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The Launch of a New AI Lab Airbnb CEO Brian Chesky is set to back a new AI lab, as reported by Bloomberg and confirmed by a person familiar with the situation. This move signals Chesky's ambition to contribute to the AI space beyond his role as Airbnb's CEO. Chesky's Background in AI Chesky has been involved in the AI ecosystem for some time. He has been advising Sam Altman, the CEO of OpenAI, on managing a hypergrowth tech company. Their connection dates back to 2006 when Chesky met Altman through Y Combinator, which incubated Airbnb. The Focus of the New AI Lab The exact focus of Chesky's new AI lab is not clear, but it is expected to explore areas such as user interaction and design. These are areas that Chesky has emphasized during his tenure at Airbnb. Implications and Future Directions Chesky's decision to launch a new AI lab could position him in competition with OpenAI, the company he has previously supported. However, he will not be leading the new lab himself, choosing instead to remain as Airbnb's CEO. The leadership of the new lab will face the challenge of competing with other established AI labs while also navigating Chesky's involvement as the founding chair of Airbnb. The Road Ahead As the AI landscape continues to evolve, Chesky's new AI lab is set to make its mark. With Chesky's experience and insights, the lab could potentially develop innovative AI solutions that impact the tech industry.

Lead: A Columnist’s Warning About AI’s Empty VoiceNesrine Malik contends that AI‑generated text is fundamentally meaningless, a fact that makes it dangerously suited to today’s political climate of repetitive, low‑emotion rhetoric. She describes a personal “nightmare scenario” where AI research tools introduce misquotes and dilute the writer’s own intellectual labor.The Column’s Core Claim: AI Lacks Humanity and Fuels Empty Political RhetoricMalik frames AI as a “tinny chant” that pervades everything from customer‑service bots to social‑media posts, stripping language of its personal alchemy. She argues that while AI can mimic styles, it cannot generate truly original voices, leaving writers dependent on a chorus of existing tones.Lack of Quantitative Data – Qualitative Observations OnlyNo financial or usage statistics are cited in the piece.The argument relies on anecdotal evidence: misattributed quotes, a Commonwealth short‑story controversy, and personal writing habits.References to external research (e.g., a Time study) suggest AI may reduce brain engagement, but no specific figures are provided.Implications for Journalism, Politics, and Public DiscourseThe column warns that AI’s bland, repeatable tone amplifies disinformation and enables political actors to hide behind “empty slogans.”Keir Starmer‑like voices are cited as examples of how AI‑styled language can mute genuine ideological expression, allowing extremist narratives to surface unchecked.Future Trajectory of Human Authorship in an AI‑Saturated LandscapeMalik predicts a growing cultural atrophy if writers continue to outsource research and prose to LLMs. She urges a conscious resistance to preserve the “social contract” of trust and authenticity, suggesting that the battle for credible, human‑crafted content will define the next era of public communication.

The Tata-ASML Deal: A Game-Changer for India's Semiconductor Sector India's Tata Electronics has signed a deal with Dutch technology giant ASML to build India's newest venture into a front-end semiconductor fabrication plant. This move is part of New Delhi's efforts to develop a domestic semiconductor manufacturing base. Details of the Agreement Under the agreement, ASML will supply advanced lithography technology to Tata Electronics for the manufacture of 300mm wafers. Tata Electronics plans to invest $11bn to build India's first semiconductor fabrication plant in Dholera, Gujarat. The plant will produce chips for sectors including automotive manufacturing, mobile devices, and AI applications. The Significance of 300mm Semiconductor Wafers The Gujarat plant will manufacture chips using 300mm wafers, the global industry standard for advanced semiconductor fabrication. Larger wafers allow manufacturers to produce more chips per production cycle, lowering costs and improving efficiency. Why the Deal Matters for India The deal is significant for India as it furthers self-sufficiency and strengthens ties with Europe. It signals a shift in India's role in the AI economy from mainly software services and AI talent toward owning part of the physical infrastructure behind AI itself. The deal supports the government's broader push to position the country as a major global technology and AI player. India's AI Ambitions India's Prime Minister Narendra Modi has expressed his desire for India to become a global AI and digital economy leader. The government has launched initiatives focused on AI research, semiconductor manufacturing, digital infrastructure, and advanced computing, including the India AI Mission with a budget of $1.07bn over five years. The Future Outlook The deal is expected to boost India's semiconductor sector and support its AI ambitions. However, experts note that challenges remain, including infrastructural issues such as power and water supplies, as well as skill development. The success of this initiative will depend on India's ability to address these challenges and create a favorable business environment.

The AI Startup Valuation ShiftAnthropic has usurped OpenAI as the world's most valuable artificial intelligence startup, soaring to a $965bn valuation ahead of expected public listings by the rival firms. Anthropic, the maker of the Claude family of chatbots, said on Thursday that it had raised $65bn from private investors after a fundraising round led by Altimeter Capital, Greenoaks, Dragoneer and Sequoia Capital.Funding and Leadership PositionThe announcement catapults Anthropic, led by CEO and cofounder Dario Amodei, ahead of ChatGPT maker OpenAI in value, which attracted an $852bn valuation in its last fundraising round in March. "This funding will help us serve the historic demand we are experiencing, stay at the research frontier, and bring Claude to more of the places where work happens," Anthropic's Chief Financial Officer Krishna Rao said in a statement.Market Recognition and AdoptionAltimeter Capital CEO Brad Gerstner hailed the adoption of Claude among the "world's most demanding organisations" as evidence of Anthropic's command in the field. "This momentum positions Anthropic to lead the next phase of AI innovation and capture the enormous opportunity ahead," Gerstner said.Rapid Growth and Market PositionFounded in 2021 by former OpenAI researchers, Anthropic has rapidly emerged as one of the leading players in Silicon Valley's scramble to dominate AI. Anthropic's Claude, first launched in 2023, is among the most popular AI models worldwide. In March, the San Francisco-based company said that the chatbot was receiving more than 1 million new sign-ups each day.Challenges and Recent DevelopmentsWhile achieving stellar success in rapid time, Anthropic has also faced challenges – in particular, a high-profile dispute with US President Donald Trump's administration, which has labelled the firm a "supply chain risk" over its refusal to allow unrestricted access to its tools for military purposes. Anthropic unveiled its latest iteration of Claude, Opus 4.8, in a separate announcement on Thursday, calling it a "modest but tangible improvement" on its predecessor.Future Outlook and Market DynamicsAnthropic, OpenAI and Elon Musk's rocket company SpaceX are all expected to go public in the near future in what are expected to be among the biggest initial public offerings in history. Jay R Ritter, an emeritus professor at the University of Florida who specialises in IPOs, said Anthropic has generated a lot of market excitement due to its widespread use by companies for software coding. "This is a big market where apparently Anthropic has the best product," Ritter told Al Jazeera.Valuation Trends and Market Analysis"The increase in valuation in a short period of time is unprecedented for a startup, although publicly traded tech companies such as SK Hynix, Nvidia, and Alphabet have seen even bigger increases, although not as much in percentage terms," Ritter said, referring to the South Korean and US chip giants, and Google's parent company. While it remains to be seen whether the massive investments pouring into AI are creating a bubble, Ritter said, the handful of successful firms that are likely to emerge in the field could see enormous profits.Industry Consolidation and Future Prospects"Nobody wants to use the eighth best product, so these companies are either one of the handful of successful firms, or they will have a zero market share," he said. "The tech industry is different than the restaurant industry, where there are not large economies of scale, and where competition limits the profit margins."

The Concept of 'Mind Children' A few months ago, an AI researcher from Europe attended a dinner party in Silicon Valley. During one of the many courses, the host addressed his guests, all of whom worked in AI. The researcher paraphrased his message like this: “Isn’t it amazing that we are the last generation of humans who will need to think about procreating biologically? We were lucky enough to be born at a time where we can simply upload our consciousnesses instead.” The Book That Sparked the Conversation The book in question was Hans Moravec’s Mind Children: The Future of Robot and Human Intelligence, which was first published in 1988, and which at the time, according to economist and futurist Robin Hanson of George Mason University, caused a big splash in a small pond – the community of robotics and machine-learning experts to which Moravec belonged. The Data Analysis Moravec’s book is more philosophical treatise than technological manual, but the central idea is that cultural evolution has long since taken over from biological evolution as the most powerful force shaping humanity. The logical extrapolation of this is that the information that encodes our future selves would soon be packed into hardware and software rather than DNA. The Impact Analysis Angela Aristidou, who studies the real-life deployment of AI at University College London, is not surprised that Moravec’s book is enjoying a revival. She says that what in 1988 might have read like science fiction – and still might to most of us – looks eminently realisable to those in the know. The Prediction Hanson shares his conviction that the revolution is inevitable, as soon as AI attains something experts agree to call human-level intelligence. “We are going to generate an explosion of things like us in the future, who will be different from us in many ways,” Hanson says. “To the extent that they have minds somewhat like ours, they are our mind children.”

The Rise of Recursive Self-Improvement in AIThe word "recursion" is the latest buzzword in AI circles. Two separate startups have taken on the name, and many more have started referencing recursive self-improvement (RSI) in their roadmaps. Like AGI before it, RSI has become a three-letter byword for a cataclysmic AI takeoff – even if there's still a little disagreement about what it exactly means.In basic terms, RSI refers to an AI system that can continuously upgrade itself. Once AI systems can manage the upgrade cycle better than humans, the process can become a closed loop, limited only by the compute power they can access, and humans are no longer necessary or even helpful.Scary or not, that's a vision that a lot of AI labs are eager to chase.Key Players Pursuing Recursive SystemsEarlier this month, well-known AI researcher Richard Socher launched the aptly named Recursive Superintelligence with RSI as an explicit goal. "Our main focus is to build truly recursive, self-improving superintelligence at scale," Socher told TechCrunch at launch, "which means that the entire process of ideation, implementation, and validation of research ideas would be automatic."A number of other prominent researchers are already chasing that same goal, hoping for a breakthrough that will make recursive self-improvement possible.One of the most prominent is Andrej Karpathy, a legendary figure from Tesla and OpenAI, who is using agent swarms to train LLMs on simple tasks for a project he calls Auto-Research. Karpathy has been unusually open about the project, tweeting about milestones regularly and making the building blocks available through a public GitHub repo. So far, the work has mostly been confined to making minor improvements on a GPT-2 scale model — as Karpathy noted in March, "It's not novel, ground-breaking 'research' (yet)" — but it's been enough to convince lots of other researchers to follow the RSI dream. And with Karpathy now working on pre-training at Anthropic, he will have plenty of opportunity to apply the idea at a larger scale.Adaption — founded by Cohere and Google alum Sara Hooker — recently launched a similar tool called AutoScientist in an effort to automate frontier training. Like Karpathy's auto-researchers, the system trains agents to make incremental improvements — but for Adaption, the goal is to make it easier to train a full-scale frontier model. If those same researchers start to push the frontier forward, the system could quickly spiral into something very much like RSI.Disarray founder Doris Xin drew more specific RSI interest when her self-trained machine learning agent took home 28 medals in a recent Kaggle competition, beating out many human-trained agents. As she sees it, the major challenge is reliability."I would argue, given infinite compute and infinite time horizon, we are already there," Xin told me. "I want to make an argument that this is not a creative endeavor, really. It's just a lot of meat-and-potatoes engineering."The Current State of Self-Improving AIThere's also plenty of evidence that the AI industry isn't very close to recursive systems in any meaningful way — and is still grappling with talking to a wary public about its progress. So Google CEO Sundar Pichai basically admitted in a recent podcast interview."It's a continuum, and we are all definitely making progress," Pichai said. "But in the way people describe RSI, that would represent a next level of acceleration and would have a lot of implications, but we aren't quite there yet."But the continuum includes an awful lot of self-improving AI systems.In January, one of Anthropic's lead programmers for Claude Code estimated that "close to 100%" of his team's code was written by the tool — a frank admission that Claude Code was literally writing itself.Just because engineers are using an AI tool doesn't mean the tool can replace them — but Anthropic seems to be getting close to replacing engineers too. In a recent survey tied to the Mythos preview, five out of 18 Anthropic engineers believed that, with harness improvements, this version of Mythos could soon substitute for an L4 engineer — a midlevel programmer who can take on involved projects without supervision.Still, there were some of the same weaknesses you might expect."Some of Claude's major reported weaknesses compared to an L4 include: self-managing week-long ambiguous tasks, understanding org priorities, taste, verification, instruction-following, and epistemics," the report reads.In other words, its weaknesses are everything involved with self-direction, which is the cornerstone for RSI. But sure, for everything else, Claude is ready to step right in.Expert Perspectives on RSI TimelinesJust like the AGI term before it, the AI industry also can't tell us how far away it is from showcasing a meaningful recursive system. When Georgetown's Center for Security and Emerging Technology assembled a group of experts to study RSI last year, the group found a major split in assessments — some expecting an imminent "superintelligence" style explosion while others expected slower progress and an eventual plateau. But all agreed that recursion made the future especially difficult to predict.Helen Toner, director of CSET and a former board member at OpenAI, told TechCrunch that simply using AI tools to do AI research isn't enough to qualify as RSI. "They're just using AI for as much as they can," Toner told TechCrunch. "And I think that is different from the classic definition of RSI, which is really that there are no humans needed."Toner pointed to a recent post by METR's Ajeya Cotra, which distinguishes different milestones on the path to the AI research takeover. One step, which Cotra calls "adequacy," would come when the system can still perform research after all humans are removed — even if the resulting research isn't as valuable or efficient. "Parity" comes when an AI-only system is as good at research as a human-only system. "Supremacy," the final stage, comes when an AI-only system outperforms a collaborative system between humans and AI.Ultimately, Cotra concludes that AI is very close to the adequacy threshold of being able to produce some work on its own — similar to the incremental changes made by Karpathy's Auto-Research system. "I wouldn't be totally shocked if you told me this milestone had already passed, and I expect it to happen in the next couple years," Cotra wrote.She was less clear on when parity will come, but once it does, she thinks it would "massively accelerate the pace of AI progress, leading to AI research supremacy within another year."The Challenges Ahead for Recursive AIWith so much of AI built on scaling laws, there's a strong tendency to think RSI will follow the same curve. Toner thinks that many of those pursuing AI research and development via RSI "think of it as a pretty smooth ladder, where you can just keep scaling up."But even if AI researchers are able to make incremental improvements like Karpathy's auto-researchers, there will be larger challenges in handing off the whole process of research. Toner put it in terms of the history of computing, which has seen human beings handing off more and more of the process while still directing things from the top."We went from machine languages to assembly language and compiled languages; you're getting further and further from the guts of the computer," Toner said. "But the human is still, in some intuitive sense, running the show."Moving beyond that paradigm will take significant challenges, both in engineering and alignment. But even with the massive investments happening, there's no infinite compute available — and the basic trade-off between human labor and machine intelligence will be hard to overcome.The Future of Recursive Self-ImprovementAs for a total recursive AI system of apocalyptic visions? The only thing researchers essentially agree on is that, like AGI, it's not here yet.

Lead: A Papal Voice Joins the Global AI DebateThe Vatican has entered the AI ethics arena with Pope Leo XIV’s inaugural encyclical, Magnifica Humanitas, a 42,000‑word manifesto that puts humanity at the centre of the digital revolution. By partnering with Anthropic’s Christopher Olah, the Pope signals a rare alliance between religious authority and cutting‑edge AI research.Leo XIV Unveils “Magnifica Humanitas” Encyclical on AIOn 15 May 2026 the Vatican presented the encyclical, echoing Pope Leo XIII’s 1891 social teaching *Rerum Novarum*. The document catalogues the “daunting challenges” of artificial intelligence and calls on political leaders to safeguard human dignity as technology outpaces ethical regulation.Published in the Vatican’s official channels on 15 May 2026.Co‑presented by Christopher Olah, co‑founder of Anthropic.Frames AI as a moral, not merely technical, issue.Scope and Scale: 42,000‑Word Document Highlights AI RisksThe encyclical’s length underscores the depth of the Vatican’s analysis. Key statistics include:42,000 words covering AI’s impact on labour, healthcare, warfare, and personal autonomy.References to existing AI‑related legislation in the EU, US, and China.Calls for “state regulation” to ensure AI benefits are distributed equitably.Implications for Tech Industry, Regulation, and Moral DiscourseThe papal intervention arrives as US President Donald Trump postponed an executive order on AI safety reviews, highlighting a policy vacuum. The encyclical’s moral framing could influence:Corporate responsibility standards for firms like Anthropic, OpenAI, and Google DeepMind.Legislative momentum in Europe and the United Nations on AI governance.Public perception of AI, shifting the narrative from profit‑driven hype to human‑centred ethics.Critics have accused the Vatican of “pope‑washing,” but the collaboration suggests a willingness to engage with secular experts.Future Trajectory: From Papal Guidance to Global AI GovernanceIf the Vatican’s call gains traction, we may see:Increased inclusion of ethical clauses in AI development roadmaps.New international forums where religious leaders, technologists, and policymakers co‑draft standards.Potential pressure on tech CEOs—such as Elon Musk—to adopt more transparent, accountable practices.Ultimately, *Magnifica Humanitas* positions the Catholic Church as a moral stakeholder in the AI age, urging a future where technology amplifies, rather than diminishes, human flourishing.

The Pope's Warning on AIPope Leo XIV has called for the "disarming" of artificial intelligence (AI), warning that "new forms of slavery" are tied to its rise. The Catholic Church leader warned against "a race for ever more powerful algorithms and larger datasets," driven by "the desire to secure geopolitical or commercial dominance."The Encyclical: Magnifica HumanitasHis concerns regarding AI were presented in his first encyclical, titled "Magnifica Humanitas" (Magnificent Humanity), in person at the Vatican. Encyclicals are one of the highest forms of teaching from a pontiff to the church's 1.4 billion members.Leo insisted that ownership of AI data must not be left solely in private hands, called for policymakers to protect the rights of workers and keep children safe from the technology, and urged the cooling of competition between AI companies."What is needed is a more active political involvement that is capable of slowing things down when everything is accelerating," Leo said.The Catholic leader continued by calling for "robust legal frameworks, independent oversight, informed users and a political system that does not abdicate its responsibility"."AI now demands to be disarmed, freed from logics that turn it into an instrument of domination, exclusion, and death," he said. "Like nuclear energy, it must be at the service of all of the common good."Industry Response and ConcernsPope Leo presented the encyclical alongside AI experts, including Christopher Olah, co-founder of US giant Anthropic. Anthropic is embroiled in a legal battle with the United States military after opposing the use of its technology for lethal autonomous warfare and mass surveillance.At the presentation, Olah said AI companies operate "inside a set of incentives and constraints that can sometimes conflict with doing the right thing".He welcomed input from outside actors like the Catholic Church to "push events in a better direction", saying that "the questions raised by AI are bigger than the AI research community".Olah highlighted three areas he said required urgent attention: the risk of widespread job losses, the need to ensure that AI benefits are extended worldwide, and the unresolved question of how to interpret increasingly complex and sometimes opaque system behavior.Military AI and Ethical ConcernsIn the encyclical, Leo also sounded the alarm over AI-directed weaponry, saying it was "not permissible to entrust lethal" decisions to tech.Leo has repeatedly clashed with the White House over the US-Israel war on Iran and its use of religion to justify conflict.The "just war" theory, espoused recently by the administration of US President Donald Trump, was "outdated", Leo wrote, adding that "no algorithm can make war morally acceptable".

President Donald Trump announced that the administration will not sign the pending AI executive order, saying it could impede the United States' strategic advantage over China in the emerging artificial‑intelligence race. Executive Order on AI Put on Hold Over China Rivalry The draft order would have established a voluntary framework requiring AI developers to engage with the federal government before releasing advanced models. Sources familiar with the document told Reuters that the administration halted the plan after objections from the president and a lobbying push from Elon Musk and other tech leaders. Political and Strategic Context Behind the Delay Trump's China visit: The postponement comes shortly after the president’s first U.S. presidential trip to China in nearly a decade, where he described the meeting with Xi Jinping as “very successful.” Domestic pressure: House Republicans recently canceled a vote on a war‑powers resolution related to Iran, highlighting the administration’s focus on foreign‑policy priorities. Tech industry influence: Elon Musk publicly denied knowledge of the order’s contents and labeled related reports as false, indicating ongoing tension between the White House and Silicon Valley. Potential Implications for U.S. AI Policy and Industry Delaying the order preserves the status quo, allowing AI firms to continue development without a formal coordination mechanism. This could accelerate the rollout of powerful models but also raises concerns about oversight, safety, and export controls, especially as the U.S. and China vie for dominance in AI research and deployment. What May Come Next for U.S. AI Regulation Analysts expect the administration to revisit the framework once it can reconcile national‑security objectives with industry interests. Future steps may include targeted legislation, tighter export restrictions, or a revised voluntary program that addresses the president’s lead‑over‑China concerns while still providing a channel for government‑industry collaboration.