Last year, China saw a boom in foundation models, the do-everything large language models that underpin the AI revolution. This year, the focus has shifted to AI agents—systems that are less about responding to users’ queries and more about autonomously accomplishing things for them.  There are now a host of Chinese startups building these general-purpose digital tools, which can answer emails, browse the internet to plan vacations, and even design an interactive website. Many of these have emerged in just the last two months, following in the footsteps of Manus—a general AI agent that sparked weeks of social media frenzy for invite codes after its limited-release launch in early March.  These emerging AI agents aren’t large language models themselves. Instead, they’re built on top of them, using a workflow-based structure designed to get things done. A lot of these systems also introduce a different way of interacting with AI. Rather than just chatting back and forth with users, they are optimized for managing and executing multistep tasks—booking flights, managing schedules, conducting research—by using external tools and remembering instructions.  China could take the lead on building these kinds of agents. The country’s tightly integrated app ecosystems, rapid product cycles, and digitally fluent user base could provide a favorable environment for embedding AI into daily life.  For now, its leading AI agent startups are focusing their attention on the global market, because the best Western models don’t operate inside China’s firewalls. But that could change soon: Tech giants like ByteDance and Tencent are preparing their own AI agents that could bake automation directly into their native super-apps, pulling data from their vast ecosystem of programs that dominate many aspects of daily life in the country.  As the race to define what a useful AI agent looks like unfolds, a mix of ambitious startups and entrenched tech giants are now testing how these tools might actually work in practice—and for whom. Set the standard It’s been a whirlwind few months for Manus, which was developed by the Wuhan-based startup Butterfly Effect. The company raised $75 million in a funding round led by the US venture capital firm Benchmark, took the product on an ambitious global roadshow, and hired dozens of new employees.  Even before registration opened to the public in May, Manus had become a reference point for what a broad, consumer‑oriented AI agent should accomplish. Rather than handling narrow chores for businesses, this “general” agent is designed to be able to help with everyday tasks like trip planning, stock comparison, or your kid’s school project.  Unlike previous AI agents, Manus uses a browser-based sandbox that lets users supervise the agent like an intern, watching in real time as it scrolls through web pages, reads articles, or codes actions. It also proactively asks clarifying questions, supports long-term memory that would serve as context for future tasks. “Manus represents a promising product experience for AI agents,” says Ang Li, cofounder and CEO of Simular, a startup based in Palo Alto, California, that’s building computer use agents, AI agents that control a virtual computer. “I believe Chinese startups have a huge advantage when it comes to designing consumer products, thanks to cutthroat domestic competition that leads to fast execution and greater attention to product details.” In the case of Manus, the competition is moving fast. Two of the most buzzy follow‑ups, Genspark and Flowith, for example, are already boasting benchmark scores that match or edge past Manus’s.  Genspark, led by former Baidu executives Eric Jing and Kay Zhu, links many small “super agents” through what it calls multi‑component prompting. The agent can switch among several large language models, accepts both images and text, and carries out tasks from making slide decks to placing phone calls. Whereas Manus relies heavily on Browser Use, a popular open-source product that lets agents operate a web browser in a virtual window like a human, Genspark directly integrates with a wide array of tools and APIs. Launched in April, the company says that it already has over 5 million users and over $36 million in yearly revenue. Flowith, the work of a young team that first grabbed public attention in April 2025 at a developer event hosted by the popular social media app Xiaohongshu, takes a different tack. Marketed as an “infinite agent,” it opens on a blank canvas where each question becomes a node on a branching map. Users can backtrack, take new branches, and store results in personal or sharable “knowledge gardens”—a design that feels more like project management software (think Notion) than a typical chat interface. Every inquiry or task builds its own mind-map-like graph, encouraging a more nonlinear and creative interaction with AI. Flowith’s core agent, NEO, runs in the cloud and can perform scheduled tasks like sending emails and compiling files. The founders want the app to be a “knowledge marketbase”, and aims to tap into the social aspect of AI with the aspiration of becoming “the OnlyFans of AI knowledge creators”. What they also share with Manus is the global ambition. Both Genspark and Flowith have stated that their primary focus is the international market. A global address Startups like Manus, Genspark, and Flowith—though founded by Chinese entrepreneurs—could blend seamlessly into the global tech scene and compete effectively abroad. Founders, investors, and analysts that MIT Technology Review has spoken to believe Chinese companies are moving fast, executing well, and quickly coming up with new products.  Money reinforces the pull to launch overseas. Customers there pay more, and there are plenty to go around. “You can price in USD, and with the exchange rate that’s a sevenfold multiplier,” Manus cofounder Xiao Hong quipped on a podcast. “Even if we’re only operating at 10% power because of cultural differences overseas, we’ll still make more than in China.” But creating the same functionality in China is a challenge. Major US AI companies including OpenAI and Anthropic have opted out of mainland China because of geopolitical risks and challenges with regulatory compliance. Their absence initially created a black market as users resorted to VPNs and third-party mirrors to access tools like ChatGPT and Claude. That vacuum has since been filled by a new wave of Chinese chatbots—DeepSeek, Doubao, Kimi—but the appetite for foreign models hasn’t gone away.  Manus, for example, uses Anthropic’s Claude Sonnet—widely considered the top model for agentic tasks. Manus cofounder Zhang Tao has repeatedly praised Claude’s ability to juggle tools, remember contexts, and hold multi‑round conversations—all crucial for turning chatty software into an effective executive assistant. But the company’s use of Sonnet has made its agent functionally unusable inside China without a VPN. If you open Manus from a mainland IP address, you’ll see a notice explaining that the team is “working on integrating Qwen’s model,” a special local version that is built on top of Alibaba’s open-source model.  An engineer overseeing ByteDance’s work on developing an agent, who spoke to MIT Technology Review anonymously to avoid sanction, said that the absence of Claude Sonnet models “limits everything we do in China.” DeepSeek’s open models, he added, still hallucinate too often and lack training on real‑world workflows. Developers we spoke with rank Alibaba’s Qwen series as the best domestic alternative, yet most say that switching to Qwen knocks performance down a notch. Jiaxin Pei, a postdoctoral researcher at Stanford’s Institute for Human‑Centered AI, thinks that gap will close: “Building agentic capabilities in base LLMs has become a key focus for many LLM builders, and once people realize the value of this, it will only be a matter of time.” For now, Manus is doubling down on audiences it can already serve. In a written response, the company said its “primary focus is overseas expansion,” noting that new offices in San Francisco, Singapore, and Tokyo have opened in the past month. A super‑app approach Although the concept of AI agents is still relatively new, the consumer-facing AI app market in China is already crowded with major tech players. DeepSeek remains the most widely used, while ByteDance’s Doubao and Moonshot’s Kimi have also become household names. However, most of these apps are still optimized for chat and entertainment rather than task execution. This gap in the local market has pushed China’s big tech firms to roll out their own user-facing agents, though early versions remain uneven in quality and rough around the edges.  ByteDance is testing Coze Space, an AI agent based on its own Doubao model family that lets users toggle between “plan” and “execute” modes, so they can either directly guide the agent’s actions or step back and watch it work autonomously. It connects up to 14 popular apps, including GitHub, Notion, and the company’s own Lark office suite. Early reviews say the tool can feel clunky and has a high failure rate, but it clearly aims to match what Manus offers. Meanwhile, Zhipu AI has released a free agent called AutoGLM Rumination, built on its proprietary ChatGLM models. Shanghai‑based Minimax has launched Minimax Agent. Both products look almost identical to Manus and demo basic tasks such as building a simple website, planning a trip, making a small Flash game, or running quick data analysis. Despite the limited usability of most general AI agents launched within China, big companies have plans to change that. During a May 15 earnings call, Tencent president Liu Zhiping teased an agent that would weave automation directly into China’s most ubiquitous app, WeChat.  Considered the original super-app, WeChat already handles messaging, mobile payments, news, and millions of mini‑programs that act like embedded apps. These programs give Tencent, its developer, access to data from millions of services that pervade everyday life in China, an advantage most competitors can only envy. Historically, China’s consumer internet has splintered into competing walled gardens—share a Taobao link in WeChat and it resolves as plaintext, not a preview card. Unlike the more interoperable Western internet, China’s tech giants have long resisted integration with one another, choosing to wage platform war at the expense of a seamless user experience. But the use of mini‑programs has given WeChat unprecedented reach across services that once resisted interoperability, from gym bookings to grocery orders. An agent able to roam that ecosystem could bypass the integration headaches dogging independent startups. Alibaba, the e-commerce giant behind the Qwen model series, has been a front-runner in China’s AI race but has been slower to release consumer-facing products. Even though Qwen was the most downloaded open-source model on Hugging Face in 2024, it didn’t power a dedicated chatbot app until early 2025. In March, Alibaba rebranded its cloud storage and search app Quark into an all-in-one AI search tool. By June, Quark had introduced DeepResearch—a new mode that marks its most agent-like effort to date.  ByteDance and Alibaba did not reply to MIT Technology Review’s request for comments. “Historically, Chinese tech products tend to pursue the all-in-one, super-app approach, and the latest Chinese AI agents reflect just that,” says Li of Simular, who previously worked at Google DeepMind on AI-enabled work automation. “In contrast, AI agents in the US are more focused on serving specific verticals.” Pei, the researcher at Stanford, says that existing tech giants could have a huge advantage in bringing the vision of general AI agents to life—especially those with built-in integration across services. “The customer-facing AI agent market is still very early, with tons of problems like authentication and liability,” he says. “But companies that already operate across a wide range of services have a natural advantage in deploying agents at scale.”

From lifelike avatars to automated fan interactions, AI is remaking digital modeling. But can tech ... More scale intimacy — or will it erode the human spark behind the screen?getty The AI boom has been defined by unprecedented innovation across nearly every sector. From improving flight punctuality through AI-powered scheduling to detecting early markers of Alzheimer’s disease, AI is modifying how we live and work. And the advertising world isn’t left out. In March of this year, OpenAI’s GPT-4o sent the internet into a frenzy with its ability to generate Studio Ghibli-style images. The model produces realistic, emotionally nuanced visuals from a series of prompts — a feat that has led some to predict the demise of visual arts as we know them. While such conclusions may be premature, there’s growing belief among industry players that AI could transform how digital model agencies operate. That belief isn’t limited to one startup. A new class of AI-powered agencies — including FanPro, Lalaland.ai, Deep Agency andThe Diigitals — is testing whether modeling can be automated without losing its creative edge. Some use AI to generate lifelike avatars. Others offer virtual photo studios, CRM — customer relationship management — integrations, or creator monetization tools. Together, they reflect a big shift in how digital modeling agencies think about labor, revenue and scale. FanPro — founded by Tyron Humphris in 2023 to help digital model agencies scale efficiently — offers a striking case study. Fully self-funded, Humphris said in an interview that the company reached $1 million in revenue within its first 90 days and crossed eight figures by 2024, all while maintaining a lean team by automating nearly every process. As Humphris noted, “the companies that will lead this next decade won’t just be the ones with the best marketing or biggest budgets. They’ll be the ones who use AI, automation and systems thinking to scale with precision, all while staying lean and agile.” That explains the big bet that startups like FanPro are making — but how far can it really go? And why should digital model agencies care in the first place? Automation In Digital Model Agencies To understand how automation works in the digital modeling industry — a fast-rising corner of the creator economy — it helps to understand what it’s replacing. A typical digital model agency juggles five or more monetization platforms per creator — from OnlyFans and Fansly to TikTok and Instagram. But behind every viral post is a grind of scheduling, analytics, upselling, customer support and retention. The average agency may need 10 to 15 contractors to manage a roster of just a few high-performing creators. These agencies oversee a complex cycle: content creation, onboarding, audience engagement and sales funnel optimization, usually across several monetization platforms. According to Humphris, there’s often a misconception that running a digital model agency is just about posting pretty pictures. But in reality, he noted, it’s more. “It’s CRM, data science and psychology all wrapped in one. If AI can streamline even half of that, it’s a game-changer.” That claim reflects a growing pain point in the creator economy, where agencies swim in an ocean of tools in an attempt to monetize attention for creators while simultaneously managing marketing, sales and customer support. For context, a 2024 Clevertouch Consulting study revealed that 54% of marketers use more than 50 tools to manage operations — many stitched together with Zapier or manual workarounds. Tyron Humphris, founder of FanProFanPro But, according to Humphris, “no matter how strong your offer is, if you don’t have systems, processes and accountability built into the business, it’s going to collapse under pressure.” And that’s where AI steps in. Beyond handling routine tasks, large language models and automation stacks now allow agencies to scale operations while staying lean. With minimal human input, agencies can schedule posts, auto-respond to DMs, upsell subscriptions, track social analytics and manage retention flows. What once required a full team of marketers, virtual assistants and sales reps can now be executed by a few well-trained AI agents. FanPro claims that over 90% of its operations — from dynamic pricing to fan interactions — are now handled by automation. Likewise, Deep Agency allows creators to generate professional-grade photo shoots without booking a studio or hiring staff and Lalaland.ai helps fashion brands generate AI avatars to reduce production costs and increase diversity in representation. A Necessary Human Touch Still, not everyone is convinced that AI can capture the nuance of digital intimacy. Some experts have raised concerns that hyper automation in creator-driven industries could flatten human expression into predictable engagement patterns, risking long-term user loyalty. A 2024 ContentGrip study of 1,000 consumers found 80% of respondents would likely switch brands that rely heavily on AI-generated emails, citing a loss of authenticity. Nearly half said such messages made them feel “less connected” to the brand. Humphris doesn’t disagree. “AI can do a lot, but it needs to be paired with someone who understands psychology,” he said. “We didn’t scale because we had the best tech. We scaled because we understood human behavior and built systems that respected it.” Humphris’ sentiment isn’t a mere anecdote but one rooted in research. For example, a recent study by Northeastern University showed that AI influencers often reduce brand trust — especially when users aren’t aware the content is AI-generated. The implication is clear: over-automating the wrong parts of human interaction can backfire. Automation doesn’t — and shouldn’t — mean that human input becomes obsolete. Rather, as many industry experts have noted, it will enhance efficiency but not replace empathy. While AI can process data at speed and generate alluring visuals, it cannot replicate human creativity or emotional intelligence. Neither does AI know the psychology of human behavior like humans do, a trait Humphris credits for their almost-instant success. What’s Working — And What’s Not Lalaland.ai and The Diigitals have earned praise for enhancing inclusivity, enabling brands to feature underrepresented body types, skin tones and styles. Meanwhile, FanPro focuses on building AI “growth engines” for agencies — full-stack systems that combine monetization tools, CRM and content flows. But not all reactions have been positive. In November 2024, fashion brand Mango faced backlash for its use of AI-generated models, which critics called “false advertising” and “a threat to real jobs.” The New York Post covered the fallout in detail, highlighting how ethical lines are still being drawn. As brands look to balance cost savings with authenticity, some have begun labeling AI-generated content more clearly — or embedding human oversight into workflows, rather than removing it. Despite offering an automation stack, FanPro itself wasn’t an immediate adopter of automation in its processes. But, as Humphris noted, embracing AI made all the difference for the company. “If we had adopted AI and automation earlier, we would’ve hit 8 figures much faster and with far less stress,” he noted. Automation In The New Era FanPro is a great example of how AI integration, when done the right way, could be a profitable venture for digital model agencies. Whether or not the company’s model becomes the blueprint for AI-first digital agencies, it’s clear that there’s a big shift in the creator economy, where automation isn’t only viewed as a time-saver, but also as a foundational pillar for businesses. As digital model agencies lean further into an AI-centric future, the bigger task is remembering what not to automate — the spark of human connection that built the industry in the first place. “In this new era of automation,” Humphris said, “the smartest agencies won’t just ask what AI can do. They’ll ask what it shouldn’t.”

OnlyFans is on the selling block, according to a report by Reuters. The current owner of the adult entertainment platform, Fenix International Ltd, is in talks to sell to an investor group at a valuation of around $8 billion. This group is being led by an entity called the Forest Road Company, which is an investment firm based in Los Angeles. The platform generated $6.6 billion in revenue just in 2023, so the idea of an $8 billion payout doesn't seem that far-fetched. OnlyFans became a global phenomenon during the COVID-19 pandemic and it takes 20 percent of all creator earnings. Investor interest has peaked over the past several months as impressive earning statements became public. It has managed to triple its revenue since 2020, which is something many companies that experienced pandemic-related boosts cannot say. Sources have stated that a deal could be reached within the next week or two. However, Fenix International Ltd have also been in talks with other potential buyers. An IPO is also being considered, an idea that's been floating around since 2022. However, an outright purchase is more likely than a public offering. This is due to the porn of it all. The company tried to get around this by announcing a ban on sexually explicit content in 2021, but reversed course before the ban even went into place. OnlyFans is, after all, primarily for sexually explicit content.This article originally appeared on Engadget at https://www.engadget.com/big-tech/onlyfans-is-in-talks-to-sell-for-8-billion-165318788.html?src=rss

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OnlyFans, the internet’s kingdom of smut, may be changing hands soon. Reuters reports that the porn platform’s parent company, Fenix International, Ltd., is in talks to sell the business for some $8 billion to a U.S. investor group. The New York Post previously reported that Leonid Radvinsky, the billionaire owner of the site, was looking to “cash out,” but had not yet found a buyer. Reuters now identifies at least one potential buyer as the Forest Road Company, an investment firm based in Los Angeles that is reportedly leading an investor group that wants to buy the porn platform. On its website, Forest Road describes itself as “not your average investment firm” and says it embraces “complexity and creativity to extract value where others see limitations.” The site also expresses an interest in “media & entertainment” and “digital assets.” Not much else is known about the talks. Citing sources familiar with the potential deal, Reuters writes that Fenix is also talking to other interested parties. Gizmodo reached out to OnlyFans for more information. OnlyFans was founded in 2016 and rose to prominence during the pandemic by helping horny web users satisfy their libidos whilst otherwise avoiding human contact. Since then, the business has only continued to grow. Other than a weird brief moment in 2021 (when the company bizarrely claimed it would ban “sexually explicit content”), it has served as a premier destination for dirty content, and has helped re-shaped the porn industry through its gig-worker model. Last year, the company reported that payments made through the platform had surged by 19 percent since 2023, topping some $6.6 billion. Radvinsky purchased the company in 2019 and it has made an absolute killing since then. Bloomberg reported last year that the mogul had made $1 billion in three years through corporate dividends from the business. The company has also been the subject of considerable criticism, as well as numerous legal complaints. Critics accuse the platform of being frequented by sex traffickers, and claim that the site has also become a portal for child sexual abuse material. The company was also recently sued by two customers who were outraged to discover that they may have not been messaging with real models (creators often outsource their customer communications to third-party firms).

AI uses a whole lot of energy. Credit: Photo Illustration by Thomas Fuller/SOPA Images/LightRocket via Getty Images You've probably heard that statistic that every search on ChatGPT uses the equivalent of a bottle of water. And while that's technically true, it misses some of the nuance. The MIT Technology Review dropped a massive report that reveals how the artificial intelligence industry uses energy — and exactly how much energy it costs to use a service like ChatGPT. The report determined that the energy cost of large-language models like ChatGPT cost anywhere from 114 joules per response to 6,706 joules per response — that's the difference between running a microwave for one-tenth of a second to running a microwave for eight seconds. The lower-energy models, according to the report, use less energy because they uses fewer parameters, which also means the answers tend to be less accurate. You May Also Like It makes sense, then, that AI-produced video takes a whole lot more energy. According to the MIT Technology Report's investigation, to create a five-second video, a newer AI model uses "about 3.4 million joules, more than 700 times the energy required to generate a high-quality image". That's the equivalent of running a microwave for over an hour. Mashable Light Speed Want more out-of-this world tech, space and science stories? Sign up for Mashable's weekly Light Speed newsletter. By clicking Sign Me Up, you confirm you are 16+ and agree to our Terms of Use and Privacy Policy. Thanks for signing up! The researchers tallied up the amount of energy it would cost if someone, hypothetically, asked an AI chatbot 15 questions, asked for 10 images, and three five-second videos. The answer? Roughly 2.9 kilowatt-hours of electricity, which is the equivalent of running a microwave for over 3.5 hours.The investigation also examined the rising energy costs of the data centers that power the AI industry. The report found that prior to the advent of AI, the electricity usage of data centers was largely flat thanks to increased efficiency. However, due to energy-intensive AI technology, the energy consumed by data centers in the United States has doubled since 2017. And according to government data, half the electricity used by data centers will go toward powering AI tools by 2028.This report arrives at a time in which people are using generative AI for absolutely everything. Google announced at its annual I/O event that it's leaning into AI with fervor. Google Search, Gmail, Docs, and Meet are all seeing AI integrations. People are using AI to lead job interviews, create deepfakes of OnlyFans models, and cheat in college. And all of that, according to this in-depth new report, comes at a pretty high cost.Disclosure: Ziff Davis, Mashable’s parent company, in April filed a lawsuit against OpenAI, alleging it infringed Ziff Davis copyrights in training and operating its AI systems. Topics Artificial Intelligence Christianna Silva Senior Culture Reporter Christianna Silva is a senior culture reporter covering social platforms and the creator economy, with a focus on the intersection of social media, politics, and the economic systems that govern us. Since joining Mashable in 2021, they have reported extensively on meme creators, content moderation, and the nature of online creation under capitalism. Before joining Mashable, they worked as an editor at NPR and MTV News, a reporter at Teen Vogue and VICE News, and as a stablehand at a mini-horse farm. You can follow her on Bluesky @christiannaj.bsky.social and Instagram @christianna_j.

"I can't imagine I'm the first, and I'm definitely not the last."Face RipoffAn OnlyFans creator is speaking out after discovering that her photos were stolen by someone who used deepfake tech to give her a completely new face — and posted the deepfaked images all over Reddit.As 25-year-old, UK-based OnlyFans creator Bunni told Mashable, image theft is a common occurrence in her field. Usually, though, catfishers would steal and share Bunni's image without alterations.In this case, the grift was sneakier. With the help of deepfake tools, a scammer crafted an entirely new persona named "Sofía," an alleged 19-year-old in Spain who had Bunni's body — but an AI-generated face.It was "a completely different way of doing it that I've not had happen to me before," Bunni, who posted a video about the theft on Instagram back in February, told Mashable. "It was just, like, really weird."It's only the latest instance of a baffling trend, with "virtual influencers" pasting fake faces onto the bodies of real models and sex workers to sell bogus subscriptions and swindle netizens.Head SwapUsing the fake Sofía persona, the scammer flooded forums across Reddit with fake images and color commentary. Sometimes, the posts were mundane; "Sofía" asked for outfit advice and, per Mashable, even shared photos of pets. But Sofía also posted images to r/PunkGirls, a pornographic subreddit.Sofía never shared a link to another OnlyFans page, though Bunni suspects that the scammer might have been looking to chat with targets via direct messages, where they might have been passing around an OnlyFans link or requesting cash. And though Bunni was able to get the imposter kicked off of Reddit after reaching out directly to moderators, her story emphasizes how easy it is for catfishers to combine AI with stolen content to easily make and distribute convincing fakes."I can't imagine I'm the first, and I'm definitely not the last, because this whole AI thing is kind of blowing out of proportion," Bunni told Mashable. "So I can't imagine it's going to slow down."As Mashable notes, Bunni was somewhat of a perfect target: she has fans, but she's not famous enough to trigger immediate or widespread recognition. And for a creator like Bunni, pursuing legal action might not be a feasible or even worthwhile option. It's expensive, and right now, the law itself is still catching up."I don't feel like it's really worth it," Bunni told Mashable. "The amount you pay for legal action is just ridiculous, and you probably wouldn't really get anywhere anyway, to be honest."Reddit, for its part, didn't respond to Mashable's request for comment.More on deepfakes: Gross AI Apps Create Videos of People Kissing Without Their ConsentShare This Article