Why China’s New AI Model Has Silicon Valley and Washington on Edge

A little more than a year-and-a-half after China‘s DeepSeek put fear in the hearts of U.S. AI companies, another Chinese model has been released that further narrows the gap between Chinese and the most advanced U.S. systems. Chinese startup Moonshot on Friday unveiled Kimi ​K3. It’s an open-weight model, meaning developers can access, study, and build on top of its architecture and users can download, run, and customize the underlying systems, unlike ​closed-source models most commonly used in the U.S. Moonshot claims Kimi K3 surpasses top systems from both OpenAI and Anthropic in some benchmarks (though it falls short of Claude Fable 5 and GPT 5.6 Sol on overall performance). Kimi K3 is the largest AI model to come from China to date, with 2.8 trillion parameters, a figure that refers to the size of its neural network. And AI experts are saying it could signal a tipping point in the industry. “Kimi K3 may be an important inflection point for AI,” wrote Gavin Baker, managing partner at investment firm Atreides Management, in a social-media post. “A world where there are only [two to three] dominant frontier labs with 90 percent inference margins is net negative for every other layer while being awesome for those [two to three] labs.” It took just a few hours for Kimi K3 to jump to the leader position in the Frontend Code Arena, a live evaluation and benchmarking platform that tests how well artificial intelligence models generate user-facing web applications. That marked the first time a Chinese model had taken that spot, which sounded alarms among tech and political leaders. Some say this bolsters the argument many AI evangelists have been making against guardrails on American AI companies. “This is concerning,” wrote David Sacks, the general partner and co-founder of Craft Ventures who previously served as the White House AI and crypto czar. “America is tying itself in knots: politicians and bureaucrats are banning new data centers, piling on state regulations, and pushing for new federal agencies to pre-approve frontier models. This is how you lose the AI race. The rest of the world won’t play by our rules if we bog ourselves down.” Kimi K3’s launch came less than a month after Anthropic’s Fable and Mythos models were withdrawn by the U.S. government due to security concerns. Seeking dominance Kimi K3 represents a threat to the U.S. attempts to secure dominance in the AI world. Federal officials have laid out an AI Action Plan, which calls for accelerating innovation, building massive domestic data center infrastructure, and leveraging advanced AI for national security. Aside from national security concerns, there are financial factors at play. Three major AI companies are in various stages of going public. SpaceX (which contains Elon Musk’s AI company) made its Wall Street debut just over a month ago, with the largest IPO in Wall Street’s history. (Shares have since fallen 22 percent from their first trade price and are currently below the IPO price.) OpenAI and Anthropic, meanwhile, have both filed confidentially with the Securities and Exchange Commission as well, though neither has announced a fixed date yet. (Anthropic is currently scheduling investor meetings and is said to be targeting a possible October IPO, while OpenAI is said to be considering waiting until next year.) There have also been whispers of the government taking an equity stake in AI companies, though nothing has been decided. Chinese AI firms, though, have been releasing new models at an increasingly faster pace. Last month, for instance, Chinese AI startup Z.ai released its new flagship model, GLM-5.2, whose benchmarks narrowly trailed closed-source models. That model operated at roughly 17 percent of the cost of closed U.S. models, raising fears that U.S. companies could use a Chinese-created model, rather than a domestic one. Analysts at the time believed China’s AI models were four- to six-months behind the top models in the U.S. but were forced to reevaluate those thoughts. Kimi K3 appears to narrow the gap further and heightens fears that China may not only be catching up with U.S. AI companies, but could one day surpass them. “Despite persistent hardware/compute capacity constraints in China, K3 demonstrates that pre-training scaling, paired with architectural innovation, can still deliver step-change gains for flagship Chinese models,” said Bank of America in a note led by Alex Liu. BY CHRIS MORRIS @MORRISATLARGE

Nvidia’s Jensen Huang Just Declared the ‘Next Frontier’ of AI—and It’s Not Chatbots

They may not have been delivered with the sonorous tones of Star Trek’s William Shatner or Patrick Stewart speaking over the show’s iconic intro, but when Nvidia’s CEO Jensen Huang talked about the “frontier” of AI this week, his words still carried significant weight. That’s because AI is seemingly everywhere and in everything at the moment, and Nvidia‘s chips are on a (much longer than five year) mission to power as much of the revolution as possible. Huang was technically unveiling a new AI model—which you may think is not really news in a time when new AI models are popping up like weeds through cracked pavement. But the new Cosmos 3 Edge model Nvidia revealed is something different. It’s a “world model.” Speaking in Japan, Huang’s comments were aimed partly at the nation where Nvidia is creating a coalition with some of the biggest tech manufacturing names, but they’re also a significant sign about where AI is going in the near future: into robots. “The next frontier of AI is in the physical world,” Huang said in a statement, adding that the coalition being created to tap physical AI is a “once-in-a-generation opportunity for Japan.” He noted that, in many ways, “Japan invented modern manufacturing,” and as he sees it, the country now has an “opportunity to reinvent it for the age of intelligent industries.” But Huang’s words will echo far beyond Japan’s borders. While OpenAI, Anthropic, and other players in the game release large language models to power their linguistic-centered AI tools, Cosmos 3 Edge is designed to help systems perceive and then navigate and manipulate physical environments in real time, CNBC reported. This kind of “world model” takes in very different types of data to the often text-centric material used in AI chatbot training, technically teaching the AI physical details about things in our human world. In a press release, Nvidia claims Cosmos “combines vision reasoning, world generation, and action prediction.” It’s all about understanding and generating “text, images, video, ambient sound and actions with leading physics accuracy.” The goal is to allow robots to maneuver in the real world and manipulate items they encounter. Think of a world model as a kind of enhancement of the AI that gives Teslas their real-time self-driving powers. Robots—be they humanoid or more purpose-designed, like welding bots in car factories—will need this kind of understanding if they’re to move into our workplaces and homes in a safe way, and if they’re to have the ability to take on different jobs they’re assigned in real time. This is where the Cosmos 3 Edge gets its name, because it’s designed to do “real-time inference at the edge.” This means that significant AI processing will happen inside robots, at the “edge” of the digital network they’re connected to, allowing the robot to, for example, predict which way something that it throws will go. Why should you care about this? Robotics company 1X recently revealed a spectacularly dexterous robot manipulator it had created for its humanoid bots. The new hand is capable of unsettlingly human-like movements, and is both delicate and precise enough to pick grapes from a bunch or to speedily manipulate a gaming controller. In its press release, 1X suggested that human-like hands were one of the last barriers to allowing robots to work in human workspaces, and that the only limit left was the sophistication of the AI code. Huang proclaiming physical AI as the “next frontier” his tech giant company is going to conquer is another giant sign that the robotic revolution may be arriving much sooner than you think. Remember, ChatGPT only really arrived in late 2022… and now sophisticated AI tools are everywhere online. If your company’s plan for the next couple of years doesn’t involve robots, that’s probably fine, but you may want to get your planning team thinking about how robots will be working for you inside five to 10 years. BY KIT EATON @KITEATON

Google’s Head of Search Shares 3 Rules Every Business Needs to Win in the AI Era

Google Search has undergone some serious changes that will likely have big implications for how businesses present themselves online—and how people find them. Google VP of Search Liz Reid says there are no quick tips to hack the system, but she does explain there are techniques that entrepreneurs and business-owners can use to optimize their digital footprint for AI search. Hint: it’s all about quality. When Reid took stage at the tech company’s annual developer’s conference in May, she spelled out her vision for a brand new world of Google Search. She touted the biggest change to Google’s iconic search bar in 25 years. That included baking AI into the search experience through conversational language search interface, contextual search history, and even search with video and images. She also teased agentic features that are still only slowly rolling out to select users. Given the fact that AI Mode rolled out in 2025, these changes are hardly the first to rock Google search in recent years. Entrepreneurs may be understandably confused about how best to optimize their online presence, as AI changes the game for keywords and SEO. Despite all these changes and perhaps a bit of confusion, there are still some best practices to keep in mind. Reid sat down with Inc. to share her advice for getting the best results out of Google search for your company. Go deep and niche Reid says the recent changes to Google Search have resulted in a higher overall volume of queries and a change in their nature. The incorporation of generative AI into Google Search means people are ditching keywords in favor of questions that are phrased the way they might actually ask them. They are getting specific, providing context, and asking follow-up questions. Because users are able to get more detailed about their questions and preferences, Reid says this new behavior offers a real opportunity for companies to seize upon what makes their product or expertise unique. She gives the example of searching for shoes, which in the era of keyword search may have weighted many shoes equally. Now users can specify that they want “eco and sustainable shoes,” made by a founder with certain specifications, Reid notes. “Now this opportunity for people to differentiate themselves and shine becomes much more possible than if you could have done it before with keywords,” she says. Of course, that means business owners have to work that individuality into content on their own websites, online storefronts, and social media. Make content with value Reid encourages entrepreneurs not only to identify what makes them unique, but create value around that. In e-commerce, that might mean uploading more detailed product information to Google’s Merchant Center, and including nuanced descriptions of products on a company’s website. For a service-based business, that can mean focusing on thought leadership through mediums like podcasts, articles, and blogs that dig deeper than surface level information people may already be able to find in a Google AI overview. “Sometimes you’ll have a bunch of sites in which they’re basically saying the same thing as 500 other sites. That’s not going to go,” she says. “People would rather go and see a site that doesn’t say this exact same thing as AI overviews, but now takes it down to a much deeper level.” And, of course, Reid says, content has to be interesting: “It’s not going to rank well if when people click on it, they hate it, and they leave right away. So the first thing you should figure out is, would anyone want to read it?” Be wary of GEO claims SEO, or search engine optimization, has quickly given way to what’s being called GEO, or generative engine optimization. And a number of businesses have already been built on the claim that they’ve unlocked the secret to GEO. Reid says entrepreneurs should be skeptical of such claims and check out Google’s own resource with best practices to help people optimize for generative AI. The site notes that SEO rules still apply, and offers more detail on what high quality content actually means. It also includes “myths” about AI search, including that websites must have machine readable .txt files, content written especially for AI, or specially structured data. “I would definitely encourage people to use the tips and to express some skepticism in what they’re reading from some folks, especially if there’s business incentives for them to claim they can solve all your problems,” she says. BY CHLOE AIELLO @CHLOBO_ILO

The Best Leaders Aren’t Replacing Employees With AI, They’re Empowering Them

For years, you’ve been told that artificial intelligence is coming for your job. Silicon Valley insisted automation would replace millions of workers. Now, the people who pushed that narrative are changing their message, and that shift could reshape how you think about technology at work. OpenAI chief executive Sam Altman and other prominent tech leaders are completely abandoning the doomsday narrative. They have realized that terrifying your workforce is a terrible way to scale an enterprise. When your employees constantly fear for their livelihoods, operational momentum stalls, engagement drops, and your best talent starts looking for the exit. To protect your company and accelerate your growth, you must completely flip your internal messaging. You need to frame these new tools as massive productivity multipliers that make your people indispensable instead of replaceable. Here are three critical leadership lessons to help guide your team through this technological transition. 1. Stop selling fear and start selling execution power. If you tell your staff that an algorithm can do their jobs faster and cheaper, you immediately destroy all psychological safety in your organization. Workers who feel threatened will actively resist adopting the expensive new tools you just purchased. Instead of framing automated software as a replacement for human talent, you must position it as an upgrade for human potential. Show your team exactly how automation eliminates their most tedious administrative tasks so they can focus on high level strategy and creative problem solving. According to recent Gallup workplace data, broader technology adoption among employees is strongly associated with having active managerial support that focuses on strategic integration. 2. Ditch top-down decrees for internal champions. You cannot force true innovation through an executive mandate. Many white collar workers remain deeply skeptical of the automated tools their employers roll out. If you send a company-wide email demanding immediate compliance with a new system, your team will only use the tool when you are actively watching them. People inherently resist mandates that are forced upon them. To build a truly innovative culture, your adoption strategy must rely on organic influence rather than executive pressure. Look closely at your team and identify the employees who are already experimenting with these tools on their own time. You must empower these enthusiastic early adopters to train and encourage their peers. When a highly skeptical employee sees a trusted colleague using new software to finish a project early and leave the office on time, they will eagerly ask for a tutorial. Peer influence will always be your most effective strategy for managing corporate change. 3. Protect human ownership of the final output. The goal of implementing automation is never to turn your employees into passive observers. If your team members become completely dependent on algorithms to think for them, the quality of your business output will rapidly decline. As a leader, you must remind your workforce that human judgment remains your ultimate competitive advantage. Encourage your team to question automated summaries, challenge algorithmic data, and inject their own unique perspectives into every project. True productivity happens when human creativity directs the technology, not the other way around. The ultimate leadership takeaway The companies that thrive in this new era will not be the ones with the most advanced algorithms. They will be the ones with the most empowered humans. Your primary job as an entrepreneur is to build a culture where technology serves your people. Stop predicting the end of human labor and start building a workplace where your team feels truly irreplaceable. EXPERT OPINION BY ASH KUMRA