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Andreessen Horowitz investors (and identical twins) Justine and Olivia Moore have been in venture capital since their undergraduate days at Stanford University, where, in 2015, they cofounded an incubator called Cardinal Ventures to help students pursue business ideas while still in school. Founding it also gave the Moores an entry point into the broader VC industry. “The thing about starting a startup incubator at Stanford is all the VCs want to meet you, even if you have no idea what you’re doing, which we did not back then,” Olivia says. At the time, the app economy was booming, and services around things like food delivery and dating proliferated, recalls Justine. But that energy pales in comparison to the excitement around AI the sisters now experience at Andreessen Horowitz. “There’s so many more opportunities in terms of what people are able to build than what we’re able to invest in,” she says. To identify the right opportunities, the Moores track business data such as paid conversion rates and closely examine founders’ backgrounds—whether they’ve worked at a cutting-edge AI lab or deeply studied the needs of a particular industry. They attend industry conferences, stay current on the latest AI research papers, and, perhaps most critically, spend significant time testing AI-powered products. That means going beyond staged demos to see what tools can actually do and spotting founders who quickly intuit user needs and add features accordingly. “From using the products, you get a pretty quick, intuitive sense of how much of something is marketing hype,” says Olivia, whose portfolio includes supply chain and logistics operations company HappyRobot and creative platform Krea. The sisters also value Andreessen Horowitz’s scale, which allows the firm to stick to its convictions rather than chase trends, and its track record of supporting founders beyond simply investing. (Andreessen Horowitz is reportedly seeking to raise $20 billion to support its AI-focused investments.) “It’s most fun to do this job when you can work with the best founders and when you can actually really help them with the core stuff that they’re struggling with, they’re working on, or striving to do in their business,” says Justine, a key early investor in voice-synthesis technology company ElevenLabs. Though the sisters live together and work at the same firm, where they frequently bounce ideas off each other, they’ve carved out their own lanes. Olivia focuses more on AI applications, while Justine spends more time on AI infrastructure and foundational models. At this point, they say, it’s not unheard of for industry contacts to not even realize they’re related. “If I see [her] on a pitch meeting in any given day, that’s maybe more of the exception than the rule,” Justine says. This profile is part of Fast Company’s AI 20 for 2025, our roundup spotlighting 20 of AI’s most innovative technologists, entrepreneurs, corporate leaders, and creative thinkers. View the full article

Last year, OpenAI decided it had to pay more attention to its power users, the ones with a knack for discovering new uses for AI: doctors, scientists, and coders, along with companies building their own software around OpenAI’s API. And so the company turned to post-training research lead Michelle Pokrass to spin up a team to better understand them. “The AI field is moving so quickly, the power-user use cases of today are really the median-user use cases a year from now, or two years from now,” Pokrass says. “It’s really important for us to stay on the leading edge and build to where capabilities are emerging, rather than just focusing on what people are using the models for now.” Pokrass, a former software engineer for Coinbase and Clubhouse, came to OpenAI in 2022, fully sold on AI after experiencing the magic of coding tools such as GitHub Copilot. She played key roles in developing OpenAI’s GPT-4.1 and GPT-5, and now she focuses on testing and tweaking models based on users who are pushing AI to its limits. Specifically, Pokrass’s team works on post-training, a process that helps large language models understand the spirit of user requests. This refining allows ChatGPT to code, say, a fully polished to-do list app rather than just instructions on how to theoretically make one. “There’s been lots of examples of GPT-5 helping with scientific breakthroughs, or being able to discover new mathematical proofs, or working on important biological problems in healthcare, saving doctors and specialists a lot of time,” Pokrass says. “These are examples of exactly the kinds of capabilities we want to keep pushing.” Creating a team with this niche focus is unusual among Big Tech companies, which tend to target broad audiences they can monetize at scale through, say, targeted ads. Catering to power users isn’t a revenue play, Pokrass says, even if many pay $200 per month for ChatGPT Pro subscriptions. Instead, it’s a way to assess the “why” of AI, with power users pointing to unforeseen opportunities. With traditional tech, it’s usually clear how people will use a product a few years down the road, Pokrass says. “With AI, we’re all discovering with our users, live, what exactly is highest utility, and how people can get value out of this.” Eventually, OpenAI figures those use cases will help inform the features that it builds for everyone else. Pokrass gives the example of medical professionals using AI in their decision-making, which in turn could help ChatGPT better understand the kind of medical questions people are asking it (for better or worse). “There’s always work for this team, because as we push boundaries for what our models can do, the frontier just gets moved out, and then we start to see an influx of new activity of people using these new capabilities,” Pokrass says. This profile is part of Fast Company’s AI 20 for 2025, our roundup spotlighting 20 of AI’s most innovative technologists, entrepreneurs, corporate leaders, and creative thinkers. View the full article

The healthcare industry faces major challenges in creating new drugs that can improve outcomes in the treatment of all kinds of diseases. New generative AI models could play a major role in breaking through existing barriers, from lab research to successful clinical trials. Eventually, even AI-powered robots could help in the cause. Nvidia VP of healthcare Kimberly Powell, one of Fast Company’s AI 20 honorees, has led the company’s health efforts for 17 years, giving her a big head start on understanding how to turn AI’s potential to improve our well-being into reality. Since it’s likely that everything from drug-discovery models to robotic healthcare aides would be powered by Nvidia chips and software, she’s in the right place to have an impact. This Q&A is part of Fast Company’s AI 20 for 2025, our roundup spotlighting 20 of AI’s most innovative technologists, entrepreneurs, corporate leaders, and creative thinkers. It has been edited for length and clarity. A high percentage of drugs make it to clinical trials and then fail. How can new frontier models using lots of computing power help us design safer and more effective drugs? Drug discovery is an enormous problem. It’s a 10-year journey at best. It costs several billions to get a drug to market. Back in 2017, very shortly after the transformer [generative AI model] was invented to deal with text and language, it was applied by the DeepMind team to proteins. And one of the most consequential contributions to healthcare today is still [DeepMind’s] invention of AlphaFold. Everything that makes [humans] work is based on proteins and how they fold and their physical structure. We need to study that, [because] you might build a molecule that changes or inhibits the protein from folding the wrong way, which is the cause of disease. So instead of using the transformer model to predict words, they used a transformer to predict the effects of a certain molecule on a protein. It allowed the world to see that it’s possible to represent the world of drugs in a computer. And the world of drugs really starts with human biology. DNA is represented. After you take a sample from a human, you put it through a sequencing machine and what comes out is a 3 billion character sequence of letters—A‘s, C‘s, T‘s, and G‘s. Luckily, transformer models can be trained on this sequence of characters and learn to represent them. DNA is represented in a sequence of characters. Proteins are represented in a sequence of characters. So how will this new approach end up giving us breakthrough drugs? If you look at the history of drug discovery, we’ve been kind of circling around the same targets—the target is the thing that causes the disease in the first place—for a very long time. And we’ve largely exhausted the drugs for those targets. We know biology is more complex than any one singular target. It’s probably multiple targets. And that’s why cancer is so hard, because it’s many things going wrong in concert that actually cause cancer and cause different people to respond to cancer differently. Once we’ve cracked the biology, and we’ve understood more about these multiple targets, molecular design is the other half of this equation. And so similarly, we can use the power of generative models to generate ideas that are way outside a chemist’s potential training or even their imagination. It’s a near infinite search space. These generative models can open our aperture. I imagine that modeling this vast new vocabulary of biology places a whole new set of requirements on the Nvidia chips and infrastructure. We have to do a bunch of really intricate data science work to apply this [transformer] method to these crazy data domains. Because we’re [going from] the language model and [representing] these words that are just short little sequences to representing sequences that are 3 billion [characters] long. So things like context length—how much context length is how much information can you put into a prompt—has to be figured out for these long proteins and DNA strings. We have to do a lot of tooling and invention and new model architectures that have transformers at the core. That’s why we work with the community to really figure out what are the new methods or the new tooling we have to build so that new models can be developed for this domain. That’s in the area of really understanding biology better. Can you say more about the company you’re working with that is using digital twins to simulate an expensive clinical trial before the trial begins? ConcertAI is doing exactly that. They specialize in oncology. They simulate the clinical trials so they can make the best decisions. They can see if they don’t have enough patients, or patients of the right type. They can even simulate it, depending on where the site selection is, to predict how likely the patients are to stay on protocol. Keeping the patients adhering to the clinical trial is a huge challenge, because not everybody has access to transportation or enough capabilities to take off work. They build that a lot into their model so that they can try to set up the clinical trial for its best success factors. How might AI agents impact healthcare? You have these digital agents who are working in the computer and working on all the information. But to really imagine changing how healthcare is delivered, we’re going to need these physical agents, which I would call robots, that can actually perform physical tasks. You can think about the deployment of robots, everything from meeting and greeting a patient at the door, to delivering sheets or a glass of ice chips to a patient room, to monitoring a patient while inside a room, all the way through to the most challenging of environments, which is the operating room with surgical robotics. Nvidia sells chips, but I think what I’ve heard in your comments is a whole tech stack, including in healthcare. There are models, there are software layers, things like that. I’ve been at the company 17 years working on healthcare, and it’s not because healthcare lives in a chip. We build full systems. There are the operating systems, there are the AI models, there are the tools. And a model is never done—you have to be constantly improving it. Through every usage of that model, you’re learning something, and you’ve got to make sure that that agent or model is continuously improving. We’ve got to create whole computing infrastructure systems to serve that. View the full article

A few years ago, Tara Feener’s career took an unexpected pivot. She’s spent nearly two decades working on creative tools for companies like Adobe, FiftyThree, WeTransfer, and Vimeo, and was content to keep working in that domain. But then the Browser Company came along, and Feener saw an opportunity to build something even more ambitious. Feener—one of Fast Company’s AI 20 honorees for 2025—is now the company’s head of engineering, overseeing its AI-focused Dia browser and its earlier Arc browser. The browser is suddenly an area of intense interest for AI companies, and Feener understands why: It’s the first stop for looking up information, and it’s already connected to the apps and services you use every day. OpenAI and Perplexity both offer their own browsers now, borrowing some Dia features like the ability to summarize across multiple tabs and interrogate your browser history. The Browser Company itself was acquired in September by Atlassian for $610 million, proclaiming that it would “transform how work gets done in the AI era.” Feener says her team has never felt more creative. “We’ve never seen more prototypes flying around, and I think I’m doing my job successfully as a leader here if that motion is happening,” she says. This Q&A is part of Fast Company’s AI 20 for 2025, our roundup spotlighting 20 of AI’s most innovative technologists, entrepreneurs, corporate leaders, and creative thinkers. It has been edited for length and clarity. How’d you end up at the Browser Company? [The Browser Company CEO] Josh Miller started texting me. We were both in that 2013 early New York tech bubble, we had a couple conversations, and he pitched me on the Browser Company. At first I couldn’t connect it to the arc of my career in creativity, but then it just became this infectious idea. I was like, “Wait a minute, I think the browser is actually the largest creative canvas of my entire career. It’s where you live your life and where you create within.” Why does it feel like AI browsers are having a moment right now? I really do believe that the browser is the most compelling, accessible AI layer. It’s the number-one text box you use. And what we do is, as you’re typing, we can distinguish a Google search from an assistant or a chat question. In the future, you can imagine other things like taking action or tapping into other search engines. It basically becomes an air traffic control center as you type, and that’s going to help introduce folks to AI just so much faster because you don’t have to go to ChatGPT to ask a question. That’s part one. Part two is just context. We have all of your stuff. We have all of your tabs. We have your cookies. With other AI tools, the barrier to connecting to your other web apps or tools is still high. We get around that with cookies within the browser, so we’re able to just do things like draft your email, or create your calendar event, or tap into your Salesforce workflow. How do you think about which AI features are worth doing? I just see it as another bucket of Play-Doh. I never wanted to do AI for the sake of AI but for leveraging AI in the right moment to do things that would have been really hard for us to do before. A great example is being able to tidy your tabs for you in Arc. There’s a little broom you can click, and it starts sweeping, and it auto-renames, organizes, and tidies up your tabs. We always had ambitions and prototypes, but with large language models, we were able to just throw your tabs at it and say, “Tidy for me.” With Arc, it was a lot about tab management. With Dia, we have context, we have memory, we have your cookies, so it’s like we actually own the entire layer. We leverage that as a tool for things like helping you compare your tabs, or rewriting this tab in the voice of this other tab, which is something I do almost every day. Being able to do that all within the browser has just been a huge unlock. Can you elaborate on how Dia taps into users’ browser histories? Browser history has always been that long laundry list of all the places you’ve been, but actually that long list is context, and nothing is more important in AI than context. Just like TikTok gets better with every swipe, every time you open something in Dia we learn something about you. It’s not in a creepy way, but it helps you tap into your browser history. Just like you can @ mention a tab in Dia and ask a question, like “give me my unread emails,” with your history you can do things like, “Break down my focus time over the past week,” or “analyze my week and tell me something about myself given my history.” We have a bunch of use cases like that in our skills gallery that you can check out, and those are pretty wild. In ChatGPT and other chat tools, it feels like you have to give a lot to build up that context body. We’re able to tap into that as a tool in a very direct way. Some AI browsers offer “agent” features that can navigate through web pages on your behalf. Will Dia ever browse the web for you? We’ve done a bunch of prototypes and for us, the experience of just literally going off and browsing for you and clicking through web pages hasn’t felt yet fast enough or seamless enough. We’re all over it in terms of making sure we’re harnessing it at the right moment and the right way when we think it’s ready. We don’t want to hide the web or replace the web. Something I like to say about Dia is that we want to be one arm around you and one arm around the internet. And it’s like, how can we make tapping into your context in your browser feel the same way it would feel to write a document, or even just to create something with plain, natural language? I think that’s like the most powerful thing. It’s like the same feeling I had when I was young and tapped into Flash, and that people had with HTML. With AI, literally my mom can write a sentence like, “turn this New York Times recipe into a salad,” and in some way she’s created an app that does some kind of transformation. And that just gets me really excited. View the full article

Raquel Urtasun is the founder and CEO of self-driving truck startup Waabi as well as a computer science professor at the University of Toronto. Unlike some competitors, Waabi’s AI technology is designed to drive goods all the way to their destinations, rather than merely to autonomous vehicle hubs near highways. Urtasun, one of Fast Company’s AI 20 honorees for 2025, spoke with us about the relationship between her academic and industry work, what sets Waabi apart from the competition, and the role augmented reality and simulation play in teaching computers to drive even in unusual road conditions. This Q&A is part of Fast Company’s AI 20 for 2025, our roundup spotlighting 20 of AI’s most innovative technologists, entrepreneurs, corporate leaders, and creative thinkers. It has been edited for length and clarity. Can you tell me a bit about your background and how Waabi got started? I’ve been working in AI for the last 25 years, and I started in academia, because AI systems weren’t ready for the real world. There was a lot of innovation that needed to happen in order to enable the revolution that we see today. For the last 15 years, I’ve been dedicated to building AI systems for self-driving. Eight years ago, I made a jump to industry: I was chief scientist and head of R&D for Uber’s self-driving program, which gave me a lot of visibility in terms of what building a world-class program and bringing the technology to market would look like. One of the things that became clear was that there was a tremendous opportunity for a disrupter in the industry, because everybody was going with an approach that was extremely complex and brittle, where you needed to incorporate by hand all the knowledge that the system should have. It was not something that was going to provide a scalable solution. So a little bit over four years ago, I left Uber to go all in on a different generation of technology. I had deep conviction that we should build a system designed with AI-first principles, where it’s a single AI system end-to-end, but at the same time a system that is built for the physical world. It has to be verifiable and interpretable. It has to have the ability to prove the safety of the system, be very efficient, and run onboard the vehicle. The second core pillar was that the data is as important as the model. You will never be able to observe everything and fully test the system by deploying fleets of vehicles. So we built a best-in-class simulator, where we can actually prove its realism. And what differentiates your approach from the competition today? The big difference is that other players have a black-box architecture, where they train the system basically with imitation learning to imitate what humans do. It’s very hard to validate and verify and impossible to trace a decision. If the system does something wrong, you can’t really explain why that is the case, and it’s impossible to really have guarantees about the system. That’s okay for a level two system [where a human is expected to be able to take over], but when you want to deploy level four, without a human, that becomes a huge problem. We built something very different, where the system is forced to interpret and explain at every fraction of a second all the things it could do, and how good or bad those decisions are, and then it chooses the best maneuver. And then through the simulator, we can learn much better how to handle safety-critical situations, and much faster as well. How are you able to ensure the simulator works as well as real-world driving? The goal of the simulator is to expose the self-driving vehicle’s full stack to many different situations. You want to prove that under each specific situation, how the system drives is the same as if the situation happens in the real world. So we take all the situations where Waabi driver has driven in the real world, and clone them in simulation, and then we see, did the truck do the same thing. We also recently unveiled a really exciting breakthrough with mixed-reality testing. The way the industry does safety testing is they bring a self-driving vehicle to a closed course and they expose it to a dozen, maybe two dozen, scenarios that are very simple in order to say it has basic capabilities. It’s very orchestrated, and they use dummies in order to test things that are safety critical. It’s a very small number of non-repeatable tests. But you can actually do safety testing in a much better way if you can do augmented reality on the self-driving vehicle. With our truck driving around in a closed course, we can intercept the live sensor data and create a view where there’s a mix of reality and simulation, so in real time, as it’s driving in the world, it’s seeing all kinds of simulated situations as though they were real. That way, you can have orders of magnitude more tests. You can test all kinds of things that are otherwise impossible, like accidents on the road, a traffic jam, construction, or motorbikes cutting in front of you. You can mix real vehicles with things that are not real, like an emergency vehicle in the opposite lane. You’re also a full professor. Are you still teaching and supervising graduate students? I do not teach—I obviously do not have time to teach at all. I do have graduate students, but they do their studies at the company. We have this really interesting partnership with the University of Toronto. If you want to really learn and do research in self-driving, it is a must that you get access to a full product. And that’s impossible in academia. So a few years ago, we designed this program where students can do research within the company. It’s one of a kind, and to me, this is the future of education for physical AI. When did you realize the time was ripe for moving from academic research to industry work? That was about eight and a half years ago. We were at the forefront of innovation, and I saw companies were using our technology, but it was hard for me to understand if we were working on the right things and if there was something that I hadn’t thought of that is important when deploying a real product in the real world. And I decided at the time to join Uber, and I had an amazing almost four years. It blew my mind in terms of how the problem of self-driving is much bigger than I thought. I thought, Okay, autonomy is basically it, and then I learned about how you need to design the hardware, the software, the systems around safety, etc., in a way that everything is scalable and efficient. It was very clear to me that end-to-end systems and foundational models would be the thing. And four and a half years in, our rate of hitting milestones really speaks to this technology. It’s amazing—to give an example, the first time that we drove in rain, the system had never seen rain before. And it drove with no interventions in rain, even though it never saw the phenomenon before. That for me was the “aha” moment. I was actually [in the vehicle] with some investors on the track, so it was kind of nerve-racking. But it was amazing to see. I always have very, very high expectations, but it blew my mind what it could do. View the full article

The rapid expansion of artificial intelligence and cloud services has led to a massive demand for computing power. The surge has strained data infrastructure, which requires lots of electricity to operate. A single, midsize data center here on Earth can consume enough electricity to power about 16,500 homes, with even larger facilities using as much as a small city. Over the past few years, tech leaders have increasingly advocated for space-based AI infrastructure as a way to address the power requirements of data centers. In space, sunshine—which solar panels can convert into electricity—is abundant and reliable. On November 4, 2025, Google unveiled Project Suncatcher, a bold proposal to launch an 81-satellite constellation into low Earth orbit. It plans to use the constellation to harvest sunlight to power the next generation of AI data centers in space. So instead of beaming power back to Earth, the constellation would beam data back to Earth. For example, if you asked a chatbot how to bake sourdough bread, instead of firing up a data center in Virginia to craft a response, your query would be beamed up to the constellation in space, processed by chips running purely on solar energy, and the recipe sent back down to your device. Doing so would mean leaving the substantial heat generated behind in the cold vacuum of space. As a technology entrepreneur, I applaud Google’s ambitious plan. But as a space scientist, I predict that the company will soon have to reckon with a growing problem: space debris. The mathematics of disaster Space debris—the collection of defunct human-made objects in Earth’s orbit—is already affecting space agencies, companies, and astronauts. This debris includes large pieces, such as spent rocket stages and dead satellites, as well as tiny flecks of paint and other fragments from discontinued satellites. Space debris travels at hypersonic speeds of approximately 17,500 mph in low Earth orbit. At this speed, colliding with a piece of debris the size of a blueberry would feel like being hit by a falling anvil. Satellite breakups and anti-satellite tests have created an alarming amount of debris, a crisis now exacerbated by the rapid expansion of commercial constellations such as SpaceX’s Starlink. The Starlink network has more than 7,500 satellites providing global high-speed internet. The U.S. Space Force actively tracks more than 40,000 objects larger than a softball using ground-based radar and optical telescopes. However, this number represents less than 1% of the lethal objects in orbit. The majority are too small for these telescopes to identify and track reliably. In November 2025, three Chinese astronauts aboard the Tiangong space station were forced to delay their return to Earth because their capsule had been struck by a piece of space debris. Back in 2018, a similar incident on the International Space Station challenged relations between the U.S. and Russia, as Russian media speculated that a NASA astronaut may have deliberately sabotaged the station. The orbital shell Google’s project targets—a sun-synchronous orbit approximately 400 miles above Earth—is a prime location for uninterrupted solar energy. At this orbit, the spacecraft’s solar arrays will always be in direct sunshine, where they can generate electricity to power the onboard AI payload. But for this reason, sun-synchronous orbit is also the single most congested highway in low Earth orbit, and objects in this orbit are the most likely to collide with other satellites or debris. As new objects arrive and existing objects break apart, low Earth orbit could approach Kessler syndrome. In this theory, once the number of objects in low Earth orbit exceeds a critical threshold, collisions between objects generate a cascade of new debris. Eventually, this cascade of collisions could render certain orbits entirely unusable. Implications for Project Suncatcher Project Suncatcher proposes a cluster of satellites carrying large solar panels. They would fly with a radius of just 1 kilometer, each node spaced less than 200 meters apart. To put that in perspective, imagine a racetrack roughly the size of the Daytona International Speedway, where 81 cars race at 17,500 mph while separated by gaps about the distance you need to safely brake on the highway. This ultradense formation is necessary for the satellites to transmit data to each other. The constellation splits complex AI workloads across all its 81 units, enabling them to “think” and process data simultaneously as a single, massive, distributed brain. Google is partnering with a space company to launch two prototype satellites by early 2027 to validate the hardware. But in the vacuum of space, flying in formation is a constant battle against physics. While the atmosphere in low Earth orbit is incredibly thin, it is not empty. Sparse air particles create orbital drag on satellites; this force pushes against the spacecraft, slowing it down and forcing it to drop in altitude. Satellites with large surface areas have more issues with drag, as they can act like a sail catching the wind. To add to this complexity, streams of particles and magnetic fields from the sun—known as space weather—can cause the density of air particles in low Earth orbit to fluctuate in unpredictable ways. These fluctuations directly affect orbital drag. When satellites are spaced less than 200 meters apart, the margin for error evaporates. A single impact could not only destroy one satellite but also send it blasting into its neighbors, triggering a cascade that could wipe out the entire cluster and randomly scatter millions of new pieces of debris into an orbit that is already a minefield. The importance of active avoidance To prevent crashes and cascades, satellite companies could adopt a leave no trace standard, which means designing satellites that do not fragment, release debris, or endanger their neighbors, and that can be safely removed from orbit. For a constellation as dense and intricate as Suncatcher, meeting this standard might require equipping the satellites with “reflexes” that autonomously detect and dance through a debris field. Suncatcher’s current design doesn’t include these active avoidance capabilities. In the first six months of 2025 alone, SpaceX’s Starlink constellation performed a staggering 144,404 collision-avoidance maneuvers to dodge debris and other spacecraft. Similarly, Suncatcher would likely encounter debris larger than a grain of sand every five seconds. Today’s object-tracking infrastructure is generally limited to debris larger than a softball, leaving millions of smaller debris pieces effectively invisible to satellite operators. Future constellations will need an onboard detection system that can actively spot these smaller threats and maneuver the satellite autonomously in real time. Equipping Suncatcher with active collision-avoidance capabilities would be an engineering feat. Because of the tight spacing, the constellation would need to respond as a single entity. Satellites would need to reposition in concert, similar to a synchronized flock of birds. Each satellite would need to react to the slightest shift of its neighbor. Paying rent for the orbit Technological solutions, however, can go only so far. In September 2022, the Federal Communications Commission created a rule requiring satellite operators to remove their spacecraft from orbit within five years of the mission’s completion. This typically involves a controlled de-orbit maneuver. Operators must now reserve enough fuel to fire the thrusters at the end of the mission to lower the satellite’s altitude, until atmospheric drag takes over and the spacecraft burns up in the atmosphere. However, the rule does not address the debris already in space, nor any future debris, from accidents or mishaps. To tackle these issues, some policymakers have proposed a use tax for space debris removal. A use tax or orbital-use fee would charge satellite operators a levy based on the orbital stress their constellation imposes, much like larger or heavier vehicles paying greater fees to use public roads. These funds would finance active debris-removal missions, which capture and remove the most dangerous pieces of junk. Avoiding collisions is a temporary technical fix, not a long-term solution to the space debris problem. As some companies look to space as a new home for data centers, and others continue to send satellite constellations into orbit, new policies and active debris-removal programs can help keep low Earth orbit open for business. Mojtaba Akhavan-Tafti is an associate research scientist at the University of Michigan. This article is republished from The Conversation under a Creative Commons license. Read the original article. View the full article

Amid an uncertain economy—the growth of AI, tariffs, rising costs—companies are pulling back on hiring. As layoffs increase, the labor market cools, and unemployment ticks up, we’re seeing fewer people quitting their jobs. The implication: Many workers will be “job hugging” and sitting tight in their roles through 2026. Put more pessimistically: Employees are going to feel stuck where they are for the foreseeable future. In many cases, that means staying in unsatisfying jobs. Gallup’s 2025 State of the Global Workforce report shows that employee engagement has fallen to 21%. And a March 2025 study of 1,000 U.S. workers by advisory and consulting firm Fractional Insights showed that 44% of employees reported feeling workplace angst, despite often showing intent to stay. So if these employees are “hugging” their current roles, it’s not an act of affection. It’s often in desperation. “Being a job hugger means you’re feeling anxious, insecure, more likely to stay but also more likely to want to leave,” says Erin Eatough, chief science officer and principal adviser at Fractional Insights, which applies organizational psychology insights to the workplace. “You often see a self-protective response: ‘Nothing to see here, I’m doing a good job, I’m not leaving.’” This performative behavior can be psychologically damaging, especially in a culture of layoffs. “If I was scared of losing my job I’d try everything to keep it: complimenting my boss, staying late, going to optional meetings, being a good organizational citizen,” says Anthony Klotz, professor of organizational behavior at the UCL School of Management in London. “But we know that when people aren’t loving their jobs but are still going above and beyond, that it’s a one-way trip to burnout.” The tight squeeze In cases where jobs aren’t immediately under threat, the effects of hugging are more likely to be slow burning. When an employee’s only motivation is to collect a consistent paycheck, discretionary effort drops. They’re less productive. Engagement takes a huge hit. Over time, that gradually chips away at their well-being. “Humans want to feel useful, that they care about the work they’re doing, and that they’re investing their time well,” Eatough says. “When efforts are low, that can impact a person’s sense of value.” The effects stretch beyond the workplace, too. Frustrated and reluctant stayers can quickly end up in a vicious cycle, Klotz says, noting, “When you’re in a situation that feels like it’s sucking life out of you, you end up ruminating about how depleting it is, then end up so tired that you don’t have energy for restorative activities outside of work. So it’s this downward spiral—you begin your workday even more depleted.” Longer term, job hugging stunts growth. “When you’re looking out for yourself, rather than the team or organization, your investment in working relationships begins to break down,” Eatough says. “Over time, staying in that situation means you’re more likely to become deeply cynical, which hurts the individual and their career trajectory.” When hugging becomes clinging Feeling stuck is nothing new. At some point in their careers, most workers will be in a situation where if they could leave for a better role, they would, says Klotz, who predicted the Great Resignation. But what distinguishes job hugging is that it’s anxiously clinging to a role during unfavorable labor markets. It’s not that employees don’t want to quit—it’s that they can’t. “It’s human nature that when there’s a threat of any sort that we move away from it and towards stability,” Klotz says. “Your job represents that stability. And currently, it’s not a great time to switch jobs.” There are few options for job huggers. The first is speaking up and working with a manager to improve the situation. But this might be unlikely for employees who feel trapped or lack motivation in the first place. Klotz says cognitive reframing can help—focusing purely on the positive aspects of a draining role, such as a friendly team, and tuning out the rest. Finally, slowly backing away from extra tasks—in other words, quiet quitting—could mean workers can redraw work-life boundaries in the interim at least. Otherwise, beyond Stoic philosophy or a benevolent boss, there is little choice but to wait it out. In some cases, a job hugger may eventually turn it around, ease their grip, and become quietly content in their role. But more often, wanting to quit usually leads to actually quitting. In effect, job hugging is damage control: hanging on until the situation changes. “I think we’ll see some people be resilient, wait it out, and find another role,” Klotz says. “But there’ll be others in the quagmire of struggling with exhaustion of spending eight hours a day in a job they don’t like.” View the full article

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Endings are tricky: You want closure and to go out with a bang—which is a hard balance. It’s natural to want the end of the year to be meaningful. Even the moon appears to agree with this sentiment, and it’s about to prove it. The final full moon of 2025, which is also called the cold moon, will be a bright supermoon occurring on December 4. Before we get into how best to moon-gaze, let’s break down what that all means, and do a year-end moon review. Why is December’s full moon called the ‘cold moon’? Human beings assign names even to celestial happenings. The Old Farmer’s Almanac compiled the most commonly used monikers, based on Old English and Native American sources. December’s moon is called the cold moon because of the chilly winter temperatures. According to EarthSky, it is also known as Moon Before Yule or the Long Night Moon. What is a supermoon? The moon orbits Earth in an elliptical pattern, which means the orb has differing proximity to the planet. When the full moon lines up with the closer approach to Earth, known as perigee, a supermoon occurs. The moon appears brighter and fuller because it is physically closer to Earth. What makes this supermoon special? December’s supermoon offering is the finale of three consecutive supermoons, which also occurred in October and November this year. Because the orb will mirror the sun, December’s supermoon will also be the highest-hanging full moon of 2025. What is the moon’s 2025 recap? There were 12 full moons in 2025. (Sometimes, because of the lunar year length, there are 13, such as in 2023.) 2025’s dozen included three supermoons, two total lunar eclipses—and a partridge in a pear tree. (Well, the scientific nature of the latter is questionable . . . but ’tis the season.) How best to view the December supermoon The most dramatic time to view the supermoon is just after moonrise, because of the “moon illusion.” This phenomenon, which is when the moon appears larger when near the horizon, can’t be fully explained by science. This optical illusion of sorts, combined with the fact that the supermoon appears brighter and bigger, makes for one spectacular nighttime view. Since viewing times vary by location, use this moonrise tool to best plan your moon-gazing experience. If you miss tonight, never fear. The moon will reach its peak on December 4 at 6:14 p.m. ET, but it will appear full for a couple of days, so you have wiggle room that allows for more moon-gazing opportunities. View the full article

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It’s a tale as old as the modern workplace: In the 1960s, women entered the workforce en masse, ready to compete with their male counterparts for promotions, pay, and opportunity—only to find the system wasn’t built for them. Today, women comprise almost half of the U.S. labor force. The playing field looks different now, but the fight for equal access hasn’t gone away. It just moved into subtler territory. Companies make quiet calculations about who’s worth “investing in,” says Corinne Low, gender economist and associate business professor at the University of Pennsylvania’s Wharton School of Business. Women often face career penalties in anticipation of motherhood as employers presume they’re more likely to take leave or step back. Once in their 40s, “past” childbearing, this bias fades. But not before it’s done damage. The cost of inaction is huge: 4 out of 10 mothers in the first five years after childbirth resign. In 2025, around 400,000 mothers with young children resigned from the U.S. workforce—the sharpest decline in more than 40 years. Mothers face a training penalty that hinders their career advancement On average, data shows women working full-time only earn 83% of a man’s median annual salary. Mothers face even worse odds—their pay is often reduced by 3% for every child they have. A new study from the University of Connecticut finds that, one to three years after childbirth, women are 17% to 22% less likely to receive on-the-job training opportunities, such as seminars, workshops, and development programs, compared with a 3% to 8% decline for men who became fathers. The result is a hidden skills and promotion gap that may explain nearly a third of the motherhood wage penalty. When women have children, they’re viewed as less committed or competent, research shows—a bias that leads employers to assume mothers are too busy, distracted, or disinterested to participate in training opportunities. This is called “benevolent prescriptive stereotyping,” and it doesn’t do mothers any favors, says Joan C. Williams, distinguished professor of law emerita and founding director of the Equality Action Center at UC Law San Francisco. As Williams points out: “If you don’t get work, you eventually either get laid off because you’re not progressing, or you leave because you’re disgusted that you don’t get good work. Or you just stall out.” If a mother turns down an opportunity for training or advancement, it’s important to circle back—not to assume it’s a permanent no, says Williams. She also recommends employers keep track of who receives opportunities in their workplace—and who doesn’t. Supporting mothers isn’t a charity case Another opportunity mothers are often left out of is informal networking, like happy hours, dinners, or travel, says Kate Westlund Tovsen, founder of Society of Working Moms, a supportive community for and by working mothers. Even if a mother can’t attend, “It’s nice to be invited,” Tovsen adds, who suggests teams try daytime coffee hours as a caregiver-friendly option. Mothers are forced to be proactive, as many companies lack frameworks to support leave or reintegration, Williams cautions. She advises scheduling meetings with superiors before and after taking family leave to make a plan. And though being a new mother is a relatively short blip on a woman’s career, companies often make “permanent decisions in terms of who they’re investing in based on this kind of temporary period when women are most squeezed,” says Low. Supporting mothers is not a charity case, she argues, but a competitive edge that lets them retain talent long term. “Caregiver strategies and investments, including benefits and return-to-work programs, deliver measurable business returns,” states Jess Ringgenberg, professional certified coach and CEO of Elxir, an advisory firm focusing on caregivers in the workplace. “Companies see three to six times ROI through higher retention, productivity, and lower absenteeism” with such programs, Ringgenberg says. Replacing a mid-level caregiver comes with backfill, training, and ramp-up expenses that can reach $200,000, says Ringgenberg, or totaling twice the employee’s annual salary. But some companies are already working hard to help mothers succeed—and it’s paying off. Small and large companies finding solutions Frontier Co-op, an Iowa-based wholesaler of natural and organic products with around 580 employees, created the Breaking Down Barriers to Employment initiative, which includes an on-site childcare center, subsidized to $120 per week per child. Their childcare program enables parents to participate in training programs and developmental opportunities that might otherwise be missed, explains Megan Schulte, vice president of human resources. She says 100% of new parents returned to work after their parental leave. While Frontier Co-op eases the logistical strains of childcare, Brigade Events, a woman-owned and operated event strategy and management company in Dallas with 10 full-time employees, tackles rebuilding confidence and access for women who stepped out. The company views its mentorship and project-based work model as a form of retraining, recognizing women’s existing expertise, rather than resetting them to zero. Senior employees work on a hybrid schedule—three days from home, two in-office—to preserve collaboration while creating space for caregiving. Brigade doesn’t bat an eye at blocked calendars for a child’s doctor appointment or school event. “Our whole culture is giving grace to each other,” says April Zorsky, partner and chief creative officer. One of their policies is that mothers returning from their 16-week maternity leave take a “transition month” working at 50% capacity. This can mean working from home, setting their own schedules, and easing back in without penalty. “As moms, we feel it’s crucial to have flexibility,” says Zorksy. Larger companies can learn to be more flexible and collaborative, too, says Marissa Andrade, a veteran HR executive and former chief people officer at Chipotle. She recalls when one of her field managers chose to take a six-month maternity leave during a period of company-wide turnaround. Before she left, she requested an interim hire from the Mom Project, a digital platform that helps companies to hire skilled mothers, to support her leave. It went so smoothly that the field manager was able to reenter without missing a beat. Andrada recommends establishing employee–business resource groups. At Chipotle, one employee-created group, “The Hustle” (Humans United to Support the Ladies Experience), formed a maternity program to keep employees in the loop while on leave, and reoriented them on compliance and training updates on their return. “Don’t overlook the power of your employees as your consumer,” says Andrada. When companies invite access for mothers—to training, to support, to opportunities that just don’t reacclimate them to their roles, but get them to thrive in them—everyone wins. Mothers aren’t just reentering the workforce with confidence. Employers are retaining their talent, too. View the full article

Companies are increasingly using AI to conduct job interviews, and, according to experts in the field, the technology is leading to some impressive results. However, giving candidates the choice between an AI interviewer or a human can create bias that makes landing a job tougher for some people, according to a new report. AI is now a common part of the job application process. According to the World Economic Forum, around 88% of employers use some form of AI for initial candidate screening such as filtering or ranking job applications. But AI is also being used to conduct interviews. Currently, around 21% of U.S. companies use the technology for initial interviews. AI interviewers can give companies an edge when during the hiring process. One study found that candidates who were interviewed by an AI were more likely to land a job than candidates who were sourced by humans screening résumés: 54% of candidates interviewed by AI got the job, compared to about 29% of candidates sourced by a traditional résumé screening. Still, there is a lot to learn about how utilizing AI interviews impacts both people and firms. Brian Jabarian, a researcher at the University of Chicago Booth School of Business with doctorates in economics and philosophy, recently examined what happens to candidates when they are offered a choice between an AI interviewer and a human interviewer, which he detailed in his paper, Choice as Signal: Designing AI Adoption in Labor Market Screening. The research, which has not been peer reviewed, finds giving candidates a choice between a human and AI interview could also create a new hurdle for low-ability candidates—applicants whose skills are below the firm’s hiring threshold. Jabarian tells Fast Company that different applicants will automatically be drawn to either AI interviewers or human interviewers based on their strengths. For example, “applicants with strong language skills prefer human interviewers to highlight their English proficiency,” he says. “In contrast, applicants with strong analytical skills choose the AI interviewer to showcase their quantitative strengths.” But the choice isn’t neutral, like a candidate may expect it to be. “An applicant’s decision to be interviewed by a human or an AI agent can reveal private information about their strengths, weaknesses, or expectations for relative performance,” Jabarian writes in his paper, also pointing out that employees with high abilities benefit because companies can identify them more easily “using both the signal and the selection decision, increasing their probability of being hired.” However, it also means firms are able to more easily identify low-ability workers. Jabarian writes: “Consequently, low-skilled workers succeed less often in obtaining a job and therefore experience a welfare loss.” Essentially, by interpreting both the choice itself as well as the information from the interview, an employer’s precision increases, which doesn’t serve lower-ability candidates. Jabarian says if firms had no insight into the candidate’s choice, then all workers would have the advantage of choosing which interviewer best shows their skill set, but companies would lose out on the advantages of using AI interviewers. While on the surface giving job candidates choices about how they are interviewed seems like a solid idea, Jabarian says that in practice, it’s not quite so simple. “Before this new paper, I was really rooting for giving this choice to people because I was confused about why everyone was assuming it was just okay to impose a new technology on people in a high-stakes environment when they maybe didn’t want it,” he explains. However, now he believes it’s clear that the choice alone hurts the weakest candidates, and therefore it shouldn’t be one that is routinely offered but rather “on a case-by-case basis.” Jabarian says he expects AI interviewing to increase, particularly because it’s good for firms. Still, that doesn’t mean humans as interviewers are a thing of the past or irrelevant. AI interviewers and humans have different strengths: Human recruiters can improvise and are able to vary their interviews, while AI creates a consistent experience and is excellent at garnering information from candidates. That means adopting hybrid techniques—where humans and AI run interviews with opposing purposes—might really be the smartest and fairest way to hire. View the full article

In today’s job market, many employees are feeling the pressure. Layoffs continue to make headlines, hiring pipelines have slowed, budgets have tightened, and job seekers are facing fierce competition. For those already employed, this environment raises a tricky question: What’s reasonable to ask for at work right now—and what isn’t? There’s always the standard wish list: promotions, raises, more flexibility, and better benefits. But in a strained economy, some of these asks may be harder to land—and for many employees, even harder to ask for. Zety, a career platform designed to make job searching easier with expert-backed tools and advice, found in its latest Pay on Pause Report three in five workers are willing to forgo or accept smaller raises this year due to fears of layoffs and job instability, and 66% avoided asking for a raise altogether, citing economic pressures and uncertainty. In a job market this unpredictable, where many employees are job hugging out of fear—one question remains: should employees hold off on asking, or should conversations still be happening? There’s fear in asking According to career expert Jasmine Escalera, many employees are hesitant to ask for anything right now. The thought process is: “I should just be grateful to have a job,” or, “I don’t want to ask for more and rock the boat, especially if AI is coming in,” she explains. Maybe even, “I don’t want to disrupt what I already have, because I don’t want to then be out in that job market and not even know when’s the next time I’m potentially going to get a position,” Escalera says. In today’s job market, employees are often hesitant to speak up, hoping staying quiet will help them maintain their positions—especially since certain requests, like pay raises, are harder to secure. Pay increases and promotions may be harder to secure It is true. Certain requests are more difficult in today’s job market, Escalera explains, and pay raises are one of them. “If layoffs and budget cuts are happening, one of the first things that are going to go is pay increases,” she says. This also includes bonuses, or any other type of financial component. “Anything that goes into the budget could potentially go wrong, which is not good for individuals who are in positions where they need to be upskilling. Or they need to be learning more to complement AI, or even potentially just for specific career growth opportunities,” she says. Promotions also face limitations. As Escalera explains, “Promotions typically come with raises and professional development [or] upskilling opportunities—those are going to be things that potentially go away. Still, it doesn’t mean employees should shy away from asking, or from putting their requests on their managers radar. Open the conversation A company may not be able to provide pay raises or promotions during a downturn, but that doesn’t mean the conversation can’t happen. “Even if your company comes out and says, ‘we don’t have the financial capacity to give pay raises right now’, or ‘we don’t have the financial capacity to give bonuses right now’—that does not mean you do not have the conversation,” Escalera says. The key is approaching the discussion thoughtfully, focusing on your contributions and the value you bring. You might say, “I understand that the organization is in financial hardship, or may not be giving bonuses or pay raises at this moment, but I really want to open up the conversation around my work’” Escalera suggests. Carolyn Troyan, CEO of Leadership360, an HR consulting and leadership coaching firm, agrees it’s important to be thoughtful with your approach. “It’s doing it in an emotionally intelligent way,” she says. “After half your team has been laid off, demanding a raise is probably not such a good idea.” But after the dust has settled and the company is back on steady footing, it’s reasonable to bring it up—or even during your next performance review, if the timing feels right. When having that conversation, acknowledge the environment and what the team has been through—but don’t let that stop you from discussing your growth with your manager. “Just because a company is struggling doesn’t mean you don’t have a career plan,” Troyan says. To your manager, you might say, “Here’s what I want to do over the next two to three years, I’d love to kind of talk about that with you. What opportunities do you see available, even in this environment, for me to learn some of these new skills?” Commonly, you’re going to hear one of two responses, Troyan explains: “We really love you, but we can’t do it right now,” which comes up a lot. Or, you may receive feedback highlighting what you need to work on to reach a promotion or raise in the future. Either way, you’re still having the conversation. Support and flexibility Even if a company can’t provide a promotion or raise due to financial hardship, there are other things to ask for. One of the biggest asks right now is support—support that isn’t monetary, Escalera says, pointing to the same report: Mental health support tops the list. “What that really shows is that individuals are incredibly burnt out and stressed out,” she said. As a result, we’re seeing more requests for mental health days and other forms of support. If a company isn’t meeting requests for pay, flexibility, or other forms of support, it may be a signal for employees to reassess their options. Even in uncertain times, understanding your value, approaching conversations thoughtfully, and asking for the support you need are all things you don’t have to shy away from. View the full article

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Creating animated videos can seem intimidating, but it’s a manageable process when broken down into clear steps. First, you’ll want to plan your video by outlining your core message and writing a compelling script. Next, storyboarding allows you to visualize each scene, followed by choosing animation software that fits your skill level. Each of these steps is essential for developing a cohesive final product, and grasping them will set you up for success in your animation project. What comes next is equally important. Key Takeaways Start with a clear script and storyboard to outline your animated video’s core message and visual flow. Choose appropriate animation software based on your skill level and project needs, such as Vyond for beginners or Adobe After Effects for advanced users. Design distinct characters and backgrounds that enhance storytelling and maintain visual coherence throughout the animation. Select a harmonious color palette and ensure audio elements are balanced, syncing voiceovers with animations for a polished final product. Test your animation with feedback from screenings, refining the script and visuals to better engage your target audience. How to Plan Your Animated Video When you plan your animated video, it’s vital to start with a clear outline or script, as this will help you define your core message and structure. Begin by developing storyboards to visually break down each scene, which aids in planning camera angles and shifts that keep viewers engaged. Next, create an animatic using your storyboards and placeholder audio to assess timing and pacing before full production. Draft your voiceover narration early to clarify complex topics and streamline editing. Finally, utilize feedback from test screenings to refine your storyboards and script, ensuring your animated video effectively communicates its message. This structured approach is fundamental when learning how to create animated videos, how to create animations for YouTube, or how to create a cartoon. Writing an Engaging Script When you’re writing an engaging script, it’s essential to know your audience and outline your key messages clearly. Comprehending who you’re speaking to helps you tailor your content effectively, ensuring it resonates with viewers. Know Your Audience How do you guarantee your animated video script resonates with your audience? First, you need to know your audience. Start with comprehending your audience’s demographics, interests, and preferences. This insight allows you to tailor your script effectively. Conducting surveys or researching audience behavior can help identify the topics and tones that will engage them. Use relatable language and examples to make your script accessible. Structuring your script with a clear beginning, middle, and end assures your audience can easily follow your message. Moreover, include a strong call to action at the end to encourage interaction. By utilizing an animated video service, you can learn how to create simple animation that reflects your audience’s values and needs. Outline Key Messages To create an engaging animated video script, it’s significant to outline your key messages effectively. Start by identifying your core message to align with your audience’s interests and the video’s purpose. Next, create a logical outline that organizes your points for clear progression. Here are four vital steps to take into account: Define the main takeaway for your viewers. Break down your core message into digestible sub-points. Write in a conversational tone, using simple language and relatable examples. Incorporate visual cues to guide animation decisions, indicating moments for specific visuals. Storyboarding Your Animation Storyboarding your animation is crucial for visualizing your narrative and ensuring that each scene flows smoothly. By breaking down your script into individual frames, you can clearly outline character positions, backgrounds, and actions, which helps with timing and pacing. This structured approach not just streamlines the production process but also serves as a valuable communication tool among team members, minimizing misunderstandings before you start animating. Importance of Storyboarding As you begin an animation project, having a well-structured storyboard is crucial for success. Storyboarding helps you break down your script into individual scenes, enhancing clarity and flow in your animated corporate video. It allows you to visualize key elements, ensuring your audience remains engaged. Here are four key benefits of storyboarding: Visualizes camera angles, character movements, and shifts. Aids in creating an animatic to assess timing and pacing. Serves as a communication tool among the production team. Saves time and resources by identifying potential issues early. Using animation software or Adobe Animate video animation programs effectively can streamline this process, aligning your creative vision and ensuring a smoother production experience. Visualizing Your Narrative Creating a storyboard serves as a fundamental step in visualizing your narrative for animation projects. This visual representation breaks down your script into individual scenes, clarifying the sequence of events and actions. Each panel should include key elements such as character positions, backgrounds, and important dialogue to guarantee a clear vision. You can improve storytelling by utilizing different shot types and camera angles. Regularly revisiting and refining your storyboard throughout the animation process will help address any inconsistencies. Scene Action Key Dialogue 1 Introduce character “Hi, I’m Alex!” 2 Character moves “Let’s go on an adventure!” 3 Conflict arises “What was that noise?” 4 Climax moment “We must face our fears!” 5 Resolution “We did it together!” This process is crucial for anyone looking to create an animated character or understand how to create cartoon animation, whether you’re working with an Animaker video creation company or on your own. Timing and Flow When planning your animation, grasping the timing and flow of your scenes is crucial for maintaining audience engagement. Effective storyboarding helps visualize the sequence of events, ensuring a structured approach. Consider these key elements: Key Frames: Illustrate major actions and changes to keep viewers invested. Camera Angles: Plan various perspectives to improve storytelling. Transitions: Smoothly connect scenes for a cohesive experience. Animatic: Combine storyboards with rough timing and audio to assess pacing before production. During storyboarding, pay attention to the timing of voiceovers and sound effects. This alignment enriches the narrative and addresses pacing issues early on, streamlining your editing process and resulting in a polished final animation. Choosing the Right Animation Software Choosing the right animation software can greatly impact your project’s success, especially since various options cater to different skill levels and animation styles. If you’re a beginner, user-friendly platforms like Vyond and Animaker might be your best animation software free choices. For advanced users, tools such as Toon Boom Harmony and Adobe After Effects offer more robust features. Consider the type of animation you want; for instance, Blender thrives in 3D animations, whereas Pencil2D is great for 2D projects. Assess specific features you need, like keyframe capabilities or vector tools. Additionally, check for free animation software options and trial periods before committing, ensuring compatibility with various file formats for easy sharing on platforms like YouTube. Designing Characters and Backgrounds When designing characters and backgrounds for your animated videos, start by defining your character’s personality and traits, as these elements guide their visual identity. You can use sketching software or traditional techniques to create various iterations, focusing on poses and expressions that best represent their characteristics. For backgrounds, consider the setting and select color palettes and styles that not just complement your characters but additionally improve the overall mood of the scene. Character Design Principles In character design, it’s essential to start by defining a character’s personality and role within the story, as these elements greatly influence their visual traits. To create compelling characters, consider these character design principles: Facial Expressions: Tailor expressions to reflect emotions aligned with the character’s personality. Color Theory: Use warm colors for friendly characters and cool colors for aloof ones to evoke the desired emotional response. Silhouette and Shape: Employ distinctive shapes—round for friendly and angular for antagonistic—to visually convey character traits. Character Turnarounds: Develop a style guide that includes character turnarounds to guarantee consistency across animations. Background Creation Techniques Creating effective backgrounds is crucial for improving the storytelling and visual appeal of animated videos. Start by sketching character concepts to establish traits that resonate with your audience. Utilize animation software, like Adobe Illustrator, to create scalable designs. When designing backgrounds, make sure they complement the story’s theme, using styles that elevate the mood. Layered backgrounds are particularly useful; they allow for parallax scrolling effects, adding depth during animation. Consider whether you’re working in 2D or 3D, as this affects the complexity of your designs. Color Palette Selection Selecting a color palette is a fundamental step in designing characters and backgrounds for animated videos. A well-chosen palette improves visual cohesion and engages the audience. Here’s how to approach color palette selection: Choose 3-5 harmonious colors to create a balanced look that isn’t overwhelming. Apply color theory principles, using complementary or analogous colors to evoke emotions; for example, blue for calmness and red for excitement. Ensure contrast between characters and backgrounds so your characters stand out clearly. Utilize tools like Adobe Color or Coolors to generate palettes, ensuring consistency throughout your project. With these tips, you’ll improve your animation download and learn how to create an animation using free animation software easy enough for anyone. Techniques for Animation Animation techniques vary widely, each offering unique methods to bring visuals to life. 2D Animation Techniques focus on creating characters and settings in a flat space, often using software like Adobe Animate or Toon Boom Harmony. For a more immersive experience, you can explore 3D Animation Techniques, which utilize software such as Autodesk Maya or Blender to model characters in three-dimensional space, enhancing realism. Motion Graphics combines graphic design with animation, using tools like After Effects to craft dynamic visuals that improve storytelling. Furthermore, Rotoscoping allows you to trace over footage, frame by frame, to achieve realistic animations, often blending live-action with animated elements. Each technique serves distinct purposes, so choose based on your project’s needs. Adding Sound and Voiceovers Once you’ve established your animation through various techniques, adding sound and voiceovers becomes a crucial step in enhancing the final product. Follow these steps to effectively incorporate audio: Import your audio files into Premiere Pro and organize them in the Fundamental Sound panel for easy management. Use the audio track mixer to adjust volume levels, ensuring your voiceovers and sound effects are balanced and clear. Carefully sync your voiceover with the animated visuals by aligning audio clips on the timeline, using waveforms for precise timing. Incorporate sound effects strategically to engage viewers, making sure they complement your animation without overshadowing the voiceover narrative. Lastly, export your animated videos in the H.264 codec for peak quality and platform compatibility. Editing Your Animated Video Editing your animated video is a critical phase where you refine and improve your project to guarantee it resonates with your audience. Start by enhancing your cartoon video with sound effects, music tracks, and voiceovers using Premiere Pro’s Vital Sound panel. This allows for better audio quality control. To capture viewer attention, consider adding animated intros at the beginning. You can as well utilize animation presets and keyframe animation capabilities to create custom motion effects that align with your video’s style. Make sure to synchronize audio with animations for a polished look. This attention to detail is vital for effective editing, whether you’re using a whiteboard animation maker or learning how to animate a video from scratch. Exporting for Optimal Playback To guarantee your animated video plays back effectively across various platforms, you’ll need to evaluate several key factors during the export process. Here are four important steps for exporting for ideal playback: Codec: Use the H.264 codec for a balance between quality and file size. Resolution: Set your resolution to at least 1920×1080 pixels for Full HD clarity. Frame Rate: Choose 30 fps for standard videos or 60 fps for smoother motion, depending on your animation style. Bitrate: Target a bitrate of around 8 Mbps for 1080p videos to maintain quality without bloating file size. Always preview your exported video for audio-video synchronization issues to guarantee a polished presentation. This knowledge aids in perfecting how to make animations for YouTube with an ai animation generator from text. Sharing Your Animated Video on Social Media Sharing your animated video on social media can greatly boost its visibility and engagement, making it a crucial step in your promotional strategy. Start by choosing the right platforms; for example, use YouTube for long-form content, Instagram for short clips, and Facebook for a broader reach. Optimize your video format according to each platform’s specifications—vertical videos perform well on Instagram Stories and TikTok. Improve your post with engaging captions and relevant hashtags to enhance discoverability. Schedule your posts during peak engagement times based on analytics, as this can considerably increase views. Finally, monitor engagement metrics like views and shares to evaluate your animated video’s performance, which will inform future content strategies and help you refine how to make cartoon animation. Frequently Asked Questions How to Make an Animation Video Step by Step? To make an animation video step by step, start by defining your key message and target audience. Next, craft a compelling script that outlines your narrative. Once that’s done, create detailed storyboards to visualize each scene. Then, design characters and backgrounds that match your vision. After designing, use animation software to animate your scenes. Finally, polish your video with audio and effects before exporting it for sharing. This process guarantees clarity and engagement. How to Create a Custom Animation With Step by Step? To create a custom animation, start by brainstorming your concept and writing a detailed script. Next, develop a storyboard that outlines each scene, including actions and changes. Design characters and backgrounds using graphic software, ensuring they match your theme. Animate your designs with tools like Adobe After Effects, applying keyframes for movement and syncing with audio. Finally, review your work thoroughly, making adjustments before exporting in your chosen format. What Are the 4 Stages of Animation? The four stages of animation are conceptualization, design, animation, and post-production. In the conceptualization stage, you develop the core idea and script that guide your project. Next, during design, you create characters and backgrounds that visually represent your story. The animation stage brings these designs to life through techniques like 2D or 3D animation. Finally, post-production involves editing and adding elements like voiceovers and sound effects to refine the final product. What Program to Use to Make Animated Videos? To create animated videos, you have several superb programs to choose from. Vyond is user-friendly and offers templates perfect for business and educational content. If you’re a beginner, Animaker’s drag-and-drop features simplify the process. For advanced users, Blender provides robust 3D modeling tools. Professionals might prefer Toon Boom Harmony for its all-encompassing 2D capabilities. Finally, Adobe After Effects excels in motion graphics, allowing you to create visually striking animations with ease. Conclusion Creating animated videos requires careful planning and execution. By following the steps outlined—planning, scripting, storyboarding, choosing software, designing visuals, adding audio, editing, and exporting—you guarantee a polished final product. Each phase contributes to a cohesive narrative that effectively communicates your message. With the right techniques and tools, you can engage your audience and improve their experience. Remember, sharing your animated video on social media can broaden its reach, so consider your distribution strategy as well. Image via Google Gemini This article, "A Step-by-Step Guide to Creating Animated Videos" was first published on Small Business Trends View the full article