Amazon’s Project Kuiper, in the race to offer satellite internet service in India, is aiming for a launch next year, though it trails rivals Starlink, OneWeb and Jio Satellite, two people aware of the matter said.

       The delay in India foray is because the Amazon arm is still to have a sufficient satellite constellation to launch the services commercially and secure necessary licence and approval in the country, they said, requesting not to be identified. The company is yet to get its network and ground system designs to comply with a set of security conditions laid out by the Indian government.

       This Payday invest the right way!

       Save Big with Best Deals!

       Subscribe now

       Already subscribed? Login

       Premium benefits

       200+ Premium Articles Weekly

       WSJ, The Economist Access at < INR 340/month

       Build Smart Finance Plans with Experts

       Top Stock Recommendations Everyday

       Expert-Backed Investment Growth

       Access Mint Lounge, Newsletters & Insights

       For all of the talk in Silicon Valley about how screwed Apple is in the AI race, the iPhone maker got a glowing endorsement of its staying power this past week from an unlikely source: Elon Musk.

       The billionaire’s artificial-intelligence company and his social-media platform sued the iPhone maker, claiming it was violating antitrust laws by giving preferential treatment to its own AI partner (and Musk enemy), OpenAI and ChatGPT.

       “This makes it hard for competitors of ChatGPT’s generative AI chatbot and super apps powered by generative AI chatbots to scale and innovate," said the lawsuit, filed by Musk’s xAI and X in a Texas federal court.

       That is at odds with a prevailing view in Silicon Valley. Meta Platforms chief Mark Zuckerberg and others believe that advanced AI will usher in a new computing paradigm that basically relegates the iPhone to something akin to a Computer History Museum exhibit. They see it as a rare generational opening to unseat Apple’s hold as the gateway to the digital world.

       A one-sided cold war has been brewing between Musk and Apple chief Tim Cook ever since the Tesla and SpaceX CEO acquired Twitter in late 2022. Musk quickly realized how powerful App Store rules are for companies like his.

       If Musk thought the paperwork to launch Starship was frustrating, he had obviously never waded through Apple’s app-review process.

       Opponents of Apple’s control of the App Economy watched with glee as Musk lashed out at Apple and Cook personally. They quietly hoped Elon’s megaphone and megabucks might help their cause in fighting the tech giant.

       His entry into the antitrust battle against Apple held the promise of fueling new excitement in legislation that was then stalled before Congress. Republican Sen. Marsha Blackburn of Tennessee, in particular, seemed eager to make hay of his interest.

       But Cook quickly dispatched Musk, essentially patting him on the head with a VIP tour of Apple Park and apparent promises of continuing to advertise on his struggling social-media platform. Soon enough, Musk raced off to the next shiny objects, such as messing with Sam Altman’s AI ambitions.

       Frankly, it’s hard to tell these days how much fire is in Musk’s belly to fight Apple’s perceived injustices. Or if Apple is receiving the incoming attacks simply because of the animosity Musk has for Altman.

       The two billionaires teamed up almost a decade ago to create OpenAI. Eventually, Musk left in a huff over their differing visions for the future. OpenAI’s sudden and, perhaps, unexpected success has turned the company into Musk’s own personal “Rosebud" obsession. He since founded xAI as a rival to OpenAI, and merged it with Twitter, now known as X.

       His companies’ lawsuit against Apple and OpenAI this past week came just days after a federal judge in the San Francisco area rejected Musk’s efforts to dismiss OpenAI’s claims that he is trying to harass the startup.

       “OpenAI puts Musk on notice that it alleges the media campaign ‘significantly threaten[ed] or harm[ed] competition,’ was either untrue or misleading and deceiving to an actual customer, and was designed to—and ultimately did—disrupt a business relationship leading to economic harm," Judge Yvonne Gonzalez Rogers wrote. “At this stage, the allegations are sufficient."

       A trial is scheduled for March.

       It’s hard not to see Musk’s continued legal campaigns against Altman as anything but a sign of how far behind his own efforts to develop AI are—despite all of his bravado.

       In the Apple-OpenAI case, his side essentially admits as much. The Musk lawsuit notes that his AI chatbot, Grok, has gained little market share “despite accolades about its superior features," while OpenAI has quickly become the dominant player.

       The arguments against Apple draw similarities to an antitrust case brought last year by the Justice Department. That case includes allegations that Apple has taken steps to suppress so-called superapps from taking hold. This was supposedly done out of fear that such third-party offerings make it easier for iPhone users to switch to rival smartphones, diminishing the value of the Apple ecosystem.

       Musk has said his broader vision for X is to remake it as a superapp, similar to China’s powerful WeChat, where users conduct much of their digital lives.

       In the latest lawsuit, Musk’s team argues that AI supercharges those superapp efforts. Essentially, Musk’s claim is that the Apple-OpenAI partnership hinders rivals from gathering important user data from iPhone customers.

       This hurts AI development, which in turn prevents superapps from effectively rising up to threaten the iPhone’s supremacy. “This is a tale of two monopolists joining forces to ensure their continued dominance in a world rapidly driven by the most powerful technology humanity has ever created: artificial intelligence," the lawsuit said.

       Apple hasn’t yet officially responded to Musk’s lawsuit, although it has previously said its App Store is “designed to be fair and bias free." It is defending itself against the government’s antitrust case and said the government lacks evidence of wrongdoing and “fundamentally misunderstands" its business.

       “DOJ says Apple stifles the success of ‘super apps,’ despite the fact that Apple’s rules allow and support such apps, and indeed a multitude of ‘super apps’ exist on the App Store today," Apple said in a July court filing.

       Even if Apple agrees with OpenAI that Musk’s claims are without merit, his escalation comes with new risks for the iPhone maker outside the courtroom—political risks.

       The idea of legislation targeting Apple has returned to Congress. Blackburn, the Republican senator, has joined with her Democratic colleagues to reintroduce the Open App Markets Act.

       She told me in a statement that Musk’s claims about Apple’s AI interference are why Congress needs to act. “Big Tech should not be allowed to play kingmaker in the mobile app economy," she said. “This kind of control allows companies to use their app stores to favor certain businesses and partnerships while stifling competition, limiting innovation, and ultimately hurting the consumer."

       For Musk, the friend of his enemy has become his enemy.

       Write to Tim Higgins at tim.higgins@wsj.com

       Fears of artificial intelligence (AI) outsmarting humans anytime soon are overblown, leading mathematicians have assured. AI is nowhere close to acquiring critical thinking, or reaching scientific breakthrough that humans are capable of, they said.

       While they admit that AI is a powerful technology that will have a profound impact on society and economy, they emphasise that children should be encouraged to enjoy mathematics—'Math for Math's sake'—to help develop creativity and problem-solving skills.

       Also Read | Nvidia is riding the AI revolution. What the chip maker isn’t telling us.

       "...that deep kind of critical thinking, analytic thinking, that keeps us producing new knowledge, that AI is not really doing yet, and whether it will be able to or not, that's sort of still an open question," Manjul Bhargava, professor of mathematics at Princeton University, who was awarded the Fields Medal in 2014 for his work on geometry of numbers, told Mint. "It will take years for it to do the kind of critical thinking, analytical thinking, new knowledge creation, kind of creativity that's required to make scientific and mathematical breakthroughs. It's not really close yet".

       The prestigious Fields Medal honour, named after Canadian mathematician John Charles Fields, is considered as the Nobel prize of mathematics.

       Also Read | Gemini’s Storybook brings the charming side of AI

       His comments come at a time when companies across the world are investing in AI-related infrastructure, and upskilling programmes just when there is a looming fear that AI will replace human jobs. In fact, Microsoft, IBM , Tata Consultancy Services (TCS), Amazon and Meta are some of the firms that have retrenched employees as AI gets deployed across hierarchies.

       But the work that AI can do today is still relegated to the content that is fed into it. Bhargava pointed out that in the next two-three years, AI will solve problems because it would have read all undergraduate math and science books and through large language learning models "mimic the kinds of solutions that are in all these books".

       He rejected the notion that mathematicians are worried about AI.

       "No, there's not so much fear. There's more excitement. Right now, there's a lot of humour and laughter at the kinds of answers that AI gives to slightly more complex math questions… But it's not necessarily going to be coming up with anything that humans don't know. So, in that sense, it's not really doing critical thinking, it is doing pattern matching".

       Also Read | Alibaba creates AI chip to help China fill Nvidia void

       V. Kumar Murty, who teaches mathematics at the University of Toronto, Canada, told Mint that the job losses seen at companies are temporary. “What we should really be thinking of is, okay, if certain jobs disappear, what new job is it going to enable, that doesn't exist now? What new opportunities is it going to create for me that don't exist now?"

       Murty, who held the post of director of the Fields Institute for Research in Mathematical Sciences, Canada, highlighted the need to encourage math learning for the sake of the subject and to move away from rote learning or focus only on entrance exams for an engineering seat.

       In India, more than 1.3 million students appeared for this year’s engineering entrance test in a bid to secure admission to one of the 23 Indian Institutes of Technology (IITs) or other government-funded engineering institutions.

       For many students, the road to a reputable engineering college goes through coaching hubs like Kota and Sikar (Rajasthan). The professors want that outlook to change.

       “The engine of innovation is mathematics. What is Google? It's linear algebra. The robotic vacuum cleaner is computational geometry. Satellite transmission is polynomial over finite fields. Any piece of technology that is in common use today has, at its root, mathematics… If you want to have that culture of strong research, strong innovation, you need to let the people who do math for math's sake have opportunity as well," Murty.

       Bhargava is more optimistic that classroom teaching is going beyond chalkboards and there is importance given to interdisciplinary teaching where subjects are not offered depending on grades with the belief that one is superior to the other.

       Coincidentally, Bhargava and Murty are also involved in the Lodha Mathematical Sciences Institute, a newly-launched privately-funded math research institute in Mumbai. While Bhargava is the inaugural thematic programme head, Murty is the director at the institute.

       Artificial intelligence can do a lot these days—and will be able to do a lot more in the future. But killing a $1.2 trillion industry will be a stretch.

       That is how much the world’s businesses are expected to spend on enterprise software this year, according to projections from market research firm Gartner. It is a big number, and nearly 11% higher than the $1.1 trillion that was spent last year.

       Businesses spend more on software than just about any other technology-related category. But the age of AI has made that budget line look increasingly under threat. Among the early promises of tools such as ChatGPT was that it could allow novices to create software by simply telling the LLM what they want in natural language. Such “vibe coding" could theoretically render premade software obsolete. In a live demo of its new GPT-5 model earlier this month, OpenAI employees created an app for teaching French to English speakers in a few minutes, all on stage.

       “We think this idea of software on demand is going to be one of the defining characteristics of the GPT-5 era," OpenAI Chief Executive Sam Altman said at the event. He is actually a bit late to the party; Nvidia CEO Jensen Huang proclaimed in 2017 that “AI is going to eat software."

       The prospect of an existential threat has cast a darker shadow on an industry that was already under a cloud. Global economic uncertainty caused by trade wars, real wars and the prospect of inflation has created a “business pause on net-new spending" on corporate IT needs, Gartner’s analysts wrote in a report last month. Booming investments in AI infrastructure are also pressuring other areas of the corporate tech budget line.

       Wall Street is getting worried. Analysts are asking executives about topics such as “AI disruption" with increasing frequency, according to an analysis of earnings calls and other events by AlphaSense. Software stocks have also been among the weakest categories in tech of late. The BVP Nasdaq Emerging Cloud Index has slumped nearly 6% over the past month and is the only major tech subcategory to be in the red for the year to date, according to FactSet.

       View Full Image

       Software’s Death by AI Has Been Greatly Exaggerated

       AI tools are certainly changing the game for software development. JPMorgan Chase Chief Financial Officer Jeremy Barnum told analysts at a meeting in May that he had been indulging in vibe coding, describing it as “pretty amazing." But highly complex software applications running mission-critical tasks won’t be simple to replace. Especially those running on data related to sensitive—and often regulated—areas such as human resources and finance.

       “More than 65% of the Fortune 500 use us, and not one of them is going to say ‘Come in here AI startup and run my back office and financial controls,’" Workday CEO Carl Eschenbach said in an interview.

       Companies such as Workday and Salesforce, which disrupted the more traditional on-premise software industry not too long ago, are working furiously to adopt AI themselves within their own products. Agents—AI chatbots that are enabled to take certain actions on behalf of people—are a big part of this effort. Nearly every software-as-a-service company is now selling agent tools to their customers, though RBC analysts argued in a report this week that the real opportunity will come from “multi-agentic" systems that can operate across different software applications, which no one has really cracked yet.

       “For example, a sales leader should be able to use natural language to onboard a new salesperson," RBC’s report read, executing across HR identity systems, expense cards, training programs and so on.

       Vibe coding is unlikely to pull that off. In his own report earlier this month, longtime software analyst Brent Thill of Jefferies cited the “meaningful complexity" across current business software workflows that AI cannot yet replace. “In our view, the intricacies of enterprise architecture make full AI disintermediation of software unlikely," he wrote.

       Stumbles by AI companies will help make that case. OpenAI faced a flood of criticism following the GPT-5 launch, with users complaining about inaccurate answers from a chatbot that Altman touted as the equivalent of “having a team of Ph.D. level experts in your pocket." Meta Platforms has also struggled with taking its Llama 4 model to the next level.

       AI chatbots may have quickly disrupted high-school term papers. Replacing billion-dollar software systems won’t come so easily.

       Write to Dan Gallagher at dan.gallagher@wsj.com

       After his ouster from Twitter, now 'X', Parag Agrawal has launched a new company, Parallel Web Systems, that is attempting to create a "web for machines". He is betting on a web that will be dominated by artificial intelligence (AI), not humans.

       Agrawal is building infrastructure and tools optimized for AI agents to access, verify, and organise web data. Simply put, he wants to change how AI surfs the internet by creating a platform that is built for AI, works in real time, can be trusted, and scales easily. But is the idea new? What does it entail? And will it truly transform the web or remain a private ecosystem? Mint explains

       What is Parag Agrawal's story so far?

       India-born Parag Agrawal began his career in 2006 as a researcher at Microsoft before moving briefly to Yahoo and later returning to Microsoft. In 2009, he joined AT&T’s research division, but it was at Twitter, which he entered in 2011 as a distinguished software engineer, that his career took off.

       After six years, he rose to chief technology officer and, in 2021, was named CEO. His tenure was cut short when Elon Musk acquired Twitter in October 2022, rebranded it as X, and ousted thousands of employees, including Agrawal and three other top executives. The employees collectively sued Musk for $500 million in severance pay, which the latter has partly tentatively settled for now. However, Agrawal and the other three senior executives continue to pursue their own claims in court.

       Also Read | When big tech pulls the plug: What Nayara's disruption reveals

       Why is he in the news again?

       The IIT Bombay graduate recently announced the launch of his new company's "Deep Research API (application programming interface)", which he claimed is "...the first to outperform both humans and all leading models including GPT-5 on two of the hardest benchmarks (the DeepResearch Bench and Browse Comp benchmarks show how well AI can dig up hard-to-find information and produce detailed reports)".

       In operations since last October, Parallel Web Systems already powers "millions of research tasks every day". According to Agrawal's LinkedIn post last week, "...some of the fastest growing AI companies use Parallel to bring web intelligence directly into their platform and agents. A public company automates traditionally human workflows, exceeding human-level accuracy with Parallel. Coding agents rely on our search to find docs and debug issues…"

       What does it mean for users and enterprises?

       Unlike Google or Perplexity, which serve people with answers or links, Parallel is designed for machines. Its Deep Research API enables AI agents to move beyond surface-level searches, using multiple research engines to deliver anything from quick responses to complex, time-intensive insights.

       Each result comes with attribution, confidence scores, and structured outputs, making the data both verifiable and machine-ready. For enterprises, this means plugging the API into their own AI systems to power tasks like market analysis, due diligence, customer research, or competitive intelligence. By prioritising traceability and reliability, Parallel is attempting to tackle the problem of AI hallucinations. That makes it especially valuable for sectors such as finance, law, and healthcare, where accuracy and trust matter most.

       Also Read | The man who wants your face to be the boarding pass—everywhere

       But how unique is Agrawal's idea?

       Agrawal is right that today’s web still serves humans: we click links, juggle tabs, compare prices, and judge credibility. AI systems attempt the same with unstructured data, paywalls, and noise, limiting them to simple queries. His vision, though, isn’t entirely new.

       The programmatic web has long imagined reshaping the internet so machines can interact with it directly. The agentic web goes further, envisioning AI agents that don’t just fetch facts but act on them— booking flights, restocking groceries, or running analysis. But unlike Web3, which focused on decentralised ownership but never scaled, Parallel is a web built for AI as its primary user. With APIs that promise clean, verifiable, real-time data, Agrawal is creating the first serious infrastructure for this shift in the hope that enterprises will pay for it.

       What about standards and protocols?

       Every major shift in the web’s history has relied on standards and protocols established by bodies like the World Wide Web Consortium (W3C) and Internet Engineering Task Force (IETF)—from hypertext mark up language (HTML) to the frameworks that make today’s web interoperable, allowing programs to communicate with each other.

       In the early days of search engines, for instance, companies each used their own indexing methods until standards around metadata and site maps helped unify the ecosystem. Likewise, the rise of mobile apps forced developers and device makers to agree on protocols that allowed apps to work across platforms.

       The programmatic web, though, is a complex marketplace dominated by opaque systems and proprietary tech. It still runs on the foundation set by bodies like the W3C and IETF, but remains a patchwork of open ideals and closed commercial interests even as standards groups are trying to rein it back.

       Agrawal's vision of a programmatic, machine-first web, too, would need common formats for attribution, verification, and structured outputs to enable AI agents to reliably share and interpret information across platforms, failing which his project risks becoming another siloed ecosystem as opposed to the transformative web infrastructure he envisions.

       Also Read | Freezing the dead: The science, startups, and controversy behind cryonics

       What about the AI bot problem?

       Automated bots already make up close to half of all internet traffic, performing tasks such as price comparisons and content scraping, but also spamming or gaming systems for ads and clicks. Further, AI-driven bots can mimic human behaviour, learn from their environment, and evade detection.

       A machine-first web risks amplifying those problems unless it can distinguish between “good" AI agents and malicious bots. Verification and attribution, which Parallel is building into its system, may help by giving enterprises a way to trust certain sources while filtering out noise. But how do you stop an AI-first internet from becoming overrun by low-quality or adversarial traffic? Search engines like Google already fight constant battles with SEO spam; a programmatic web like Agrawal's Parallel could magnify that challenge many times over.

       So, what can we conclude?

       For now, the good news is that investors are supporting the idea. To date, Agrawal has secured $30 million in funding from investors including Khosla Ventures, First Round Capital, and Index Ventures. However, given the bad bot problem and interoperability challenges, Agrawal's AI startup will not only have to build infrastructure for AI research, but also ensure governance and guardrails that prevent the platform from being gamed.