Breaking AI & Tech News Analyzed

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 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 Lead Enterprise organizations are not rejecting AI. They are rejecting operational instability. The Event Details At TechCrunch Disrupt 2026, taking place October 13–15 at Moscone West in San Francisco, Arsalan Tavakoli-Shiraji, co-founder and SVP of field engineering at Databricks, will discuss the shift in enterprise AI adoption during his AI Stage session, “The Enterprise Isn’t Broken. Your Assumptions About It Are.” The Data Analysis The enterprise AI market is full of successful pilots that never became real deployments. Not because the technology failed. But because the organization could not absorb the operational consequences of adopting it. The Impact Analysis The market is maturing. Enterprise buyers are asking different questions now. They are evaluating whether AI products are safe to deploy broadly, and whether they integrate cleanly into existing systems, create less workflow friction, and are easier to govern. The Prediction The startups that succeed in enterprise AI over the next several years may not necessarily be the ones with the most advanced models. They may be the ones that best understand how enterprises actually absorb change.

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.

Kouame's Stunning French Open Win France's Moise Kouame has become the youngest man since Rafael Nadal in 2003 to reach the third round of a Grand Slam with a stunning match tie break victory against Paraguay's Adolfo Daniel Vallejo. Matching Nadal's Record Kouame, 17, became the youngest Grand Slam match winner for 17 years when he beat former US Open champion Marin Cilic in the first round. His feat, matching that of Nadal at Wimbledon 20 years ago, was achieved with a 6-3 7-5 6-3 6-2 6-6 (10-8) defeat of Vallejo. The Match in Detail The 22-year-old Vallejo is ranked 71st in the world – compared to Kouame's 318 listing – and recovered from a narrow second set defeat to storm level from two sets down, then moving to the verge of victory at 5-3 in the fifth, only for his teenage opponent to break back. The Impact of Kouame's Victory Kouame's victory, achieved in front of a partisan Parisian home support at Roland Garros, has sparked a new Parisian love affair with the young player. His showmanship and swagger suggest a star may just have been born. The Future Outlook With this impressive win, Kouame is set to make a significant impact in the tennis world. His ability to perform under pressure and his exceptional skills on the court make him a player to watch in the future.

Serena Williams, 44, is contemplating a return to the professional circuit at the upcoming Queen’s Club WTA 500 tournament, targeting a doubles wildcard alongside Canadian rising star Victoria Mboko. The plan, confirmed by The Served Podcast, comes after six months in the drug‑testing pool and could reignite global interest in women’s tennis.Williams Targets a Grass‑Court Return with a Doubles WildcardThe former world No. 1 will aim for a wildcard entry in the doubles draw of the second edition of the Queen’s Club event, scheduled to start on 8 June 2026, a day after the French Open concludes. Partnering with Mboko, ranked No. 9 in singles, would give Williams a low‑key re‑entry while still delivering marquee appeal.Key Numbers: Age, Rankings, and Tournament TimelineAge: 44 years oldGrand Slam titles: 23 singles titlesDrug‑testing pool: 6 months completedVictoria Mboko: 19 years old, world No. 9 in singlesEvent start date: 8 June 2026Potential Ripple Effects on Women’s Tennis and Global AudiencesPeers such as Naomi Osaka and Madison Keys have voiced excitement, noting that Williams’ presence historically drives TV ratings and ticket sales. A successful comeback could attract new sponsors, increase WTA 500 event visibility, and inspire younger players worldwide.What a Successful Return Could Mean for the WTA CalendarIf Williams competes and performs well, the WTA may consider more high‑profile wildcard entries for veteran stars, potentially reshaping tournament marketing strategies ahead of the grass‑court season. Conversely, a modest showing would still reinforce her status as a draw‑card, encouraging broadcasters to allocate premium slots for women's matches.

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.

The Tactical Chess Match of Champions League FinalIt would be easy to look at Saturday's Champions League final between Paris Saint-Germain and Arsenal and see it as a battle of attack versus defence, of beauty against pragmatism, of French elan against English doughtiness, as some sort of tussle for the soul of football. But it would not entirely be true. And where, after all, was the honour at Agincourt? In the vainglorious charges of the dashing French cavalry or the stoic defiance of the British archers arrayed, naked from the waist down, behind their defensive stakes?The final promises to be a fascinating tactical contest between two teams with contrasting approaches but complementary strengths. PSG's devastating wings, featuring players like Desiré Doué and Khvicha Kvaratskhelia, will test Arsenal's defensive resolve, while Arsenal's set-piece prowess could provide their route to goal.PSG's Dominant Possession vs Arsenal's Defensive ResilienceThe statistical comparison between the two teams reveals contrasting strengths. In the Champions League this season, Paris Saint-Germain have averaged 63.4% possession, higher than anybody apart from Barcelona; Arsenal's figure is 52.6%, the 11th-highest of the 36 sides who made the league stage. PSG's pass completion has been 89.3% to Arsenal's 85.7% (third-highest to 14th-highest). PSG have scored 44 goals to Arsenal's 29. But on the flip side, Arsenal have conceded six goals to PSG's 22 and won 13.4 aerial duels per game to PSG's 9.4 (sixth-highest to 29th-highest).These figures suggest that PSG will dominate possession, while Arsenal will likely sit deep and look to counter-attack. However, that was not how either leg of the semi-final between the teams last season played out: PSG shaded possession at the Emirates and Arsenal at the Parc des Princes as they chased the game.The Full-Back Dilemma for ArsenalThe biggest danger to Arsenal is probably a counterattack. Most opponents sit deep against PSG, especially in Ligue 1, but the evidence of PSG's wins over Chelsea, Liverpool and Bayern Munich is that they are lethal in transition. Arsenal cannot let Desiré Doué or Khvicha Kvaratskhelia get a run on whoever they have at full-back. Both are rapid, supreme dribblers and terrifyingly direct.Full-back is an issue for Arsenal, especially on the right. Ben White is out with a knee injury and Jurriën Timber is doubtful with a groin problem sustained against Everton in mid-March. Martín Zubimendi started at right-back against Crystal Palace but it would seem more likely that Cristhian Mosquera operates there if Timber has not recovered, if only because he is a more natural defender.Riccardo Calafiori has seemed Mikel Arteta's preferred option on the left. His role will be twofold: to stop Doué and to invert into midfield, particularly out of possession, to try to prevent the counter. It may be that Myles Lewis-Skelly is used ahead of Zubimendi alongside Rice, in part because he is familiar with playing at left-back and so could help double up on Doué, or would be comfortable covering for Calafiori were he caught upfield.Midfield Strategies to Counter PSG's WingsAlthough PSG have scored more goals from non-penalty set plays than Arsenal in the Champions League this season (eight to five), it probably is reasonable to assume that corners and free-kicks offer Arsenal's best chance of a goal. But to counter PSG's midfield dominance, Arsenal may need to embrace a more aggressive approach.The first leg of PSG's semi-final against Bayern was remarkably open, almost basketball-like in its end-to-end attacking. But that should not necessarily be regarded as characteristic. PSG can at times seem a little sloppy, too reliant on their attacking prowess, but their performance away to Bayern, when Fabián Ruiz returned, showed how effective PSG's midfield can be. And that means either that Arsenal have to sit deep and accept PSG will dominate the ball or that they need to ensure their midfield has a destructive edge.Lessons from Previous EncountersChelsea's success against PSG in the Club World Cup final perhaps offers, if not a template, then at least inspiration for how Arsenal can hurt the defending European Champions. Enzo Maresca's approach was asymmetric, using Cole Palmer almost as an inside-right, haunting the channel between Nuno Mendes and the left-sided centre-back while getting in behind the left-back wherever possible.On the left, Marc Cucurella regularly tucked into midfield, just as Calafiori surely will, with Pedro Neto tracking back almost as a wing-back to check Achraf Hakimi's thrusts in support of Doué. If Arteta sees things similarly, that is probably more of a job for Leandro Trossard than Eberechi Eze, who may end up on the bench if Arteta, as he surely must, prefers 4-3-3 to 4-2-3-1.Keys to Victory in Saturday's FinalThere is an irony in this. The stereotype of Arsenal this season has been of a defensive side reliant on set plays, but that is not entirely accurate; rather they are a side whose defensive qualities have been highlighted because of deficiencies of creativity and attacking quality. But to beat PSG, it may be that they have to embrace the narrative and be the side critics say they are.Arsenal's right-back situation remains critical. White links better with Bukayo Saka than any of Arsenal's other full-backs, and Timber is as tactically astute as any player in the squad. Unless Timber is fit, the right-back issue is likely to diminish them from a defensive and an attacking point of view.The final will come down to which team can impose their tactical approach most effectively. Can Arsenal's defense contain PSG's devastating wings, or will PSG's midfield dominance prove too much for Arsenal to handle? The answer will determine who lifts the Champions League trophy on Saturday.

The Unlikely Fashion Statement Mamdani made a surprising appearance during Eid al-Adha celebrations, donning an Arsenal thobe. The Significance of the Thobe The thobe, a traditional garment, was uniquely designed with Arsenal's colors or logo, blending cultural heritage with sports enthusiasm. Fan Reactions and Cultural Impact Social media was abuzz with reactions from fans and followers, discussing the intersection of sports and cultural attire. The Broader Context of Sports and Fashion This incident highlights the growing trend of sports brands and teams influencing fashion, even in traditional settings. Looking Ahead It will be interesting to see if more sports personalities or brands follow suit, merging sports and cultural fashion.