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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 Plan for World Cup Glory As co-hosts, Canada enter the World Cup with high expectations, despite never winning a match at a previous tournament. Since a Concacaf Nations League semi-final defeat to Mexico in March 2025 the team have lost one of 15 matches at the time of writing, a run that has included some excellent opponents such as Colombia, Ecuador, Ukraine and the USA, whom they have defeated twice in the past two years, including their first win on US soil in 57 years. The coach, Jesse Marsch, has maintained a consistent 4-4-2 with the emphasis on pressing from the front and pace in wide positions. "Some teams press to win the ball back, we press to punish and think about scoring immediately when we recover the ball," said Marsch, who is American, but has captured the hearts of many Canadians since he took the job in May 2024 and guided the team to the semi-finals of the Copa América. Canada's World Cup Schedule 12 June v Bosnia and Herzegovina, Toronto (3pm local, 8pm BST) 18 June v Qatar, Vancouver (3pm local, 11pm BST) 24 June v Switzerland, Vancouver (noon local, 8pm BST) Success at that tournament, and subsequently in friendlies, is based on a defensive structure Marsch worked on immediately when taking the job and playing against the Netherlands and France in his first two matches in charge. Nine clean sheets in 13 matches before the pre-tournament friendlies is even more impressive considering Moïse Bombito, their star centre-back from Nice, and Bayern Munich's Alphonso Davies did not play in any of those matches because of injury. The Coach's Vision Jesse Marsch's first venture into international management has been a successful one, but not one he found easy to adjust to. "From the moment I worked with this group of players in the first camp, I knew I was going to fall in love with these guys," he says. "They are a unique group of really good people, who are very talented, and when I said goodbye to them it was different from what I was used to as a head coach in the club game." Marsch has enjoyed those gaps in his schedule, using time to visit Canadian players across the world and spending a lot of time in the country at the provincial level to help bring a more united approach to the way the game is developed and governed. Star Player's Return Questioned The captain, Alphonso Davies, has not played for Canada since tearing his ACL against USA in the Nations League third-place match last March. Whether to play him at left-back or on the wing has been one of the biggest questions for years, but under Marsch the Bayern Munich man has predominantly been used at the back and has been excellent. However, another injury setback, against Paris St-Germain in the Champions League semi-final second leg – his third in the past three months – has put his participation for the opening game against Bosnia and Herzegovina in doubt. He has started 12 of 29 internationals in the Marsch-era at the time of writing. One to Watch Few players have received more work and attention from his national coach than the midfielder Ismaël Koné, who was dropped during the Copa América as he struggled to make an impact. Since then he has been excellent for Sassuolo in Serie A and has turned into a dynamic box-to-box midfielder for Marsch, learning valuable lessons defensively in Italy, where his discipline and tactical concentration has improved significantly. Expected to start next to the excellent Stephen Eustáquio in a key double-pivot tandem for Canada. Unsung Hero Norwich's Ali Ahmed has become a favourite of Marsch's because of his selfless work on the pitch. Ahmed is asked to lead the press on the left wing, often cutting inside to increase the midfield numbers and bring intensity and energy off the ball. One of the reasons Marsch has not deployed Davies further forward is because he views his team without the ball more than with it and in that vision the former Vancouver Whitecaps man is crucial. Probable Starting XI Canada's likely formation for the World Cup matches will be based on the 4-4-2 system that Marsch has consistently employed, with specific attention to defensive structure and pressing from the front. Fan Expectations Canada is ready to host the world, but the attention is more on this team than other games happening in the country. Being the only side to start on the east coast and move directly to the west coast allows fans in Toronto and Vancouver to watch their team in the group stages. The supporters group The Voyageurs will lead the noise with their flags and chants of "Ooh, Ahh Canada". Canada is known for its cosmopolitan population and cultural diversity, with people from all over the world, and should benefit from playing three group opponents with relatively diverse fan bases.

The Road to Wembley Wigan Warriors are gearing up for a big presence at Wembley as they compete in the Challenge Cup finals on Saturday. The club has selected two players, Liam Farrell and Jenna Foubister, to represent them at a Wembley photoshoot, showcasing the team's strong squad and dedication to the sport. Wigan's Successful History Wigan have a remarkable record in finals, rarely losing two on the bounce. With 21 Challenge Cups under their belt, the team is driven by a strong mentality and a rich history of success. According to Farrell, 'There's a bit of outside pressure, an expectation from fans in the town to win. There's also a strong mentality at the club of Wigan lads, who have grown up watching us win finals, wanting to reproduce that themselves.' The Next Generation The club's academy graduates account for 20% of all Super League players, demonstrating Wigan's commitment to developing young talent. Foubister, a 19-year-old player, has already made her England debut and won the quadruple, highlighting the club's ability to nurture and support its players. 'The club put a lot into the youth system,' she says. 'They are very supportive in the way they shape players for the future.' A New Era for Women's Rugby Wigan have taken a proactive approach to providing for their female players, with the women's team having sole use of the revamped Edge Hall Road site. This move has helped to increase the team's fanbase and provide a platform for players like Foubister to develop their skills. 'It is a privilege having our own ground,' she says. 'We can go up whenever we want and have the freedom to train, whereas at Robin Park you got slotted in at a certain time.' Building a Legacy As Farrell's career enters its final phase, Foubister aims to become a hero in her hometown and build a legacy for the women's team. 'The men have a lot of history behind them, but the women's team has to build a history of our own now,' she says. With the support of the town and the club, Foubister and her teammates are well on their way to achieving their goals.

IOC President Kirsty Coventry sparked a social‑media firestorm by declaring athletes should not be paid prize money at the Games, prompting a wave of criticism from Olympians worldwide.Coventry’s anti‑prize‑money stance fuels athlete criticismDuring an interview with New Zealand outlet Sport Nation, Coventry said, “I don’t believe in paying athletes… I come from a small country… I still don’t think we should be paying athletes at the Olympic Games.” She added that the IOC should focus on talent identification and support for athletes from smaller nations. The remarks arrived on her first Oceania visit as the first woman and first African chief of the IOC.Prominent athletes responded on Instagram, with Cameron McEvoy calling the timing “inopportune” after the controversial Enhanced Games offered lucrative payouts. Former champions Filippo Magnini, Grant Hackett, Roland Schoeman, and others echoed the sentiment that athletes sacrifice without financial reward.Financial figures underline the controversy$12.4 b – total revenue generated by the IOC in the 2021‑2024 cycle.74 % – portion of that revenue redistributed back into international sport.$250,000 – prize awarded per gold medal at the Enhanced Games.$1 m – bonus earned by swimmer Kristian Gkolomeev for a “world‑record” at the same event.$350,000 – reported annual salary for the IOC president.Broader impact on Olympic governance and athlete rightsThe backlash has revived calls for an athletes’ union and a review of the IOC’s use of athletes’ name, image, and likeness (NIL). Critics point to the World Athletics decision to award $50,000 for Olympic gold as a benchmark, while questioning why the IOC, which commands billions, does not adopt a similar model.Former champion Greg Rutherford and Paralympic star Hunter Woodhall labeled the stance “embarrassing” and urged faster formation of a union. The debate also intersects with recent controversies over gender‑verification policies and past financial scandals involving the former president Thomas Bach.What’s next for IOC compensation policies?Analysts suggest the mounting pressure could force the IOC to explore NIL‑type arrangements or introduce modest prize pools to retain athlete goodwill. If the union movement gains traction, the organization may face a governance overhaul similar to the NCAA’s 2021 NIL reforms.Until a concrete policy shift is announced, the conversation around athlete compensation is likely to dominate Olympic discourse in the lead‑up to the 2028 Los Angeles Games.

Bloomberg Leaks Reveal New Siri App Integrated with Dynamic Island Just before WWDC in June, Bloomberg published leaked renders of Apple’s upcoming AI upgrade for the iPhone. The screenshots depict a brand‑new Siri app that will launch from the Dynamic Island and replace the traditional button‑press activation in iOS 27. Users will also be able to swipe down on the home screen—leveraging the familiar Spotlight gesture—to invoke AI‑powered searches. Scale Advantage: Apple’s 2.5 Billion Devices vs ChatGPT’s 900 Million Users Apple’s install base: 2.5 billion active devices across iPhone, iPad, Mac, and wearables. ChatGPT weekly active users: 900 million. iOS version introducing the feature: iOS 27. New Siri app will support text, photo, and document uploads and retain chat history. Strategic Shift: Apple Leverages Google’s Gemini to Accelerate AI Rollout The leaked details confirm that Apple’s rebuilt AI model runs on Google’s Gemini technology under the hood. This mirrors Apple’s earlier multibillion‑dollar partnership that made Google the default search engine on iPhone. By tapping Gemini, Apple sidesteps the massive R&D costs of building a large‑scale model from scratch while still delivering cutting‑edge capabilities. Apple is also developing local AI models that run directly on devices, reinforcing its privacy‑first brand and reducing reliance on cloud processing. What Apple’s AI Push Means for the Mobile AI Landscape Post‑WWDC Analysts expect Apple to announce the standalone Siri app at WWDC, positioning it as a direct competitor to ChatGPT, Claude, and other generative chatbots. The integration with Dynamic Island and Spotlight suggests a seamless, on‑device experience that could accelerate user adoption, especially among the billions who have not yet embraced third‑party AI tools. If Apple rolls out the feature globally in the next iOS update, the company could leverage its massive ecosystem to set new standards for privacy‑preserving, AI‑enhanced mobile interactions.

The Shocking Exit at Roland GarrosJannik Sinner's bid for a maiden French Open title and career Grand Slam went up in smoke as he experienced physical issues in his second-round match against Juan Manuel Cerundolo and fell to a 3-6 2-6 7-5 6-1 6-1 defeat. The 24-year-old Italian arrived in Paris as the clear favorite for the title, having lifted claycourt titles in Monte Carlo, Madrid and Rome, with his main rival and defending champion Carlos Alcaraz ruled out with injury and Novak Djokovic searching for his best form.The Dramatic Turn of EventsBut Cerundolo tore up the script in a dramatic clash on a scorching Thursday where he held his nerve even as last year's runner-up Sinner crumbled while on the verge of a big win, sending shockwaves through Roland Garros. As the temperature climbed over the 30 degrees Celsius (86F) mark for the first time in the afternoon, Sinner had already breezed through the first set on the back of a solitary break, and looked to be in cruise mode.The Physical Toll of the MatchCerundolo offered resistance towards the end of the second set, but the 56th-ranked Argentinian was left with a mountain to climb after Sinner unleashed a huge forehand winner to double his lead in the match for the loss of only five games. The four-time Grand Slam champion cooled off with an ice towel in the break and turned up the intensity on his unseeded opponent in the third set to go 5-1 ahead, before he began to struggle and halted play when serving at 5-4.The Comeback VictorySinner returned from an off-court medical timeout five minutes later and was immediately broken for 5-5, and dropped the next two games to hand the set to his opponent, who sensed the chance to pull off a major upset. Still not at his best, Sinner surrendered the fourth set tamely and was broken early in the decider, as Cerundolo took full advantage to leave the Grand Slam without its title favorite.The Tournament AftermathSinner's unexpected exit creates a wide-open draw at Roland Garros, with the top half of the men's bracket now lacking a clear favorite. The Italian's physical concerns may also raise questions about his preparation for the upcoming grass court season, including Wimbledon. For Cerundolo, the victory represents the biggest win of his career and establishes him as a dangerous floater in the tournament, with the confidence to challenge remaining players.

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 Enterprise AI Market's Critical ShiftEnterprise organizations are not rejecting AI technology itself—they are rejecting operational instability. This fundamental misunderstanding is separating successful AI companies from those that stall after initial momentum, according to Databricks co-founder Arsalan Tavakoli-Shiraji.For years, AI startups benefited from a market driven by experimentation where impressive demos and powerful visions were sufficient to generate interest. Now, enterprises have moved beyond evaluating whether AI is exciting—they're assessing whether it's safe to deploy broadly.Tavakoli-Shiraji's Disrupt 2026 SessionAt TechCrunch Disrupt 2026, taking place October 13-15 at Moscone West in San Francisco, Tavakoli-Shiraji will unpack this critical shift during his AI Stage session, "The Enterprise Isn't Broken. Your Assumptions About It Are."The event will bring together 10,000+ founders, investors, and operators to explore technologies and operational pressures changing how companies are built and scaled, featuring 250+ sessions across six stages led by tech leaders.The Operational Reality of Enterprise AIThe enterprise AI market is filled with successful pilots that never became real deployments—not because the technology failed, but because organizations couldn't absorb the operational consequences of adoption.Startup AI deals rarely die because models underperform. They fail because enterprises lose confidence in what deployment would require. This distinction is crucial as many AI startups continue optimizing for initial excitement rather than long-term operational adoption.The New Enterprise AI Success FactorsAI startups gaining traction in large organizations increasingly share one common trait: they reduce uncertainty. They integrate cleanly into existing systems, create less workflow friction, and are easier to govern, explain internally, and trust over time.Enterprise buyers are now asking different questions:How will this affect our existing workflows?What happens when something goes wrong?How do we control and explain the outputs?What does deployment actually require from our teams?The Future of Enterprise AI AdoptionThe startups that succeed in enterprise AI over the next several years may not necessarily have the most advanced models. They will likely be the ones that best understand how enterprises actually absorb change.Tavakoli-Shiraji brings valuable perspective to this conversation, with a background spanning both enterprise strategy and technical systems architecture. Before joining Databricks, he was an associate principal at McKinsey & Company, advising enterprises on cloud computing and transformation strategy, and earned a PhD in computer science from UC Berkeley.

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.