
Altman and Musk Battle to Build the Ultimate ‘Everything App'
Earlier this week, Sam Altman unveiled more of his ambitious vision, not as the CEO of OpenAI, but as the co-founder and chairman of Tools for Humanity, the organisation behind Worldcoin. Now available in the U.S., Worldcoin distributes cryptocurrency to individuals who scan their eyes using specialised orbs, which are being deployed in retail stores across the country. But this is only one piece of a much larger puzzle. The long-term goal? To power a super app that could directly rival Musk's X.
Altman's World App serves multiple functions: it's a crypto wallet, social network, and a growing ecosystem of mini apps. According to Tools for Humanity, the app has seen its monthly user base double in just six months, now boasting 26 million users—12 million of whom have verified their identity using an orb. Within the app, users can chat through World ID-linked messages, transfer cryptocurrency, and interact with third-party mini apps, such as those developed by Kalshi, with seamless in-app transactions.
Meanwhile, Elon Musk is pursuing a similar goal with X. He has openly stated his intention to turn X into a central hub for finance and social networking. Plans are already underway for Venmo-style payment features, rolling out in partnership with Visa later this year. Coincidentally—or perhaps competitively—Tools for Humanity also revealed its own partnership with Visa to launch a U.S. debit card this summer. The card will enable transactions using Worldcoin and offer exclusive rewards for AI-related services.
Aside from competing on features, both platforms aim to solve a shared challenge: combating bots and fake accounts. 'It was clear to us that there was a need for something like this, that we needed some sort of way for authenticating humans in the age of AGI,' Altman said during the event. 'We wanted a way to make sure that humans stayed special and central in a world where the internet was going to have lots of AI-driven content.'
Tools for Humanity CEO Alex Blania echoed this vision during a press Q&A. He pointed to Musk's X platform as the kind of environment they hope to enhance with World ID verification. He added that bots are no longer as easily detectable as they once were: 'Bots on X used to be 'so stupid that you could see it was some crypto scam,'' he said. 'Now, it's not as clear.'
OpenAI insiders were also spotted in the audience at the event, adding fuel to speculation about a possible collaboration. Leading up to the keynote, rumors swirled that OpenAI might partner with Worldcoin for its own social network. When asked about this, Blania responded, 'definitely open to it,' hinting at future developments. Unfortunately, Altman exited the venue after his keynote, leaving further questions unanswered.
As the race to build the ultimate app intensifies, Altman and Musk continue to push the boundaries of what a digital platform can be—each with their own powerful ecosystem in the making.
Hashtags

Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles


Time of India
17 minutes ago
- Time of India
AI errors: RBI panel calls for 'tolerant supervision'
MUMBAI: An RBI panel examining the responsible use of AI in finance has urged regulators to adopt a "tolerant supervisory stance" towards mistakes made by AI systems. The idea is to allow institutions some leeway for first-time errors if they have adequate safety measures in place. The aim, the panel argues, is to encourage innovation rather than stifle it. Such tolerance is justified, the report says, because AI is inherently probabilistic and non-deterministic. A strict liability regime that penalises every misstep could make developers overly cautious, limiting AI's ability to deliver novel solutions. This approach could be controversial as it may be seen to be shielding institutions at the expense of customers who suffer losses from AI errors. The framework rests on seven "sutras": maintain trust; keep people in control; foster purposeful innovation; ensure fairness and inclusion; uphold accountability; design for transparency; and build secure, resilient, energy-efficient systems that can detect and prevent harm. Its 26 recommendations span building better data infrastructure, creating sandboxes for AI testing, and developing indigenous models to help smaller players. Regulators are advised to draft flexible rules and apply liability proportionately. Banks are told to adopt board-approved AI policies, implement strong data governance, and safeguard customers through transparency, effective grievance systems, and robust cybersecurity. Continuous monitoring, public reporting, and sector-wide oversight are proposed to keep AI use safe and credible. Stay informed with the latest business news, updates on bank holidays , public holidays , current gold rate and silver price .


NDTV
18 minutes ago
- NDTV
RBI Panel Proposes Fund To Build Homegrown AI Framework For Finance Sector
Mumbai: A Reserve Bank of India (RBI) committee has recommended a framework for developing AI capabilities for the country's financial sector, while safeguarding it against associated risks, according to a report released on Wednesday. The committee has recommended setting up a digital infrastructure to help build indigenous AI models and a multi-stakeholder standing committee to evaluate risks and opportunities. It also suggested building a fund to incentivise the development of homegrown AI models tailored for the needs of India's financial services sector. "The report envisions a financial ecosystem where encouraging innovation is in harmony, and not at odds, with mitigation of risk," the RBI said in a statement. The report contains 26 recommendations under six categories, including infrastructure, capacity, policy, governance, protection and assurance. Other key recommendations by the eight-member committee headed by Pushpak Bhattacharyya, a computer scientist at IIT Bombay, include issuing an enabling framework to integrate AI with existing digital public platforms such as instant payment system UPI, and designing audit frameworks. The central bank had set up the committee in December to develop a Framework for Responsible and Ethical Enablement of Artificial Intelligence (FREEAI) for the finance sector. "The challenge with regulating AI is in striking the right balance, making sure that society stands to gain from what this technology has to offer, while mitigating its risks," according to the report.


The Hindu
33 minutes ago
- The Hindu
To survive AI and global geopolitics, India should become a hub of knowledge creation, not just knowledge processing
Earlier this month, Tata Consultancy Services (TCS), India's largest IT services firm, confirmed it will lay off 12,000 employees. For decades, companies such as TCS symbolised India's prowess in IT-enabled services — a low-cost, high-scale model that rode the wave of globalisation. But that model is now under existential strain. The era of labour arbitrage is drawing to a close, and the age of artificial intelligence (AI) is rewriting the rules of economic competitiveness. Generative AI, machine learning, and automation are fast replacing the very tasks that once gave India its edge: coding, data entry, support services, and even parts of analytics. The decline in headcount is not a blip; India's core export, white-collar digital labour, is being disrupted. And the country does not seem prepared as we see problems in absorbing science and engineering talent newly entering the job market. Simultaneously, the manufacturing-led catch-up route is narrowing. For years, economists argued India could do what China did in the 1990s — turn industrial policy and export-led manufacturing into mass employment and structural transformation. But that ship has largely sailed. Countries such as Vietnam and Bangladesh have already captured the low-cost manufacturing space. Add to that rising automation and India's own infrastructure bottlenecks, the feasibility of China-style manufacturing resurgence diminishes rapidly. What, then, is India's pathway to sustained economic relevance? The answer lies upstream — in innovation, discovery science, and a smart, coordinated science, technology, and innovation (STI) policy. If India wants to be a rule-maker rather than a rule-taker in the AI-driven global economy, it must invest urgently in becoming a hub of knowledge creation, not just knowledge processing. This will only be achievable with a new national compact that starts from STEM but goes above and beyond embracing STEPS — an integration of STEM with policy and society. This means building a generation of technologists who understand not just how to build systems, but how those systems affect entrepreneurship, business model and scaling, ethics, governance, and inclusion. It also means reforming curricula to include data governance, AI ethics, climate-tech, innovation economics, and intellectual property policy. Finally, it also means urgent, mission mode requirement of an integrated, State-agnostic approach where we will see not just southern India having a head start in STEM and STEPS. The New Education Policy (NEP), 2020 provides some groundwork, but implementation must go further and deeper. From IITs to State universities, India will need a deliberate shift toward interdisciplinary innovation and doctoral-level research capacity. India's innovation-to-education pipeline is currently too weak to sustain a 21st century knowledge economy. And sadly in this, as noted above, manufacturing likely will not save India any more. The dream of becoming the 'next China' in manufacturing is now largely unrealistic. India's manufacturing sector contributes just 14-16% of the GDP — a figure that has barely budged in a decade. More worryingly, global manufacturing is undergoing its own AI-led transformation: smart factories, predictive maintenance, and robotic assembly lines are shrinking the need for cheap labour. Competing on cost is now a losing battle. Moreover, global supply chains are also realigning around strategic resilience and digital integration, not just wage arbitrage. India's challenge is not to attract the next garment factory but to build the next quantum computing lab or climate-resilient agri-tech platform. Which brings us to the question of how a Triple Helix approach might be India's best shot at future-readiness. To get there, India will need a clear National Science and Innovation Strategy underpinned by deep collaboration between government, industry, and academia. No single actor can deliver the transformation needed and increasingly the need of the hour will be science-based entrepreneurship and scientist entrepreneurs. It has been done before like by Vijay Chandru, inventor of Simputer and founder of Strand Genomics, also a former IISc Professor, but one Vijay Chandru is hardly enough for a country of 1.3 billion. Blue-sky science Government also must invest in blue-sky science, reform its R&D funding structures, and design enabling regulatory frameworks for frontier tech (AI, biotech, semiconductors, and so on). Universities must evolve into innovation hubs, not just exam factories. They must work closely with industry, build tech transfer offices, and reward risk-taking. Industry also must move beyond short-term returns and co-invest in long-horizon research, from chip design to synthetic biology refusing to accept modest productivity gains with a middling equilibrium mindset. Global lessons abound. The U.S.'s DARPA ecosystem, Germany's Fraunhofer Institutes, and Israel's Start-Up Nation playbook all demonstrate how strategic state support and institutional coordination can turn ideas into global advantage. India can build from their lessons, leverage on the current global geopolitical headwinds and create a national consciousness around science and innovation. It is not just investment in science that will matter, but investment in the science of innovation itself brings in a critical evaluation mindset for upgrading based on evidence. India lacks a coherent framework to measure what works: which R&D models yield translational success? How do tech incubators perform over time? Where does research funding leak or stagnate? A National Science of Science and Innovation Policy (NSIP) platform — a cross-ministerial, data-driven approach to governing the innovation ecosystem — could be a way forward. NITI Aayog's AI strategy and the recent National Research Foundation are steps in the right direction, but coordination and scale remain insufficient. This effort must include dedicated funding for AI safety, public interest technologies, twin transition policies and sovereign computational infrastructure. The stakes are high: if India does not develop its own AI stack, algorithms, chips, cloud, data protocol, it will remain captive to technological colonialism. Stagnation, inequality The fallout from the AI transition is not hypothetical as we see in the TCS situation mentioned above. If India does not invest in science, technology, and evidence-based policy today, it will face economic stagnation, rising inequality, and geopolitical irrelevance tomorrow. The global economy will not wait for India to catch up and in fact, catching-up economies are looking for the country's leadership in these areas. This is particularly concerning since already, a handful of countries — mostly in West and East Asia — are monopolising AI patents, funding, and talent. Without a deliberate national push, India will continue to supply coders to other nations' AI empires rather than building its own. The good news is that India has the ingredients: a young demographic, a robust start-up ecosystem, and scientific institutions with proven excellence. What we need now is leadership, vision, and a strategic shift in mindset — from cost to creativity, from services to science, from political populism to real performance. India can still leapfrog into the global innovation vanguard. But only if it recognises that science, technology, and smart policy are not luxuries — they are our last, best bet in the age of AI. The dragon is roaring already, will the elephant wake up? Chirantan Chatterjee is a Professor of Development Economics, Innovation and Global Health at the University of Sussex