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The Rise of AI Financial MarketsThe most important market of the future could be in LLM tokens — and financial groups are rushing to build new infrastructure for them. China's Shanghai Futures Exchange is currently designing a derivatives market for AI tokens, while major derivatives exchanges CME Group and the Intercontinental Exchange (the owner of the NYSE) have separately announced they're working on launching futures contracts for renting GPUs.Building the AI Derivatives InfrastructureGPU markets are still maturing, but given the wide range of companies using, selling, and renting GPUs, there's already a robust market for spot prices on GPU rental, typically charged by the hour. This has prompted major financial players to develop futures contracts that would allow businesses to hedge against fluctuating compute costs.Enterprise plans for major AI companies are commonly denominated in tokens: OpenAI, for example, charges $5 per million input tokens, and $30 per million output tokens if you want to use the API for its latest GPT-5.5 model. Even cloud providers are increasingly offering the opportunity to charge per token, as in Amazon's Bedrock system.The Economics of GPU and Token PricingAccording to data from AI Mining Co., which tracks daily GPU rental pricing across 28 marketplaces and cloud providers, median prices for Nvidia H100 GPUs ranged from $1.40 to $4.27 per hour across 13 marketplaces, while the average price for H200 GPUs were between $2.34 and $5 per hour across 10 marketplaces.Just over the past seven days, average H100 prices ranged from $2.79 to $3.33, showing the volatility that makes futures contracts attractive for risk management.Transforming the AI Investment LandscapeThe effort comes amid an unprecedented buildout of AI infrastructure. Cloud service providers, private equity firms, and infrastructure players alike have poured hundreds of billions into building data centers, anticipating that demand for GPUs and compute will continue to rise.An emerging crop of global neocloud companies is also vying for a piece of this demand. Some of these new entrants are specializing, focusing on inference, while others are competing with cloud giants like Oracle, AWS, and Google Cloud to offer their services to AI companies.The Future of AI Financial InstrumentsBy targeting AI tokens, the Shanghai exchange's derivative product would be tied to how AI companies price their services, giving businesses, investors, and data center operators a way to hedge against the cost of compute. As AI becomes increasingly central to business operations, these financial instruments will likely become essential components of the technology investment ecosystem.

The Lead The United Nations has added Israel to a blacklist of countries and entities accused of using sexual violence as a weapon of war, prompting Israel to cut ties with UN chief Antonio Guterres. Israel's Response to the UN's Decision Israel's ambassador to the UN, Danny Danon, denounced the decision, saying, 'The decision to blacklist Israel and accuse us of using sexual violence as a weapon of war is an outrageous decision.' Danon added that Israel will have no contact with Guterres's office as long as he serves as head of the organisation. The Allegations Against Israel The UN's decision is based on allegations of sexual violence committed by Israeli security forces against Palestinian detainees in prisons and detention centers. The UN has cited 'credible information' regarding these allegations, which include torture and sexual violence. The Impact on Israel-Palestine Relations The move has further strained relations between Israel and the UN, which have been fraught since October 7, 2023, when Hamas launched an attack that preceded Israel's war on Gaza. Israeli authorities have criticized Guterres and other UN officials for their condemnation of its conduct in Gaza. The Future Outlook The addition of Israel to the blacklist is likely to have significant implications for Israel's international reputation and its relations with the UN. It may also lead to increased scrutiny of Israel's actions in Gaza and the West Bank.

Mauricio Pochettino is on the verge of a significant career shift, with reports confirming he is in talks with AC Milan to take over as manager next season. This development casts a spotlight on the end of his tenure with the US men's national team as they prepare for the 2026 World Cup on home soil.The European Pivot and World Camp ContextThe Guardian confirmed the talks, initially reported by journalist Nicolò Schira. Pochettino's status became a hot topic during the team's opening training camp at the US Soccer Federation's new center in Fayetteville, Georgia. Most analysts view the World Cup as the final chapter for the Argentine manager before a return to European club football.USMNT's Tight Timeline and Contract DynamicsThe USMNT has a packed schedule leading into the tournament, creating a tight window for Pochettino to finalize his move:Final friendly vs Germany (upcoming)World Cup opener vs Paraguay on 12 June at Los Angeles StadiumRegarding Pochettino's contract, US Soccer CEO JT Batson confirmed that while the manager has been transparent about club interest for years, no specific extension has been confirmed. Batson noted that succession planning is a monthly process, implying the federation is prepared for his departure.Managing the Distraction FactorThe looming exit has raised concerns about team chemistry, but the players seem unfazed. Tyler Adams, the USMNT midfielder, compared the situation to standard contract negotiations, stating that Pochettino remains fully present and focused on training. This suggests the squad is professional enough to handle the transition without internal friction.The End of the USMNT EraGiven the confirmed talks with a major European club like Milan and the CEO's comments on succession planning, it is highly probable that Pochettino will depart immediately after the World Cup concludes. The focus now shifts to who will replace him and how the team will adapt to a new leadership style during the tournament.

North American Nations Coordinate Ebola Response for World Cup The United States, Mexico, and Canada have announced aligned public health travel measures for people coming from African regions at greatest risk from Ebola as they prepare to host the World Cup next month. In a joint statement, the three nations emphasized that "the health and safety of every person in the region remains our highest priority as we welcome the world to North America." Coordinated Travel Restrictions Implemented The three neighboring countries have established various containment measures to prevent the spread of Ebola across their borders. The United States initially banned noncitizens who had traveled to the Democratic Republic of the Congo (DRC), Uganda, or South Sudan in recent weeks from entering the country. This ban was subsequently extended by the US Centers for Disease Control and Prevention to include green card holders who have been in those countries within the previous 21 days. Canada has implemented a 90-day entry ban for residents from the DRC, Uganda, and South Sudan. Additionally, Canadian citizens, permanent residents, and other foreign nationals who have been in affected areas without symptoms must undergo a 21-day quarantine period beginning Saturday. Mexico's Health Secretary David Kershenovich announced enhanced Ebola screening measures at airports, urging the public to avoid travel to the DRC and requiring arrivals from the country to observe a 21-day quarantine. WHO Declaration Triggers Global Response The World Health Organization declared an Ebola outbreak in the Democratic Republic of the Congo a public health emergency of international concern on May 17, warning of a high risk that the virus could spread to neighboring countries. This declaration has prompted governments worldwide to implement travel-related containment measures. The coordinated response by North American nations reflects the growing concern about potential transmission during the upcoming World Cup, which will bring together visitors from around the world. Impact on International Travel and Major Events These measures represent one of the most significant coordinated public health responses in recent years, affecting international travel patterns and potentially impacting the experience of fans and participants attending the World Cup. The restrictions may create challenges for travelers from affected regions and require additional resources for health screening at entry points across North America. The joint approach by the three host countries demonstrates a recognition that public health threats require unified responses, particularly when hosting international events that bring together people from diverse geographic locations. Future Outlook for Ebola Containment As the World Cup approaches, health officials will likely continue monitoring the Ebola situation closely, potentially adjusting restrictions based on the evolving outbreak status. The coordinated measures may set a precedent for how nations collaborate on public health responses during international events, particularly in an era of increasing global connectivity and potential disease spread. Success in containing this outbreak will depend not only on travel restrictions but also on effective public health measures within affected regions and continued international cooperation on disease surveillance and response.

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.

The Collapse of a 30-Match StreakJannik Sinner’s bid for a maiden French Open title and a career grand slam was abruptly halted on Thursday. The world No. 1 was forced to retire from his second-round match against Argentina's Juan Manuel Cerúndolo, succumbing to the extreme playing conditions rather than a lack of skill. The match ended in a 3-6, 2-6, 7-5, 6-1, 6-1 defeat, marking a significant psychological and statistical setback for the Italian star.Heatwave Takes Center StageThe defining narrative of this match was not the tactical battle between the top seed and the 56th-ranked opponent, but the relentless 33°C (91°F) temperature. Sinner dominated the opening two sets, winning them 6-3 and 6-2 with ease. However, the physical toll became evident in the third set when he was serving for the match at 5-4. After bending over in distress and leaving the court for medical attention, he returned but lost the set 7-5, eventually conceding the match in the fifth set.The Numbers Behind the DefeatStreak Broken: Sinner's 30-match winning streak, which dated back to February, came to an end.Ranking Gap: The match pitted the world No. 1 against the 56th-ranked Cerúndolo, a significant gap in form and ranking.Temperature: The match began at 29°C (84°F) and was forecasted to rise to 33°C (91°F), creating a grueling environment for endurance.The Physical Toll of Extreme ConditionsSinner's struggle highlights a recurring vulnerability for top players: adapting to extreme heat. This is not the first time the Italian has faced such challenges; he previously struggled against Eliot Spizzirri at the Australian Open in January, where the roof was closed to mitigate the heat. The sight of his light blue outfit soaked through with sweat and his visible distress off-court underscores the severe physiological stress players face in these conditions.Navigating the Elements in Grand Slam TennisAs the climate continues to impact major sporting events, the mental and physical resilience required to play in high temperatures is becoming a critical factor in tournament outcomes. Sinner's exit serves as a stark reminder that even the best players in the world are not immune to the elements. Future matches will likely see players needing to manage their energy levels more aggressively to survive the deciders.

General Compute, a new inference neocloud, raised a $15 million seed round at a $60 million post‑money valuation and booked a $300 million order for SambaNova’s upcoming SN50 chips. The company promises 600‑700 tokens per second per chip and a deployment model that fits into existing, air‑cooled data‑center infrastructure. General Compute’s Funding and Strategic Partnerships Seed round led by FUSE VC with participation from Carya Venture Partners and Village Global Ventures. Co‑founders Finn Puklowski (CEO) and Jason Goodison (CTO) partnered with SambaNova, an Intel‑backed chipmaker focused on inference. General Compute will be the first neocloud to deploy SambaNova’s SN50 chips, ordering $300 million worth of hardware. Colocation strategy includes traditional data‑center providers and repurposed crypto‑miner facilities. Financial Snapshot: $15 Million Seed and $300 Million Chip Order Seed funding: $15 million raised, valuing the company at $60 million post‑money. Chip commitment: $300 million of SN50 chips on order, enough to power a large inference fleet. Comparable market moves: Nvidia’s $20 billion acquisition of Groq (Dec 2025) and Cerebras’ $57 billion IPO (May 2026) illustrate the scale of inference‑focused investments. Implications for the AI Inference Landscape The shift from GPU‑centric training to specialized inference hardware is accelerating. SambaNova’s memory‑rich, flexible architecture claims to outperform GPUs, Groq, and Cerebras on token‑throughput, delivering 600‑700 tokens/sec versus ~250 tokens/sec for GPUs. Air‑cooled, low‑power chips lower the barrier to entry for colocation, enabling rapid deployment in existing facilities and even in repurposed crypto‑mining sites. This could democratize high‑speed inference, pressure pricing, and spur a wave of niche cloud providers focused on agent‑to‑agent workloads. What the Next Year May Hold for Inference‑First Cloud Providers When SambaNova releases its next‑gen chips later in 2026, General Compute’s early access positions it to capture a sizable share of the fast‑inference market. Expect: Increased competition among inference‑only clouds (e.g., CoreWeave, OpenRouter) to offer multi‑model routing and token‑cost optimization. More venture capital flowing into inference‑focused startups, mirroring the recent $113 million Series B for OpenRouter. Potential consolidation as larger players (Nvidia, Intel) seek partnerships or acquisitions to secure the most efficient inference stacks. Speed and cost efficiency will become the primary differentiators, shaping the architecture choices that dominate the AI future.

Visual Tour of U.S. Workplace Lactation Spaces The photo series walks readers through a variety of lactation rooms, from sleek corporate suites to modest community‑center setups. Each image captures the balance between privacy, comfort, and functionality that employers aim to provide. Privacy: Curtains, lockable doors, and sound‑proofing are common features. Comfort: Reclining chairs, footrests, and adjustable lighting appear in most locations. Convenience: Nearby sinks, refrigeration for milk storage, and charging outlets support daily nursing routines. Why Lactation Rooms Matter for Employee Well‑Being Beyond aesthetics, these spaces address critical health and equity concerns. Providing dedicated rooms helps reduce stress for nursing parents, supports infant nutrition, and aligns with broader diversity‑inclusion goals. Improved maternal health outcomes by facilitating continued breastfeeding. Enhanced employee retention as parents feel valued and supported. Compliance with state and federal regulations that mandate reasonable accommodations for nursing mothers. Future Outlook for Workplace Breastfeeding Support As more companies publicize their family‑friendly policies, the visual narrative suggests a trend toward standardized, high‑quality lactation environments. Continued advocacy and policy reinforcement are likely to expand access, especially in smaller firms and remote work settings.