ChatGPT’s Latest Upgrade Isn’t Just a New Model. It’s What Free Users Can Do Without Limits

OpenAI, aware of the ever-increasing role ChatGPT is playing in people’s lives, has tweaked something that will benefit millions on a daily basis: it’s upgraded the default version of the chatbot for free users. And while the new improved GPT-5.6 Luna model will be great, the most important benefit is another new feature: unlimited text-based chats for free users. This could dramatically open up how people use ChatGPT. In its blog post announcing the changes, OpenAI pointed out that there are still a few constraints in place for free unlimited access. While you can query the chatbot using text-based questions as much as you like, and receive the resulting text-based answers, if you’re asking the chatbot to analyze a file, or input an image or voice as a query, there are still limits for free users. Similarly, limits remain if you’re asking the AI to generate an image, and a few other higher-power features. It’s worth keeping in mind that the complex computer power needed to process a user’s chatbot query burns through resources that cost OpenAI money. Giving users free unlimited access to the core AI features is thus a risk for the AI maker, because it will consume a variable percentage of the available resources. It’s a smart move to control this risk by limiting how free users can use the models. Meanwhile, the unlimited access may encourage people to use the AI in more meaningful ways, and more frequently, which will certainly tempt a share of users on the free tier to pay to upgrade their membership so they can access the AI’s full capabilities. Unlimited queries alone would be a great perk for free tier users, but OpenAI is also upgrading the default AI model to its GPT-5.6 Luna system, which it promises is a major improvement because responses containing factual errors are rarer for this system. In fact, the AI maker says that responses with errors are about 62 percent less common than the previous model (GPT-5.5 Instant). Users who pay for the Go tier, costing $8 a month, will gain these upgrades too, along with allowances for more messages with tools, more uploads, more image creation and more voice chats without busting through limits. Go users will also get free unlimited text chats. And both Go and free tiers will get a button that instructs the tool to think more deeply about answering (which may take more time). The higher Plus and Pro tiers (starting at $20 a month and $100 a month, respectively) actually get a better version of the default model, GPT-5.6 Sol. OpenAI says this tool is better at delivering tightly-focused answers with less unnecessary formatting. It also has a more level tone across multiple types of conversation, and it’ll make fewer mistakes because it’s better at accessing source material to look up details. What’s the practical upshot of these upgrades? The whole world may breathe a sigh of relief at the upgrade to GPT-5.6 Luna. In its press push for these improvements, OpenAI explained that one billion people use ChatGPT every week. An email from an OpenAI spokesperson noted that the Luna upgrade also brings “major improvements in factuality to the majority of people who use ChatGPT.” Given the carefree way that many people use this tool for generating content they share online, on social media or for work purposes, the model having an improved grip on facts may lead to less misinformation from hundreds of millions of people. Fewer erroneous answers also will benefit businesses that let their staff use ChatGPT in the workplace. As does unlimited access to text-based queries: for companies on a tighter budget, this could even turbo-charge how you use AI to polish processes and free up worker time for meaningful tasks. Companies who pay for their workers’ ChatGPT access will get still more powerful tools, and an improved experience which has clear benefits. The changes also remind us that things change quickly in the AI world, and companies that are comfortable with using the tech need to pivot quickly to keep up with the fast-evolving tools. AI-savvy CEOs will also see these tweaks to the market-leading AI as a reminder that they need to upgrade their staff training on how to best use AI, along with guidelines on which company data is and isn’t appropriate to share as part of their unlimited queries. BY KIT EATON @KITEATON

With Just 5 Words, OpenAI’s President Admitted the Problem With the New ChatGPT App

Confused about the new ChatGPT desktop app? OpenAI president Greg Brockman thinks it’s messy, too. Brockman addressed the app’s unintuitive user interface in a wide-ranging interview with tech journalist Joanna Stern, released on YouTube this Wednesday. Stern pointed out that the app was “kind of a mess,” and Brockman echoed her, saying, “it’s kind of a mess, we agree.” OpenAI launched a do-it-all app on July 9, transforming what was formerly the ChatGPT app into an everything app, merging it with their standalone coding agent app, Codex, and introducing a “Work” mode alongside “Chat” and “Codex.” The app formerly known as “ChatGPT” became “ChatGPT Classic,” which only has the chat mode. At launch, users struggled to understand the difference between the Chat and Work options, and were frustrated by how unintuitive it was to switch between the different modes. “I am so confused right now,” wrote tech writer and investor M.G. Siegler in a post titled “The ChatGPT ‘Super App’ Sort of Super Sucks.” The next day, Codex engineering lead Thibault Sottiaux acknowledged user complaints in an X thread, and on July 16, OpenAI updated the desktop app with a clearer way to switch between Chat, Work and Codex. But navigation is still not intuitive. The app now has a “Chat/Work” toggle at the top of the app, but to select the Codex mode for coding work, users have to navigate to a drop-down menu on the left sidebar to choose between “ChatGPT” and “Codex.” The default mode is also not consistent across the desktop and web apps. The desktop app defaults to “Work” but the web interface defaults to “Chat,” while “Work” on the web is only available for Pro plans. “I’m almost afraid to ask but… in the web interface, what on earth is the difference between chatgpt ‘work’ and ‘chat’ mode?” posted Lucas Beyer, Meta researcher and ex-OpenAI employee, on X. “Asked ChatGPT Work to summarize it for you (and agree the UI should tell you this directly and you shouldn’t have to come here to ask),” replied Codex engineering lead Thibault Sottiaux. “ChatGPT Work is optimized for work!” Sottiaux and OpenAI describe Work as intended for longer, multi-step tasks where “agents” plan and carry out tasks more autonomously, such as generating research reports. Work follows Codex usage structure, so can draw down more tokens than Chat. OpenAI product engineering lead Akshay Nathan also said this week that ChatGPT tries to push users to the “Work” mode if they are creating a spreadsheet. In his interview with Stern, Brockman said he expects they will phase out the Work tab by the end of the year. “We were hoping to land with zero tabs,” he admitted in the interview. “But I definitely think that by end of year there should be no work tab. You know, that this will be something that will just seamlessly mold into ChatGPT.” In the meantime, don’t ask Brockman to call it a super-app. “We actually don’t really use the word super-app,” he told Stern. “I regret that [it] has become the term of art,” he said with a laugh. BY JULIE LEE

Nvidia Just Bet $5 Billion on an AI Startup Most People Have Never Heard Of. Here’s Why

Nvidia, the world’s leading AI chipmaker, just announced it’s investing $5 billion dollars—a giant chunk of money by any reasonable measure—into a smallish AI startup that most people probably haven’t heard of. It’s an outfit called Safe Superintelligence, SSI for short, based in Palo Alto, California and Tel Aviv, Israel. The investment could nevertheless be hugely important for a number of reasons relating to the future of AI tech. Here’s what’s going on. What is Safe Superintelligence? SSI was founded only in mid-2024, and its co-founder and CEO is Ilya Sutskever, formerly OpenAI’s chief technology officer. Sutskever created a fuss when he left OpenAI because he’d been intimately involved in bringing ChatGPT to the world, and was leading the AI’s alignment team. This part of OpenAI was critical, especially at the time, because it had one main job: making sure that as OpenAI’s products got more sophisticated they aligned with humankind’s needs, rather than evolving into a threat. Sutskever’s departure led to some serious questions about OpenAI’s good intentions when developing future AI models—a debate that’s still bubbling away today, as OpenAI’s Sam Altman stirs the pot by announcing he feels we’re already in a powerful singularity moment. Safe Superintelligence is actually about more than just building AI chatbots like Siri or ChatGPT. The clue’s in the name: it’s not just about intelligence—it’s trying to make “superintelligence.” This, experts have long suggested, is an AI capable of out-thinking even the most agile human mind, in pretty much any area you can imagine. The company’s own website says this may be “the most important technical problem of our time” and it “is our mission, our name, and our entire product roadmap, because it is our sole focus.” Rather than developing ever-smarter AIs and then bolting on safety and security, SSI is developing AI and safety “in tandem, as technical problems to be solved through revolutionary engineering and scientific breakthroughs.” News like the recent international ban of Anthropic’s Mythos 5 model by the U.S. government for national security reasons, and the fact that an OpenAI model went rogue, escaped and then attacked a rival’s AI systems with a hack, show how important safe AI development is becoming. For superintelligent AIs, safety is clearly going to be even more important. SSI has been in and out of the headlines since its founding because although it’s raised sizable investments (topping $3 billion in total by late 2025,) it has yet to release any kind of meaningful product. The new $5 billion from Nvidia, its biggest financial injection yet, has resurfaced many questions about the company. Why does the investment matter? The mammoth investment is a sign that Nvidia, which by many accounts makes the world’s leading AI chips, is interested in a safe future for AI, and that it’s thinking beyond the current AI chatbot paradigm and has an eye on the next generation of superintelligent systems. As part of the deal, SSI will also gain access to Nvidia’s Vera ​Rubin chips. These are next-generation chips that are even more sophisticated than the company’s Blackwell chips, which stirred plenty of media attention when they were revealed in 2024. For certain key processes needed to make AI calculations, the new chips may be between two and five times faster than the Blackwell chips. This kind of raw power should speed the development of SSI’s AI systems significantly. In a press release, Nvidia also revealed the investment and technology deal goes both ways. It noted that the “two companies will also collaborate on the technical advancement of NVIDIA’s current and future compute platforms, leveraging SSI’s unique insights into the future of AI.” This implies that SSI has made powerful and useful progress that Nvidia executives have seen, and they want to make the most of SSI’s developments to keep their own company at the cutting edge of AI. The release quotes Nvidia CEO Jensen Huang, who praised Sutsever’s expertise and “fundamental breakthroughs at the foundation of modern AI.” He went on to say he was “excited to see what new breakthroughs SSI will discover powered by our Vera Rubin platform.” Why should you care about this? The news won’t directly impact the way you use AI in your own company. But it may remind you that current-generation AI tech isn’t inherently safe or trustworthy. Use these tools in the wrong way, and you could make a disastrous financial decision because of false information an AI told you, for example; or, a third party AI company may leak sensitive data your own staff have shared with an AI tool (as just happened with Anthropic’s Claude model). But the idea of superintelligent AI tools should be a part of your long term business plans. If you’re finding today’s AI tools helpful in building your business, you shouldn’t sleep on the innovative AI models that the future promises. Constantly checking to see if AI matches your needs could become a new business norm. BY KIT EATON @KITEATON

AI Has Freed Interns From Grunt Work. Now Companies Have a New Problem

Internships have long been considered a valuable steppingstone toward future full-time jobs, often because many companies hire people they previously mentored. But a number of recent workplace trends—notably increasing business deployment of AI tools—are creating new challenges for many younger apprentices as they seek to effectively learn the corporate ropes. Frequently, those changes are leaving interns with little or even none of the administrative grunt work they’d been traditionally given, and which AI applications have now automated. Even if that sounds like a good thing, it can strand many trainees in what business consultancy Korn Ferry called “a new kind of boredom.” In an effort to respond, companies are now assigning novice workers weightier workplace responsibilities they haven’t been trained to assume and are often terrified to take on. Consider it a feast-or-famine scenario for post-AI workplace apprenticeships. Under it, the workflow management and decision-making skills interns previously learned through repetitive and boring administrative tasks are being swapped for far more consequential roles usually reserved for more seasoned employees. “Thanks to AI, the drudgery that typically accompanies an internship—data entry, report drafting, meeting tracking—is being replaced by a different kind of cognitive burden that requires more fact-checking than judgment or critical-thinking,” a Korn Ferry blog post on the change said. “Companies expect [interns] to arrive fully proficient in AI so that they can spend more time developing their problem-solving and other human skills.” Unmentored interns The problem with this shift isn’t merely the bigger risks and higher costs of trainees stumbling while making decisions previously reserved for experienced staff. Interns may also lack the ongoing supervision they’d previously benefitted from, in part because of the effects of now common remote working arrangements or the manager-depleting effects of hierarchy “flattening” strategies. Indeed, a survey by the National Associations of Colleges and Employers (NACE) found nearly 20 percent of 2025 interns said they didn’t have a mentor, “which is a key anchor point to and sounding board for an organization.” Having a mentor is also critical in preventing trainees from being too terrified to make the decisions they’ve been assigned, or making costly errors after plucking up that courage. Alternatively, in many cases where workplace mentors were either never or infrequently present, novice workers were told to carry out work using the same AI bots that had already automated the administrative tasks earlier generations fulfilled. A far duller form of that came with younger trainees being instructed to monitor output of those apps—essentially an updated form of earlier grunt work that now keeps watch for slop the tech produces. Why should the shifting skills and experiences interns are learning be of concern to employers? According to Korn Ferry, a big reason is that companies frequently recruit the same young people they’ve helped train. Its post said last year that fully 63 percent of former interns received a full-time job offer from either employers they apprenticed with, or other companies that appreciated those training efforts. Fully 89 percent of businesses say they rely those programs on to identify future full-time employees, with NACE data showing nearly half of internship veterans received at least one employment offer before graduating from college this year. Internship programs need a big AI update Meanwhile, the size of the talent pipeline is huge, with an estimated 3 to 4 million people interning for U.S. companies each year. That flow of trainees is becoming an even bigger recruitment focus for businesses, now that AI has eliminated many traditional entry-level jobs for college graduates don’t have similar hands-on experience. But as important as internship programs have become, employers need to revise and refocus them in order for both youthful participants, and the employers themselves, to continue getting maximum benefits from them. With apps and AI replacing the administrative tasks trainees previously performed, businesses must find a middle ground between the contrasting alternatives many have adopted in the post-AI era. That means enriching roles situated somewhere between vetting chatbot output for slop, and the often terrifying responsibility of making decisions typically reserved for managers. “Firms are going to have to be more deliberate about teaching and coaching the skills they actually want interns to develop,” Mark Royal, a Korn Ferry senior client partner who specializes in employee engagement, said in the blog post. That means employers should focus less on the immediate, pragmatic concerns about assigning interns whatever work remains available that AI hasn’t taken over yet. Instead, they need to aim for the longer, strategic objective of identifying the tasks, experiences, and roles that will shape the kind of young workers they’d be eager to hire as employees. “Internships aren’t really about the output,” said Jerry Collier, leader of Korn Ferry’s EMEA assessment and succession practice. “They’re supposed to be about developing people.” BY BRUCE CRUMLEY @BRUCEC_INC