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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 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 Controversial Stoppage Rico Verhoeven, the Dutch former kickboxer who has switched to boxing, wants an apology as well as a rematch, after being stopped one second before the end of the penultimate round in a WBC title bout with unified world heavyweight champion Oleksandr Usyk last Saturday. The Event Details The stoppage was controversial, with Verhoeven feeling he could have continued and some replays suggesting the bell may have rung before the referee signalled the end of the fight — only Verhoeven’s second since switching to boxing — at the Pyramids of Giza in Egypt. The Data Analysis Scorecards published by The Ring magazine afterwards showed two of the three judges had the fight tied 95-95 going into the 11th of 12 rounds and the other had Verhoeven ahead 96-94. The Impact Analysis “[I want] just an apology. What else can we do? I can’t demand anything else,” Verhoeven told the BBC on Thursday, adding that his team had lodged an appeal with the WBC. The Prediction Germany’s Agit Kabayel is the WBC’s mandatory challenger and Usyk could have to fight him first before any rematch with Verhoeven. “Let’s see what pops up next,” said Verhoeven. “But I have to be honest, it’s got to be big. I feel like I’m the uncrowned king.”

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 Lead: Apple's AI RevolutionJust ahead of Apple's Worldwide Developers Conference (WWDC) in June, Bloomberg has published leaked renders of what Apple's planned AI upgrade could look like on iPhone — including a brand-new Siri app meant to rival ChatGPT and other AI chatbots. This represents Apple's most significant push into the competitive AI landscape, leveraging its massive user base to introduce AI capabilities to billions of devices worldwide.The Event Details: New Siri Interface and CapabilitiesWhile users will still be able to press a button in iOS 27 to trigger Siri, the animation and response will now emerge from the iPhone's Dynamic Island — that's the black pill-shaped area at the top of the screen that today houses Live Activities. This mode will work best for quick voice queries or searches, maintaining familiarity for existing Siri users.A new mode will put Siri-powered search within easy reach, capitalizing on people's muscle memory for swiping down on their screen to access Spotlight Search. The swipe-down gesture will still open search, but now those searches will draw on the AI-powered Siri, which includes a rebuilt AI model that uses Google's Gemini AI technology under the hood for added intelligence.From here, iPhone users can search, launch apps, start messages, ask about the weather, add calendar appointments, search their notes, and trigger app shortcuts, with results displayed in formatted text in a card-style interface that also emerges from the Dynamic Island.The Data Analysis: Strategic Partnerships and Scale AdvantageApple's approach to AI mirrors its earlier multibillion-dollar partnership with Google that made Google the default search engine on iPhone. Just as building a search engine from scratch was never in Apple's playbook, AI presents a similar calculus — it's too expensive and complex to go it alone, at least right now. So Apple is working with outside partners for AI technology that users want today, while simultaneously building out its own models, including local AI that runs on local devices rather than the cloud.The scale advantage is substantial. While ChatGPT now has 900 million weekly active users, Apple's install base (all devices, not just iPhone) is 2.5 billion — meaning the company has an unmatched runway to introduce AI to people who haven't yet adopted standalone AI tools.The Impact Analysis: Shaping the AI LandscapeApple's entry into the competitive AI chatbot space with a standalone Siri app will significantly reshape the market dynamics. The app will surface users' past chat history and allow them to upload documents and photos, in addition to text, positioning it as a direct competitor to ChatGPT, Claude, Gemini, and others.This move demonstrates Apple's strategy of leveraging partnerships while maintaining its privacy-focused brand. By using Google's Gemini AI technology while developing local AI capabilities, Apple aims to deliver powerful AI experiences without compromising on its core privacy principles. This approach could set a new standard for how tech companies balance powerful AI features with user privacy concerns.The Prediction: Future of AI IntegrationLooking ahead, Apple's AI strategy appears focused on seamless integration rather than standalone dominance. The company is likely to continue its dual approach: leveraging partnerships for immediate capabilities while developing proprietary technology for long-term differentiation.As Apple rolls out these AI features across its ecosystem, we can expect to see similar AI-powered enhancements in macOS, iPadOS, and watchOS. The company's emphasis on local AI processing suggests a future where more AI tasks happen on-device, reducing latency and enhancing privacy — potentially setting a new industry standard that other tech companies will need to follow.

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.

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.

Anti‑immigrant anger is reaching a new peak in South Africa as municipal officials ordered the removal of makeshift camps that housed thousands of migrants, leaving them exposed on public streets. The move has ignited protests, a surge in xenophobic incidents, and a heated debate over the nation’s immigration policy. Escalating Xenophobic Tensions After Forced Evictions City councils in Johannesburg and surrounding townships issued eviction notices this week, citing health and safety concerns. Residents of the cleared camps report being given less than 24 hours to vacate, with many forced to sleep on sidewalks or in overcrowded shelters. Evictions began on 2026-05-25 across three major informal settlements. Local NGOs estimate that over 5,000 migrants were displaced. Community leaders claim the actions were taken without adequate consultation. Limited Data Highlights a Growing Crisis Official statistics on the displacement are scarce, but available reports point to a sharp rise in xenophobic activity: The South African Police Service logged a noticeable uptick in hate‑crime complaints in the past month. Human‑rights groups note an increase in verbal and physical attacks targeting foreign nationals. Economic analysts warn that prolonged unrest could deter foreign investment. Political Fallout and Social Cohesion at Risk The government’s response has split opinion. While some politicians defend the evictions as necessary for public order, opposition parties and civil‑society groups accuse the administration of stoking xenophobia. President Cyril Ramaphosa called for “orderly migration management” but avoided direct criticism of local authorities. Opposition leader John Steenhuisen demanded an immediate halt to evictions and a review of immigration policy. International bodies, including the UN, have urged South Africa to uphold the rights of migrants. Potential Policy Shifts and International Scrutiny Analysts predict that sustained pressure could force the government to adopt a more coordinated approach: Implementation of a national framework for temporary housing of displaced migrants. Increased funding for community‑integration programs to mitigate xenophobic sentiment. Possible sanctions or aid reductions from foreign partners if human‑rights violations continue. Until concrete measures are taken, the risk of further unrest remains high, and South Africa’s reputation as a regional hub for trade and tourism could suffer.