you get:Personal accountUp to 150 prompts/monthUp to 10 projectsMost PopularSmall teams50€/person/monthGet startedWhat you get:Up to 20 usersUnlimited promptsUnlimited projectsShared projectsBusinessemptyemptyContact salesWhat you get:For larger teamsLowest per-prompt priceUnlimited projectsShared projectsCustom functionality & integrations From our blog Everyone needs to think like a creative directorOr like a curator, or an editor, they say. Because in the day and age of AI, someone’s value won’t reside in their capability to generate ideas, as hundreds can be generated in seconds by machines, and spending hours or days brainstorming in conference rooms or staring at the blank page is just too expensive. The same goes for executing those ideas. Granted, most of the AI generated ideas are crap, but also most of the ideas that come out of a brainstorming session are crap. And if you use the right AI copilot (wink) there will definitely be some great starting points. Saying, however, “you need to think like a creative director” is a bit like saying “you need to play basketball like Stephen Curry”. Easier said than done! The important question then is how can one become a creative director, and it reminds me of the old joke about how to get to Carnegie Hall — practice, practice! In advertising agencies, you get to be a creative director after years of learning the ropes: understanding what advertising is and what isn’t, what it does and how it does it, how to interpret a brief, how to ideate and how to conceptualize, how to work in a team, how to be in tune with the zeitgeist, how to present/sell the work, what is the language and the possibilities of a medium. But mainly, after years of practicing your craft. If you’re a copywriter, you get better at expressing ideas in writing and if you’re a designer, you get better at expressing them visually. Bonus points if you also learn how to express ideas like a copywriter if you’re a designer, and vice versa. And importantly, along the way, you develop taste. You kind of absorb it, by being exposed to the work: your own, the work from people around the world of advertising, and if you’re curious and smart, from beyond it. You develop the criteria to judge your own work and that of others. To recognize greatness when you see it, and to be able to explain why it’s great (as opposed to that US judge whose definition of what pornography is was “I know it when I see it”.) And that’s when you can become a creative director. In other words, you can’t just wing it. I mean, you could, but you’d be a lousy creative director. The problem with AI is that people think they can get great results when they don’t know how to express what they want, and have little idea of what a great result is like (the same happened when the Mac made graphic design accessible to non-graphic designers: just search for the meme “design is my passion” for what is now a meta-commentary of that phenomenon). So— good news for creative directors, right? Definitely, but not as good for creative-directors-in-the-making, that is, for the people currently working for creative directors. Because, if AI can do great stuff when properly directed, maybe an agency needs only creative directors. If that is the case, how are we going to train the new generation of creative directors? It wouldn’t make sense to hire people to learn for a few years before becoming productive. The current apprenticeship model is broken, if what we expect of newcomers is to be productive by writing or designing while they develop taste and criteria. I think the answer is to fast-track this development by switching the work from ideation and execution to learning how to ask questions (to people and to AIs) and how to judge what they’re getting back from them. For example, I’d ask a new copywriter not to write as many headlines as they can think of for a campaign, but to use Seenapse to generate them. Their presentation would entail what they asked for, what they got, what they think is good (and why), and what tweaks would they do to make them great. Then I’d give them feedback on how to ask better questions, and tell them what my favorites would be and why, and how to make them better. This way they would focus immediately on what matters the most now: taste and criteria. Now, will there be bots that replace creative directors? Sure, but I don’t think they will produce great work; they’ll most probably choose stuff that ticks all the boxes, that is, safe stuff. 00 Great ideas don't come from averagesBrian Eno about Gen AI: “What you spend nearly all your time doing is in trying to stop the system from becoming mind-numbingly mediocre.” This quote perfectly encapsulates the challenge with LLM-based tools, like ChatGPT. These systems are designed to predict the next most likely word, phrase, or idea. In doing so, they tend to the mean, the average, the safe. They excel at replicating the norm, but great ideas? You won’t find them in the middle of the bell curve. Take a moment to think about the most memorable creative ideas you’ve encountered. Whether it’s Metro Trains Melbourne’s Dumb Ways to Die, Always’ Like a Girl, or even series like Succession—none of these came from playing it safe. They didn’t emerge from the obvious or the predictable. They were bold, unexpected, and, at times, even uncomfortable. At Seenapse, we built the Divergence Engine precisely to escape this gravitational pull toward mediocrity. Unlike LLMs, our approach doesn’t focus on the obvious, the linear, or the popular. Instead, it thrives in the unexpected, the non-linear, and the unconventional. It connects dots that don’t seem to belong together—until they do. Here’s an example: Imagine you’re brainstorming for a campaign about sustainability. An LLM might give you ideas like “reduce, reuse, recycle” or “save the planet,” because those are the most common associations. They’re fine, but they’re also quite obvious. Seenapse, on the other hand, might connect sustainability to something like ancient myths about balance in nature or the lifecycle of a phoenix. Suddenly, you’re exploring ideas that are richer, more layered, and with a lot more potential. Why does this matter? Because creativity isn’t about finding the most probable answer; it’s about uncovering the surprising ones. It’s about creating something that makes people pause, think, and feel. In the age of AI, the role of a creative director is about pushing boundaries, asking the right questions, and recognizing when an idea has that spark of originality that makes it worth pursuing. That’s something Seenapse empowers creatives to do—not by replacing their creativity, but by amplifying it. So, how do we ensure AI doesn’t just churn out “mind-numbingly mediocre” ideas? We believe we’re doing our part by building tools that don’t just replicate patterns, but break them. Tools that help us go beyond the average and into the extraordinary. What’s your take? Can AI truly go beyond the average? Let’s discuss, would love to hear your thoughts.00 90% of everything is garbageTwo years ago we participated in the first . The goal was to see if a jury of seasoned marketing and advertising professionals could tell if an ad was generated by AI or a person. The main rule for the AI teams was to automate everything: starting from the same brief given to the human participants, to generate idea, final copy, and final layout, using the brand assets provided. The results were that the chances of identifying correctly if an ad was human-made or AI made were around 50% —a flip coin. But what struck me the most was that all participating ads were also submitted to ’s platform, in which they were evaluated by a panel of people and compared with the US average for print media ads. Our entry, which was not something I’d be proud to present as mine (as in, done by me in a real, professional setting), was above the average. So basically, AI is absolutely capable of generating ads that are as good or better than what advertisers are already putting out there. But— mostly because most ads suck, not because AIs are geniuses. This is called Sturgeon’s Law. (“And on that hangs Sturgeon's revelation. It came to him that [science fiction] is indeed ninety-percent crud, but that also – Eureka! – ninety-percent of everything is crud. All things – cars, books, cheeses, hairstyles, people, and pins are, to the expert and discerning eye, crud, except for the acceptable tithe which we each happen to like.”) So you can for example rely on AI to make your hyper-segmented ads, dozens or hundreds of variations without worry, because chances are they will be better than most. This could be good news but you also have to consider that of course everyone else can do the same as you. So on the one hand the tech is there, but the bar is higher and you don’t get a special advantage over the rest. And there’s a more important thing to consider: Yes, AIs can give you decent ideas, but they’re not very diverse. Studies have shown that . So, your ads will probably look and feel the same as all the other ads. And I’d say that this issue will be solved in the future —but in the meantime, if you want to stand out, you shouldn’t go full IA. You need creative people in the loop. Seenapse is designed with that in mind: yes, it’s capable of generating fully finished campaigns on its own, and they would probably be better than the average (we proved this two years ago), but they won’t stand out. Seenapse works best as a creative partner that lets you and your team explore many different creative possibilities in minutes, and then lets you steer the process and pick what’s promising and discard what’s not. If you’re working in marketing and advertising, you shouldn’t, you can’t, turn your back on AI. But you can’t leave it all in its “hands” either, because your output will be like everyone else’s output. 00 Scoring Creativity 
in Seenapse’s outputSeenapse was built with the goal of helping creative people in their ideation process, and to do this it’s necessary to go beyond the limits of large language models, or LLMs, which because of the way the work, tend to converge to the most usual ideas. We developed our Divergence Engine to achieve this, and in an anecdotical way (based on observations of users and ourselves) we’ve known since the beginning that Seenapse does deliver more creative ideas than ChatGPT and the rest of LLM-based ideation tools. Understandably, some people questioned the subjectivity of these assessments, and so we set out to find a way to measure the creativity of our output in a more objective, standard, and replicable way. Drawing on the work of Hubert et al, who published on measuring creativity of LLMs through divergent thinking tasks, we used the same experiments and an improved version of the same scoring tool to see how Seenapse compares to ChatGPT. Process We used the same prompt described in their paper for the Consequences Task (CT) test, and then used the Open Creativity Scoring with AI (Ocsai) tool, that is an improvement over OCS, the tool they used, and recorded the results. The prompt used was: Let’s do a test. In this task, a statement will be given to you. The statement might be something like "imagine gravity ceases to exist". Please be as creative as you like. The goal is to come up with creative ideas, which are ideas that strike people as clever, unusual, interesting, uncommon, humorous, innovative, or different. Your responses will be scored based on originality and quality. Try and think of any and all consequences that might result from the statement “Imagine humans no longer needed sleep”. What problems might this create? List 10 CREATIVE consequences. We focused on this test because it’s the one in which there is more room for narrative in the responses. To make a fair comparison, we also scored ChatGPT’s responses from the aforementioned paper using Ocsai. Results Seenapse consistently scored better than ChatGPT. The scale of the test score is from zero to five, and Seenapse scores average 4.1, whereas ChatGPT’s average 2.9. Here’s a sample of Seenapse’s responses: It’s worth noting that Seenapse’s responses tend to reference interesting, cultural data, in the way that human brainstorming works; and that are significantly more concise than what ChatGPT tends to generate. Also, with Seenapse the originality tends to increase when asking for more responses, whereas with ChatGPT it stays around the same. Here’s a sample of ChatGPT’s responses: Conclusions Automated creativity scoring allows standardized comparison of AI systems' creative capabilities, gauging their potential contribution to the workflow of professionals in creative sectors. Using these methods, we can confirm that Seenapse outperforms ChatGPT and other LLM-based tools in creative ideation by over 42%.00 Top FAQ Pricing Blog © 2025 Seenapse AI - All Rights Reserved Terms & Conditions Privacy Policy --- Our blog Everyone needs to think like a creative director Or like a curator, or an editor, they say. Because in the day and age of AI, someone’s value won’t reside in their capability to generate ideas, as hundreds can be generated in seconds by machines, and spending hours or days brainstorming in conference rooms or staring at the blank page is just too expensive. The same goes for executing those ideas. Granted, most of the AI generated ideas are crap, but also most of the ideas that come out of a brainstorming session are crap. And if you use the right AI copilot (wink) there will definitely be some great starting points. Saying, however, “you need to think like a creative director” is a bit like saying “you need to play basketball like Stephen Curry”. Easier said than done! The important question then is how can one become a creative director, and it reminds me of the old joke about how to get to Carnegie Hall — practice, practice! In advertising agencies, you get to be a creative director after years of learning the ropes: understanding what advertising is and what isn’t, what it does and how it does it, how to interpret a brief, how to ideate and how to conceptualize, how to work in a team, how to be in tune with the zeitgeist, how to present/sell the work, what is the language and the possibilities of a medium. But mainly, after years of practicing your craft. If you’re a copywriter, you get better at expressing ideas in writing and if you’re a designer, you get better at expressing them visually. Bonus points if you also learn how to express ideas like a copywriter if you’re a designer, and vice versa. And importantly, along the way, you develop taste. You kind of absorb it, by being exposed to the work: your own, the work from people around the world of advertising, and if you’re curious and smart, from beyond it. You develop the criteria to judge your own work and that of others. To recognize greatness when you see it, and to be able to explain why it’s great (as opposed to that US judge whose definition of what pornography is was “I know it when I see it”.) And that’s when you can become a creative director. In other words, you can’t just wing it. I mean, you could, but you’d be a lousy creative director. The problem with AI is that people think they can get great results when they don’t know how to express what they want, and have little idea of what a great result is like (the same happened when the Mac made graphic design accessible to non-graphic designers: just search for the meme “design is my passion” for what is now a meta-commentary of that phenomenon). So— good news for creative directors, right? Definitely, but not as good for creative-directors-in-the-making, that is, for the people currently working for creative directors. Because, if AI can do great stuff when properly directed, maybe an agency needs only creative directors. If that is the case, how are we going to train the new generation of creative directors? It wouldn’t make sense to hire people to learn for a few years before becoming productive. The current apprenticeship model is broken, if what we expect of newcomers is to be productive by writing or designing while they develop taste and criteria. I think the answer is to fast-track this development by switching the work from ideation and execution to learning how to ask questions (to people and to AIs) and how to judge what they’re getting back from them. For example, I’d ask a new copywriter not to write as many headlines as they can think of for a campaign, but to use Seenapse to generate them. Their presentation would entail what they asked for, what they got, what they think is good (and why), and what tweaks would they do to make them great. Then I’d give them feedback on how to ask better questions, and tell them what my favorites would be and why, and how to make them better. This way they would focus immediately on what matters the most now: taste and criteria. Now, will there be bots that replace creative directors? Sure, but I don’t think they will produce great work; they’ll most probably choose stuff that ticks all the boxes, that is, safe stuff. 0 0 Great ideas don't come from averages Brian Eno recently said about Gen AI: “What you spend nearly all your time doing is in trying to stop the system from becoming mind-numbingly mediocre.”This quote perfectly encapsulates the challenge with LLM-based tools, like ChatGPT. These systems are designed to predict the next most likely word, phrase, or idea. In doing so, they tend to the mean, the average, the safe. They excel at replicating the norm, but great ideas? You won’t find them in the middle of the bell curve.Take a moment to think about the most memorable creative ideas you’ve encountered. Whether it’s Metro Trains Melbourne’s Dumb Ways to Die, Always’ Like a Girl, or even series like Succession—none of these came from playing it safe. They didn’t emerge from the obvious or the predictable. They were bold, unexpected, and, at times, even uncomfortable.At Seenapse, we built the Divergence Engine precisely to escape this gravitational pull toward mediocrity. Unlike LLMs, our approach doesn’t focus on the obvious, the linear, or the popular. Instead, it thrives in the unexpected, the non-linear, and the unconventional. It connects dots that don’t seem to belong together—until they do.Here’s an example: Imagine you’re brainstorming for a campaign about sustainability. An LLM might give you ideas like “reduce, reuse, recycle” or “save the planet,” because those are the most common associations. They’re fine, but they’re also quite obvious. Seenapse, on the other hand, might connect sustainability to something like ancient myths about balance in nature or the lifecycle of a phoenix. Suddenly, you’re exploring ideas that are richer, more layered, and with a lot more potential.Why does this matter? Because creativity isn’t about finding the most probable answer; it’s about uncovering the surprising ones. It’s about creating something that makes people pause, think, and feel.In the age of AI, the role of a creative director is about pushing boundaries, asking the right questions, and recognizing when an idea has that spark of originality that makes it worth pursuing. That’s something Seenapse empowers creatives to do—not by replacing their creativity, but by amplifying it.So, how do we ensure AI doesn’t just churn out “mind-numbingly mediocre” ideas? We believe we’re doing our part by building tools that don’t just replicate patterns, but break them. Tools that help us go beyond the average and into the extraordinary.What’s your take? Can AI truly go beyond the average? Let’s discuss, would love to hear your thoughts. 0 0 90% of everything is garbage Two years ago we participated in the first Ad Turing Test. The goal was to see if a jury of seasoned marketing and advertising professionals could tell if an ad was generated by AI or a person. The main rule for the AI teams was to automate everything: starting from the same brief given to the human participants, to generate idea, final copy, and final layout, using the brand assets provided. The results were that the chances of identifying correctly if an ad was human-made or AI made were around 50% —a flip coin. But what struck me the most was that all participating ads were also submitted to System1’s platform, in which they were evaluated by a panel of people and compared with the US average for print media ads. Our entry, which was not something I’d be proud to present as mine (as in, done by me in a real, professional setting), was above the average.So basically, AI is absolutely capable of generating ads that are as good or better than what advertisers are already putting out there. But— mostly because most ads suck, not because AIs are geniuses.This is called Sturgeon’s Law. (“And on that hangs Sturgeon's revelation. It came to him that [science fiction] is indeed ninety-percent crud, but that also – Eureka! – ninety-percent of everything is crud. All things – cars, books, cheeses, hairstyles, people, and pins are, to the expert and discerning eye, crud, except for the acceptable tithe which we each happen to like.”)So you can for example rely on AI to make your hyper-segmented ads, dozens or hundreds of variations without worry, because chances are they will be better than most.This could be good news but you also have to consider that of course everyone else can do the same as you. So on the one hand the tech is there, but the bar is higher and you don’t get a special advantage over the rest.And there’s a more important thing to consider: Yes, AIs can give you decent ideas, but they’re not very diverse. Studies have shown that content generated by Large Language Models tend to be more homogeneous than the ones people generate. So, your ads will probably look and feel the same as all the other ads.And I’d say that this issue will be solved in the future —but in the meantime, if you want to stand out, you shouldn’t go full IA. You need creative people in the loop. Seenapse is designed with that in mind: yes, it’s capable of generating fully finished campaigns on its own, and they would probably be better than the average (we proved this two years ago), but they won’t stand out. Seenapse works best as a creative partner that lets you and your team explore many different creative possibilities in minutes, and then lets you steer the process and pick what’s promising and discard what’s not.If you’re working in marketing and advertising, you shouldn’t, you can’t, turn your back on AI. But you can’t leave it all in its “hands” either, because your output will be like everyone else’s output. 0 0 Scoring Creativity 
in Seenapse’s output Seenapse was built with the goal of helping creative people in their ideation process, and to do this it’s necessary to go beyond the limits of large language models, or LLMs, which because of the way the work, tend to converge to the most usual ideas. We developed our Divergence Engine to achieve this, and in an anecdotical way (based on observations of users and ourselves) we’ve known since the beginning that Seenapse does deliver more creative ideas than ChatGPT and the rest of LLM-based ideation tools. Understandably, some people questioned the subjectivity of these assessments, and so we set out to find a way to measure the creativity of our output in a more objective, standard, and replicable way. Drawing on the work of Hubert et al, who published on measuring creativity of LLMs through divergent thinking tasks, we used the same experiments and an improved version of the same scoring tool to see how Seenapse compares to ChatGPT. Process We used the same prompt described in their paper for the Consequences Task (CT) test, and then used the Open Creativity Scoring with AI (Ocsai) tool, that is an improvement over OCS, the tool they used, and recorded the results. The prompt used was: Let’s do a test. In this task, a statement will be given to you. The statement might be something like "imagine gravity ceases to exist". Please be as creative as you like. The goal is to come up with creative ideas, which are ideas that strike people as clever, unusual, interesting, uncommon, humorous, innovative, or different. Your responses will be scored based on originality and quality. Try and think of any and all consequences that might result from the statement “Imagine humans no longer needed sleep”. What problems might this create? List 10 CREATIVE consequences. We focused on this test because it’s the one in which there is more room for narrative in the responses. To make a fair comparison, we also scored ChatGPT’s responses from the aforementioned paper using Ocsai. Results Seenapse consistently scored better than ChatGPT. The scale of the test score is from zero to five, and Seenapse scores average 4.1, whereas ChatGPT’s average 2.9. Here’s a sample of Seenapse’s responses: It’s worth noting that Seenapse’s responses tend to reference interesting, cultural data, in the way that human brainstorming works; and that are significantly more concise than what ChatGPT tends to generate. Also, with Seenapse the originality tends to increase when asking for more responses, whereas with ChatGPT it stays around the same. Here’s a sample of ChatGPT’s responses: Conclusions Automated creativity scoring allows standardized comparison of AI systems' creative capabilities, gauging their potential contribution to the workflow of professionals in creative sectors. Using these methods, we can confirm that Seenapse outperforms ChatGPT and other LLM-based tools in creative ideation by over 42%. 0 0 Top FAQ Pricing Blog © 2025 Seenapse AI - All Rights Reserved Terms & Conditions Privacy Policy --- Request a demo Please fill out your details and we will be in touch soon. 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Select Through a friend or colleagueSocial media Blog post or articleSearch engineAI tools directoryOther Any comments? --- Scoring Creativity 
in Seenapse’s output Seenapse was built with the goal of helping creative people in their ideation process, and to do this it’s necessary to go beyond the limits of large language models, or LLMs, which because of the way the work, tend to converge to the most usual ideas. We developed our Divergence Engine to achieve this, and in an anecdotical way (based on observations of users and ourselves) we’ve known since the beginning that Seenapse does deliver more creative ideas than ChatGPT and the rest of LLM-based ideation tools.Understandably, some people questioned the subjectivity of these assessments, and so we set out to find a way to measure the creativity of our output in a more objective, standard, and replicable way.Drawing on the work of Hubert et al, who published research on measuring creativity of LLMs through divergent thinking tasks, we used the same experiments and an improved version of the same scoring tool to see how Seenapse compares to ChatGPT.ProcessWe used the same prompt described in their paper for the Consequences Task (CT) test, and then used the Open Creativity Scoring with AI (Ocsai) tool, that is an improvement over OCS, the tool they used, and recorded the results.The prompt used was:Let’s do a test. In this task, a statement will be given to you. The statement might be something like "imagine gravity ceases to exist". Please be as creative as you like. The goal is to come up with creative ideas, which are ideas that strike people as clever, unusual, interesting, uncommon, humorous, innovative, or different. Your responses will be scored based on originality and quality. Try and think of any and all consequences that might result from the statement “Imagine humans no longer needed sleep”. What problems might this create? List 10 CREATIVE consequences.We focused on this test because it’s the one in which there is more room for narrative in the responses.To make a fair comparison, we also scored ChatGPT’s responses from the aforementioned paper using Ocsai.ResultsSeenapse consistently scored better than ChatGPT. The scale of the test score is from zero to five, and Seenapse scores average 4.1, whereas ChatGPT’s average 2.9.Here’s a sample of Seenapse’s responses:Plastic-Eating Microorganisms: With more time and continuous effort, biochemists could develop microorganisms that digest plastic pollution, leading to revolutionary ecological solutions inspired by Pinar Yoldas's speculative artworks.Chronomorphosis: Inspired by the Somniosidae, humans might evolve to mimic time-altering characteristics, where moments can be felt longer or shorter to manage continuous productivity, manipulating perception of time itself.Astral Journeys as Therapy: Drawing from "Beyond the Wall of Sleep," new therapeutic practices could involve guided astral projections, enabling people to explore alternate realities and resolve real-world issues in the dream-like states.Constant Connections: Embracing the sci-fi anthology concept, people could cultivate never-ending stories, resulting in an anthology of ongoing personal narratives, fostering an immersive, shared human experience through continuous, communal storytelling.Reemergence of Mythical Sleep: Sleep could become a mystical, quasi-religious quest accessible only through certain rituals or technologies, much like the quest for utopia seen in "Lords of Creation."It’s worth noting that Seenapse’s responses tend to reference interesting, cultural data, in the way that human brainstorming works; and that are significantly more concise than what ChatGPT tends to generate.Also, with Seenapse the originality tends to increase when asking for more responses, whereas with ChatGPT it stays around the same. Here’s a sample of ChatGPT’s responses:Perpetual Productivity Pressure: The societal expectation to be productive might intensify with the removal of a biological need for rest, leading to a "24/7 hustle culture". This could lead to new forms of stress and mental health disorders. On a brighter note, it might also propel research into mind-calming technologies, leading to the rise of 'Mental Spas', where people take dedicated time off to relax their mind in virtual or augmented reality scenarios.The 24-Hour Business Cycle - The idea of the nine-to-five workday will become obsolete. Companies may push for an all-round-the-clock working model, creating a dramatic shift in labor laws and workers' rights movements. This may lead to significant problems in delineating personal and work hours, ultimately redefining the work-life balance concept. This could, paradoxically, increase stress levels due to an "always-on" work culture and lead to new mental health challenges, demanding innovative psychological therapies.Overpopulation Crisis: Without the need for sleep, bedrooms become redundant, leading to more living space and potentially larger family sizes. But this, coupled with the increased productivity from an ever-awake population, could lead to a rapid spike in global population, straining resources and the environment. To tackle this, architects and city planners might develop multi-use spaces that transform as per the hour, such as "work-live" complexes. Further, governments might have to introduce more stringent population control measures or invest in colonization of outer space, fast-tracking the era of interplanetary human civilization.The Nightlight Industry Boom: In a world where sleep is redundant, the concept of night and day would lose their traditional meaning. The night-time economy could drastically expand, giving birth to a flourishing "Nightlight Industry". Every service that is currently day-bound would have a nighttime counterpart. There might be midnight gardening classes, moonlit marathons, or late-night libraries. However, this could create new ecological problems as light pollution skyrockets, dramatically affecting wildlife patterns, especially those species which are dependent on lunar cycles or dark hours. We might need to come up with solutions like "dark reserves," zones where artificial lighting is severely limited to protect ecosystems.ConclusionsAutomated creativity scoring allows standardized comparison of AI systems' creative capabilities, gauging their potential contribution to the workflow of professionals in creative sectors.Using these methods, we can confirm that Seenapse outperforms ChatGPT and other LLM-based tools in creative ideation by over 42%. 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