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The Plan Switzerland has qualified for the World Cup for the sixth time in a row and will head to the US west coast with high expectations. Coach Murat Yakin has set ambitious goals, stating, "We want to play the best World Cup seen from a Swiss team." Switzerland's World Cup History Switzerland has never advanced past the quarter-finals at the World Cup, with their last appearance at that stage being in 1954 on home soil. They have typically been eliminated in the last 16, as seen in their 2022 loss to Portugal. Group B Fixtures 13 June v Qatar, San Francisco (noon local, 8pm BST) 18 June v Bosnia and Herzegovina, Los Angeles (noon local, 8pm BST) 24 June v Canada, Vancouver (noon local, 8pm BST) The Coach: Murat Yakin Murat Yakin's appointment as coach in August 2021 was a surprise, given he was managing second-tier FC Schaffhausen at the time. Despite some challenges, he extended his contract to 2028 after a positive Euro 2024. Star Player: Granit Xhaka At 33, Granit Xhaka remains Switzerland's most important player, dictating the tempo of the game and ensuring a balance between defense and attack. This could be his last World Cup, but he may continue his international career afterward. One to Watch: Johan Manzambi Johan Manzambi, a Geneva-born midfielder, has impressed with his performances at Freiburg. Europe's top clubs are monitoring him, and he could become one of the most expensive Swiss transfers after the World Cup. Unsung Hero: Remo Freuler Remo Freuler, a midfielder from Zurich, has worked hard to reach the top. He complements Xhaka well in midfield, excelling in running capacity, one-on-one situations, and footballing intelligence.

The LeadThe Guatemalan government has firmly denied reports that it agreed to permit United States military strikes against drug traffickers within its borders, while simultaneously confirming its request for security cooperation with Washington. This clarification comes amid growing concerns about US military operations in Latin America and the complex relationship between regional governments and Washington's anti-drug policies.The Government's Position on Military Operations"There is no agreement authorising foreign military operations by any country within national territory," the government of President Bernardo Arevalo stated in a formal release on Thursday. This denial directly responds to a New York Times report citing unnamed sources who claimed Arevalo had agreed to US military action in Guatemala.Accompanying the government statement was a note from a letter by Guatemala's Defense Minister Henry Saenz to his US counterpart Pete Hegseth, dated May 28. The letter reveals that Guatemala "desires to lead, with US assistance, active military operations" against drug groups identified as "designated terrorist organisations" (DTOs) by Washington."In accordance with existing bilateral agreements and arrangements, such combined Guatemala-led operations would further bilateral interests in defeating DTOs and advancing regional and hemispheric security," Saenz wrote in the document.The Regional Context of US Anti-Drug OperationsThe Guatemalan clarification emerges against a backdrop of increasingly assertive US anti-drug policies in Latin America. Under President Donald Trump, the United States has demonstrated a willingness to use military force in the region, including conducting air strikes against alleged drug boats in the Caribbean Sea and Pacific Ocean.These operations have resulted in at least 194 deaths and drawn criticism from rights advocates who characterize them as extrajudicial killings. The US has also taken more direct action, including the abduction of Venezuela's President Nicolas Maduro in January, whom it accused of drug trafficking.Following Maduro's removal, his vice president Delcy Rodriguez has improved relations with Washington and allowed greater foreign involvement in Venezuela's oil sector, though the US continues to exert control over the country's oil exports.The Impact on US-Latin America RelationsMany countries in Central and South America have struggled to contain gang violence related to the drug trade, creating a complex security landscape. In January, Guatemala's Arevalo declared a 30-day state of emergency after suspected gang members killed at least 10 police officers, highlighting the severity of the security challenges.Latin American leaders have consistently demonstrated a nuanced approach to US involvement - wary of direct military intervention but open to intelligence sharing and security cooperation. This delicate balance reflects both the genuine security needs of these nations and the historical sensitivities surrounding US intervention in the region.President Arevalo, elected in 2023 on an anticorruption platform, appears to be navigating this complex terrain carefully, seeking assistance while maintaining sovereignty over military operations within Guatemala.Future Outlook for Regional Security CooperationThe situation in Guatemala suggests a likely continuation of this pattern of conditional cooperation. Regional governments will likely continue to seek US assistance in combating drug trafficking and organized crime while resisting direct military operations on their soil.The coming months may see increased diplomatic efforts to define the boundaries of security cooperation, with Guatemala potentially serving as a model for other nations seeking to balance security needs with sovereignty concerns.As the US continues its anti-drug operations in Latin America, the region's response will likely shape the future of hemispheric security policies and determine whether cooperation can be achieved without compromising national sovereignty.

The Office of Personnel Management (OPM) released a draft directive that would require all current and former federal employees to sign a non‑disclosure agreement (NDA) before speaking to the press, signaling a new wave of information control from the Donald Trump White House.Proposed NDA Directive Unveiled by OPMThe guideline, announced on Tuesday, states that violations could trigger legal action by the White House. It expands the definition of “confidential” beyond traditional intelligence classifications to cover internal agency operations, personnel matters, procurement processes and any pre‑decisional material not publicly available.Timeline and Procedural Numbers Behind the Rule30‑day public comment period once the rule is published in the Federal Register.Implementation timeline not specified; individual agencies must opt‑in.Agreements would also bind former employees who have signed the NDA.OPM spokesperson McLaurine Pinover framed the move as a response to “unauthorized disclosures” disrupting agency work.Potential Ripple Effects on Government Transparency and Whistleblower ProtectionsCritics argue the blanket NDA could “kneecap” whistleblower safeguards and undermine the First Amendment.The Freedom of the Press Foundation’s Lauren Harper called the policy “dangerously secretive.”Existing federal law already protects employees who report fraud, abuse or misconduct to internal watchdogs or Congress; the draft claims the NDA would not apply to those disclosures.Past White House actions include banning the Associated Press from the press pool and restricting Pentagon media access, moves previously ruled unconstitutional.What Legal and Political Battles May FollowPotential lawsuits from media organizations and civil‑rights groups challenging the rule’s constitutionality.Congressional hearings could pressure the administration to revise or withdraw the directive.Judicial injunctions may arise, similar to prior rulings against White House media restrictions.If upheld, the NDA could set a precedent for broader governmental control over public information.

The LeadStrictlyVC is set to host its exclusive Los Angeles event on Thursday, June 18, 2026, at The Aerospace Corporation Campus in El Segundo. The intimate gathering will bring together leading investors and entrepreneurs for high-signal conversations about venture capital and frontier technologies, with a special focus on defense technology and physical AI.The Event DetailsThe StrictlyVC Los Angeles 2026 event offers an evening of direct access to ideas and leaders shaping where technology and capital are headed next. The event will feature several key speakers discussing critical topics in the tech investment landscape.Date: Thursday, June 18, 2026Location: The Aerospace Corporation Campus, El Segundo, Los AngelesFocus: Defense technology, physical AI, venture capital, and frontier technologiesThe Value PropositionFor executives, investors, and founders navigating an increasingly complex market, this event provides a rare opportunity to step inside conversations that rarely happen in public. Attendees will hear directly from the people driving change across defense, AI, and advanced industry sectors.Featured Speakers and TopicsThe event will begin with Ethan Thornton, founder of Mach Industries, presenting "Built for a New Era of Defense Technology." Thornton will discuss building hard tech companies at speed and why defense innovation is undergoing a structural shift as autonomy, manufacturing, and national security become increasingly interconnected.The conversation will then turn to "backing the next frontier of physical AI," featuring Delian Asparouhov of Founders Fund and Saif Khawaja of Shinkei Systems. They will explore how advances in AI, robotics, and automation are reshaping both software systems and the physical world, and what it takes to move breakthrough technologies from concept to real-world deployment at scale.Additional speakers and conversations will be announced in the weeks ahead as the StrictlyVC Los Angeles agenda continues to take shape.The Impact AnalysisThis event reflects a growing trend of technological acceleration in traditionally slow-moving industries. The focus on defense technology and physical AI indicates a significant shift in venture capital priorities toward tangible, real-world applications of artificial intelligence. As these technologies mature, they have the potential to reshape national security, manufacturing, and automation sectors, creating new opportunities and challenges for investors and entrepreneurs alike.The PredictionAs the evening unfolds, the real value of the event will emerge from the conversations that continue beyond the stage. In an environment defined by access, focus, and proximity to industry leaders, introductions are likely to turn into insights, and insights often turn into opportunities. This event is poised to become a catalyst for new partnerships, investments, and technological breakthroughs in the defense and physical AI sectors, potentially setting the stage for the next wave of innovation in these critical areas.

The Launch of Sesame's Conversational AI On Thursday, the AI startup Sesame, co-founded by Oculus' founders and others from the VR company that sold to Meta, released a public preview of the conversational AI agents it's been developing for over a year. With its new iOS app, Sesame is rethinking the traditional AI chatbot experience popularized by apps like ChatGPT, creating one where conversation flows, even if the AI needs time to think. Reimagining AI Conversation Flow As the company explains in its launch announcement, "There's an inherent tension between replying quickly and taking the time to compose thoughtful responses. A slower response is usually more correct, but it can also feel unnatural if it takes too long." To address this challenge, Sesame claims to have built fast search and retrieval systems, so the AI can have up-to-date information, as well as technology that allows it to run multiple parallel searches while speaking, weaving those results into its responses as it talks. That means the AI will talk more like a human, even pivoting mid-sentence if need be, as it taps into newer information — as a human might when remembering another key fact or point they want to add. User Growth and Development Milestones The app offers four distinct AI agents called Maya, Miles, Simone, and Charlie, each of which have their own distinct voice, personality, point of view, and memory. Maya and Miles were previously available in Sesame's Research Preview of its technology, where they were soon accessed by over one million people within the first few weeks, said Sesame investor Sequoia at the time. (The company had then just raised its $250 million Series B from Sequoia and others and was opening up a beta.) During the beta, Sesame learned from user feedback and rolled out features such as search cards with image results for visualizing concepts, notes for capturing takeaways, a texting mode for those times when speaking aloud is not an option, and support for deep dives where you can get more in-depth results. There's also a new incognito mode for private conversations, which allows the agents access to prior context but saves nothing to memory. Transforming the AI Landscape The app, however, is only the first step toward Sesame's bigger plans for AI involving intelligent eyewear, which the team expects to launch in 2027. Before that, the agents will also learn to do more than just think with you, Sesame hints, suggesting they'll later be able to take action on your behalf — hence why they're called "agents" in the first place, instead of just chatbots. That is potentially even more interesting, as working with agentic tools or apps today requires being able to prompt for what you need and have a specific idea of what you want to happen, and sometimes, even how it should happen. A conversational agent that you could talk to naturally could help you take the next steps, without you having to perfect the command you're giving it. The Road to AI-Powered Eyewear The iOS app is out today in 39 countries, and the full experience is free for the time being. However, there still may be a short waitlist at sign-up. An Android preview is coming in the future, the company says.

The Strategic Shift in iOS 27Just ahead of Apple’s Worldwide Developers Conference (WWDC) in June, leaked renders reveal a significant overhaul of the iPhone's interface, driven by a new generation of AI capabilities. The most visible change is the integration of Apple’s AI upgrade directly into the user experience, moving beyond simple voice commands to a comprehensive, card-style interface.The Dynamic Island as the AI Command CenterThe iconic black pill-shaped area at the top of the screen, known as the Dynamic Island, is set to become the central hub for AI interactions. While users can still trigger Siri via a button press, the primary mode of interaction will shift to the Dynamic Island. This allows for quick voice queries and searches, mimicking current usage patterns while offering a richer visual output.Furthermore, Apple is capitalizing on muscle memory by integrating AI-powered search into the swipe-down gesture. This feature, powered by a rebuilt AI model using Google's Gemini technology, allows users to search, launch apps, send messages, and manage calendar events directly from the search card.Scale as Apple's Competitive AdvantageApple’s primary weapon in this AI race is its sheer scale. With a total install base of 2.5 billion devices, Apple has an unmatched runway to introduce AI to users who have not yet adopted standalone tools like ChatGPT. While ChatGPT boasts 900 million weekly active users, Apple’s ecosystem offers a frictionless entry point for millions of new users.A Hybrid Approach to AI DevelopmentApple’s strategy mirrors its successful partnership with Google for search: leveraging external technology to meet immediate user demand while simultaneously developing proprietary solutions. By utilizing Google's Gemini under the hood for cloud-based intelligence and investing in local AI models for on-device processing, Apple aims to maintain its privacy-first brand without the prohibitive costs of building a massive AI infrastructure from scratch.The Standalone Chatbot ChallengerIn addition to system-wide integration, Apple is developing a dedicated Siri app designed to compete directly with market leaders like ChatGPT and Claude. This standalone application will feature past chat history, document uploads, and photo analysis, providing a robust alternative for users seeking advanced AI assistance.

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.

YouTube announced on May 28, 2026 that its Premium service will soon include an AI‑powered podcast recommendation tool, an “Auto speed” playback feature, and an on‑the‑go listening mode, aiming to deepen engagement with its growing podcast audience. AI‑Driven Podcast Recommendation Engine Launches The new recommendation tool leverages the same generative AI behind YouTube’s "Ask Music" to suggest podcasts based on genre, listener mood, or shows already enjoyed. Premium users will see personalized suggestions directly in the Podcasts tab, streamlining discovery without leaving the app. Auto Speed Playback and On‑the‑Go Mode Arrive on Android First Auto speed: Dynamically adjusts playback speed during slower speech or dense segments, preserving comprehension while reducing total listening time. On‑the‑go mode: Adds quick‑skip controls, episode‑jump shortcuts, and background‑play optimization for activities like running or commuting. Both features are live for Premium users on Android and will roll out to iOS in the coming months. Premium Podcast Consumption Metrics Highlight Growth Potential Premium users logged over 800 million hours of podcast playback in April 2026. YouTube Podcasts now boasts more than 1 billion monthly active users. The platform’s "Ask Music" already powers personalized radio stations, indicating a ready AI infrastructure for podcast recommendations. Strategic Play to Capture Audio‑First Audiences By enhancing discovery and hands‑free listening, YouTube is positioning itself against established audio platforms such as Spotify and Apple Podcasts, while also responding to Netflix's recent push into video podcasts. The focus on AI personalization and adaptive playback reflects a broader industry shift toward seamless, user‑centric audio experiences. What This Means for the Future of Podcast Platforms Analysts expect the AI recommendation engine to increase user retention, potentially driving Premium subscription growth by double‑digit percentages over the next year. If the Auto speed feature delivers measurable time‑saving benefits, it could set a new standard for intelligent playback, prompting competitors to develop similar adaptive technologies. The on‑the‑go mode further blurs the line between video and audio consumption, suggesting that YouTube will continue to integrate podcasting deeper into its core ecosystem.

Visa has disclosed an undisclosed investment in AI coding platform Replit, aiming to embed its payment suite directly into the developer environment so that both developers and AI agents can accept payments without leaving the platform. Strategic Investment and Joint Exploration of AI‑Powered Payments The two companies are testing how Visa Intelligent Commerce and the Trusted Agent Protocol can be woven into Replit’s workflow. More than 1,000 Visa employees already use Replit for prototyping, and the collaboration remains in an exploratory stage with no formal product announcements. Valuation Surge and Funding Milestones Highlight Replit’s Growth September 2025: Replit reached a $3 billion valuation. March 2026: Raised $400 million in a Series D led by Georgian Partners, pushing valuation to $9 billion. Enterprise self‑serve contracts now allow deals up to $200,000 without sales interaction. Customer churn is described as "very, very low" with net retention hitting 300 % in some cases. Implications for the Emerging Agentic Payments Ecosystem The move underscores a broader race to build infrastructure for "agentic payments," where AI agents transact on behalf of users. Competitors such as Robinhood (agent‑driven trading) and Google (shopping agents) are pursuing similar capabilities, suggesting the market will soon demand secure, verifiable AI‑mediated transactions. Future Trajectory: From Prototype to Mainstream Agentic Commerce If the exploratory projects mature, Replit could become a one‑stop shop for developers to build, host, and monetize AI agents, accelerating adoption of Visa’s Trusted Agent Protocol. Analysts anticipate that as enterprise adoption grows and churn remains low, the partnership may evolve into a commercial product suite within the next 12‑18 months, positioning Visa and Replit at the forefront of the next wave of AI‑driven commerce.