Top AI companies have discussed creating their own standards body

Anthropic, Google and OpenAI have discussed creating an AI industry standards body, people familiar with the situation told CNN. The conversations preceded the events of the past week, when a former Anthropic researcher resigned, saying the top AI companies were not “behaving responsibly” – and also before Anthropic CEO Dario Amodei proposed embedding third party watchdogs at AI companies. The Information first reported on the conversations. According to those familiar with the situation, the catalyst for the discussions was a July essay written by Google DeepMind founder Demis Hassabis, who proposed a US-led Standards Body modeled on the Financial Industry Regulatory Authority. The standards body, Hassabis argued, should test advanced AI models before deployment. Hassabis said the body should be a public-private partnership, overseen by the government but funded by the industry and staffed by “independent leading technical experts and open-source representatives.” The conversations are ongoing, one of the people said, and they are continuing with or without the Trump administration. In July, shortly after Hassabis publicized his proposal, Bloomberg reported Treasury Secretary Scott Bessent was considering a FINRA-like independent regulatory agency for AI that would report to the Securities and Exchange Commission. Not all tech leaders are on board. Meta CEO Mark Zuckerberg reportedly advised President Donald Trump against the idea in a phone call this summer, Politico reported earlier this month. Representatives for Google, OpenAI and Anthropic either declined to comment or did not respond to requests for comment. There are currently few industry standards or regulations for AI models and how they’re tested. Concerns over the safety of AI models and their lab tests have been raised after several incidents this summer where AI agents went rogue during testing. In the most severe case, OpenAI agents escaped their testing environment and hacked into another company’s systems to cheat on a cybersecurity test. The White House has an opaque system in place where AI companies can voluntarily submit their latest models for government review up to 30 days before they are publicly released. But the eligibility requirements for models or the process of the review has not been publicized. Late last month, a White House official told CNN the administration “continues to work with industry stakeholders on the implementation of the framework.” The AI companies say they want better standards. “I believe that shared safety standards and international coordination on further AI development need to be priorities now,” OpenAI chief scientist Jakub Pachocki told reporters at a briefing earlier this month. When asked what progress had been made on an industry wide standards body, Pachocki said they had been talking “to some external organizations about potential concrete standards we could put in place,” and that they’d have more to share “in the next months.” OpenAI CEO Sam Altman said in a late Sunday night post they “look forward to collaborating with our colleagues across the industry to formulate the best version” of industry standards. House Speaker Mike Johnson told CNN’s Jake Tapper on Sunday there’s little consensus among the companies, who are fierce competitors, on what the standards and guardrails should be. “There’s no consensus among them. And Congress is obviously less qualified than the people who are pushing this frontier to know all the ins and outs of it,” Johnson said, adding he thinks the AI leaders should immediately meet to hammer out some standards alongside the government. “So this has to be a partnership with the industry itself, with the corporations that are doing this and with the policy and lawmakers.” By Hadas Gold

Nvidia’s Jensen Huang Thinks Young People Are Overlooking the Skill That Will Matter Most

Tech executive Jensen Huang wants younger generations to focus on the foundation of engineering before heading straight into the world of artificial intelligence. For decades, the Nvidia CEO has helped foster the AI boom. But as younger generations enter the space, Huang wants newcomers to focus on one discipline he believes will outlast any wave of automation: engineering. “Engineering teaches you to start from first principles, grounding everything in physics and mathematics and applying it to real problems,” Huang said in a statement to Fortune. “It teaches you to break complex challenges into solvable parts, which is how we build systems at Nvidia.” At a moment when entry-level workers face growing uncertainty about how AI will reshape their careers, Huang is urging them to bet on a skill set rooted in problem-solving and grit. “You learn that meaningful problems require resilience, as the most important outcomes often seem impossible at first,” he said. “Over time, I’ve come to see engineering as the most noble profession. It is the foundational building block of modern society, enabling everything from infrastructure to computing to science.” Engineering first Huang’s emphasis on engineering isn’t just a response to the AI boom. It’s rooted in his own career. He studied electrical engineering at Oregon State University, where he joined IEEE, the world’s largest technical professional organization. Decades later, IEEE awarded Huang its highest honor, the Medal of Honor, recognizing his role in pushing the boundaries of modern computing. At the ceremony, Huang made clear that the AI era will be defined by both disruption and expansion—and that engineers will sit at the center of both. For Huang, AI isn’t eliminating work. Instead, it’s changing who defines it. “Engineers ultimately are the ones that take an invention and advance it in such a way that it’s safe, beneficial, ultimately transformative to society,” Huang said, according to Fortune. “The engineers in the AI industry must advance AI in service of a better future for all of us.” However, not everyone is in absolute agreement with Huang’s assertion. “First-principles thinking is a powerful mental framework, and it’s something people should absolutely incorporate as AI reshapes how we work. But I wouldn’t think about engineering as the answer in absolute terms,” Juan Jose Lopez Murphy, the head of data science and artificial intelligence at Globant, told Inc. The expansion and accessibility of AI isn’t just a trend, but a historical phenomenon. According to a report from Stanford, AI reached 53 percent public adoption in just three years, faster than any technology on record. This has led to a wider use of the new capabilities, such as vibe coding, where users can approach AI software with natural language prompts to instruct an AI assistant to build applications, websites, or games without writing or reviewing the source code manually. In this new environment, some are pushing younger generations toward developing a diverse set of skills—instead of specializing. “Engineering is one of many valuable foundations, and in a world changing so quickly, over-specializing can actually make you more fragile,” said Murphy. “The most durable skill is being able to apply strong problem-solving principles across disciplines and adapt as the technology evolves.” AI fluency According to the U.S. Bureau of Labor Statistics, engineering roles, from computer hardware to electrical systems, are projected to grow faster than average, with demand accelerating across AI, energy, and defense. Huang sees this moment as a meaningful opening for young professionals. “AI is expanding the scope of human work, not shrinking it. We’re busier than ever because we have more ideas to pursue, and AI makes it possible to go after them,” he told Fortune. “Jobs will change because tasks will change, but work grows with productivity.” That growth is already visible inside Nvidia itself. The company plans to double its workforce to roughly 75,000 employees over the next decade, hiring that will likely lean heavily on engineering talent, Fortune reported. But Huang’s advice doesn’t stop at choosing a major or career path. He argues that everyone, regardless of role, needs a baseline level of technical fluency. “Every young person should become an AI expert,” he said. “It is an incredible technology that significantly lowers the knowledge barrier of any professional field… AI fluency will empower you and elevate your chosen craft.” BY LEILA SHERIDAN, NEWS WRITER

Apple Broke Its Own Rules for 2 New Macs—and AI Buyers Are Snapping Them Up

Apple has predictable habits for releasing new hardware, so it was a surprise when the tech giant revealed new Macs with updated, more powerful chips last week. The refreshed hardware arrived before Apple’s traditional iPhone event, which this year occurs on Wednesday, September 9. So why did Apple release these machines, the Mac Mini and Mac Studio, when it did? Thanks to a new report, we think we understand: Apple’s updated desktop Macs were announced early because they’re selling like hotcakes and Apple wants to sell more of them to eager buyers. These machines are desirable because they’re ideal for acting as hosts for local AI models. According to news site The Information, the sudden AI-driven popularity of the machines caught the Cupertino, California-based company by surprise. Apple even apparently lacked the necessary enterprise-centric support teams. Why would anyone want to run an AI locally, though, when enterprise-ready AI systems are everywhere at the moment? Everyone from Google to Microsoft is offering powerful AI services from their giant cloud server farms, with plenty of business-centric tools. And platforms like Amazon Web Services offer powerful developer-friendly AI environments from their data centers. The keywords are “cloud” and “data centers.” These third-party AI offerings require gigantic computer facilities, which is why they’re offered by deep-pocketed tech giants like OpenAI on a remote-access basis. But if you run your own, less powerful AI models on your own hardware, then you remain in control of the entire operation. This means you can train the models with data that no one else can access. It means only you and your staff see the outputs when you query an AI. It means that if your developers improve the AI algorithms in clever ways, then only you benefit. All of this is useful for intellectual property protection and even, for some companies, for preserving audit trails for sensitive data handling. Finally, hosting an AI model on your own hardware means you retain control of the cost. Spiraling, expensive AI bills for remote-access services have surprised many companies in recent months, landing some users in the headlines because they owe so much. Thus Apple’s reasonably priced Macs are suddenly hugely popular. The newly updated machines are even faster than earlier versions for AI purposes, too: Apple highlights that the new Studio can carry out “Up to 9.8x faster” LLM AI prompts, and the new Mini has similar improvements over previous editions, thanks to the new M6 and M5 Pro processors inside. MacRumors pointed out that when Apple announced the new Macs, it even highlighted that they can be clustered together to create a powerful compute facility (think almost-a-supercomputer on your desktop) for exactly this purpose. The Mac Mini’s prices start at just $900, leaping up if you select more powerful chips or more memory. The more powerful Mac Studio starts at $2,500, and higher-end configurations can reach many thousands of dollars. But these remain one-off purchases, compared with paying an open-ended bill for AI-as-a-service from the likes of OpenAI. There’s a lesson here for many smaller-business owners. AI is the buzziest tech right now, and it comes with the promise of boosting efficiency and maybe helping to cut costs, too. But typically, because AI is delivered by cloud-based companies like OpenAI or Google, each system brings its own risks in terms of potential expenses as well as data leaks. Surveys show a staggeringly high number of workers merrily type sensitive company data into these chatbots, unaware of the risk they pose. So running your own AI models on machines like Apple’s new ones could be a good solution. And even if you’re not in the market for building your own safer, Apple-powered local AI server, other options exist. Some AI models are freely downloadable and can run on relatively modest hardware. This may be an even simpler and cheaper option, depending on your company’s AI needs. The news should also serve as a reminder to savvy CEOs that deploying AI is not a one-and-done maneuver. The tech is advancing fast, so continuously evaluating which AI best serves your needs at what price could save you money in the long run. BY KIT EATON @KITEATON

5 Side Hustles You Can Start Today With AI

Artificial intelligence can be a significant income source for people who choose a smart side hustle. AI may still have a long way to go with some tasks, but with others, it can increase productivity and results. And there are a number of companies looking to take advantage of those benefits. The best AI-driven side hustles use the technology as a great equalizer. Small business owners, particularly of established businesses, often use AI in a limited fashion, if at all, says Peter Hansen, director of research and policy analysis with the National Federation of Independent Business (NFIB). Those founders value and emphasize the human connection to their customers. But even if they don’t use it, they recognize AI can help in other areas. Many of those owners don’t have the time to learn the ins and outs of various AI systems. And even companies that are using AI are often not taking full advantage of it. That creates an opening for side hustles that center around AI. “More than three-quarters of businesses already using AI report higher productivity, yet most are still applying it to a narrow set of tasks,” says Simon Worsfold, head of data communications at Intuit QuickBooks, which puts out a monthly Small Business Index exploring market trends. “What is emerging is a large, underserved layer of advisory, implementation, and training services that small businesses need in order to scale their use of AI,” he says. Here are five ideas for AI-focused side hustles that could be lucrative—or even become the foundation of a full-time business. AI Consultant This is a side hustle with multiple branches. Some people are well suited to help people or businesses integrate AI with their calendar, notes, and local files. Others can develop workflow audits that review how a company’s employees work to discover repetitive tasks that the AI could handle. Rates for an AI consultant range from $150–350 per hour for independent workers and people running it as a side hustle. Those can jump as high as $600 per hour if you convert this side hustle into a full-time company. AI Researcher To stay competitive, businesses need to know what their competitors are doing and what’s trending in their industry. That data can be remarkably complex, however, and not every founder or CEO has the time to do the deep dive it requires. Side hustle operators with strong AI skills can use the technology to filter the data into easily digested insights, then sell those as reports, newsletters, or direct subscriptions. You’ll need to carefully identify the best source material and be sure to double check the output, since AI’s comprehension is still flawed. “The AI doesn’t give the correct answer all the time,” says Shaun Ghavami, Founder of 10XBNB, a side hustle-turned-business that now oversees a portfolio of over $100 million of short-term property rentals. “The real skill is in prompting.” GEO (AI Search) Optimization For the past two decades, businesses have hired specialists to help them rank high on search results pages. While that’s still valuable placement, smart business owners are also looking into how they can be among the frequently-cited sources for AI search results. People with a combination of AI and content knowhow can create a side hustle specializing in this. You’ll teach companies the best ways to refine their content and meta tags and improve readability for large language models. If you have the tools to measure analytics, such as Alli AI, Frase, and MarketMuse, you have a better chance of establishing a recurring relationship with those clients, increasing your income and establishing a base should you want to make this more than a side hustle. Content Repurposing (Clipping) Both content creators and businesses regularly churn out videos and stories as promotional tools, or in an effort to be seen as thought leadership experts. Quite often, though, that content needs to be pared down before they’re posted on everything from TikTok to LinkedIn to Instagram. And that takes time, which the companies and content creators may not have to spare. As an AI content repurposing expert, you can transform the long-form content into digestible bites to widen the potential audience in a much shorter period of time. Use tools like CapCut, Canva, and ChatGPT to effortlessly pick and highlight the most relevant parts. Create AI Microtools AI can be intimidating to many people who don’t know where to start, especially when it comes to creating agents or GPTs that are relevant to their needs. A smart side hustle operator, though, knows that you don’t have to be an expert to create your own AI tools. Sites like Gumloop let you visually build workflows that can be run at large scale. You’ll use a drag and drop template that lets you create workflows that do just about anything, from running a search engine optimization audit of a Website to a ranking system for job applicants. You can either custom create those for clients or build general purpose tools and sell them on Etsy or some other marketplace. BY CHRIS MORRIS @MORRISATLARGE