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The Lead Barcelona has completed the signing of Anthony Gordon from Newcastle for £70m, a move that brings a direct and intense playing style to their attack. The 25-year-old England winger is known for his turbo-charged talent and ability to terrorize defenses. Gordon's Playing Style Gordon is a versatile right-footed forward who is arguably at his best on the left but capable of playing across the frontline. He is aggressive and direct, reveling in accelerating into space behind defenders and pressing relentlessly from the front with rare intensity. His playing style is not without risk, as he often forces defenders into taking gambles they would prefer to avoid. The Data Analysis In 26 league games for Newcastle, Gordon contributed six goals, three of them penalties, and only two assists. However, in the Champions League, he scored 10 times in 12 appearances and contributed two assists. His performance in the Champions League has drawn praise from top managers, including José Mourinho. The Impact Analysis Gordon's signing is part of Hansi Flick's plan to keep Madrid firmly in their place. His arrival brings unpredictability to Barcelona's attack, and his ability to interchange positions with other forwards could make their attacking trio more formidable. However, Gordon's inconsistency and sometimes selfish play may pose a risk for Flick. The Prediction If Gordon can refine aspects of his game and diplomatic skills at the Camp Nou, he could become a key player for Barcelona. Meanwhile, Newcastle seems poised for an even more dramatic reinvention, with their sporting director pursuing several new signings to strengthen their squad.

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. This is the shift many founders still misunderstand — and it is becoming one of the defining realities separating enterprise AI companies that scale from the ones that stall after early momentum. 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 unpack that shift 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 Now the reality founders need to face is that startup AI deals rarely die because the model underperformed. They die because the enterprise lost confidence in what the deployment would require. The AI startups gaining traction inside large organizations increasingly share one thing in common: They reduce uncertainty. 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. That is the kind of operational pressure that Tavakoli-Shiraji and other speakers on the AI Stage at Disrupt will explore.

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.

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.

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.

The Burberry CEO's New Bonus Scheme Burberry's CEO, Joshua Schulman, could earn up to £12.2m this year under a new bonus scheme introduced by the luxury British brand. Schulman, who was hired in July 2024 to help revive Burberry, was paid £4m in the year to March, up from £2.5m for his first nine months in the job. Details of the Bonus Scheme Schulman's basic pay will increase by 3% to £1.24m from July. He could earn a new long-term share bonus worth up to 300% of salary if he meets performance targets. The targets include increasing Burberry's annual revenues to £3.1bn by 2029. Financial Performance Burberry made pre-tax profits of £49m in the year to 28 March, compared with a loss of £66m in the previous 12 months. Sales were flat year on year at £2.4bn, once the effect of exchange rates was taken into account. Impact on Executive Pay The pay package of Kate Ferry, the finance director of Burberry, more than doubled to £2.5m, up from £904,000 the previous year. Ferry could earn £5.6m this year if she hits all targets and Burberry's share price increases by 50%. Future Outlook The new bonus scheme aims to incentivize Schulman to meet performance targets and retain him by improving his pay position relative to those who head the brand's luxury peers. The scheme is intended to be "reasonable" and subject to "the delivery of stretching performance targets".

Former Prime Minister Tony Blair has called for the UK to scrap its 2050 net‑zero goal and ramp up North Sea oil and gas drilling, prompting a swift backlash from climate experts who label the suggestion “bizarre” amid a historic heatwave and rising energy costs. Blair’s Call to Re‑Open North Sea Oil and Gas E3G programme director Ed Matthew warned that abandoning net zero during the “worst May heatwave on record” would be a “massive setback” for the UK, emphasizing that clean energy is cheaper and has near‑zero operating costs. Economic Stakes: £200 million Heatwave Losses and Fossil‑Fuel Costs Heat stress on livestock and crops is projected to cost the UK economy over £200 million this year. The International Energy Agency’s Fatih Birol notes that new oil fields would have “little impact” on domestic fuel prices. Renewable‑energy growth, especially record‑breaking solar generation, is already reducing household energy bills. Why Renewables Outperform Fossil Fuel Revival in the UK Analysts such as Jess Ralston (Energy and Climate Intelligence Unit) argue that expanding solar and other clean‑power technologies shields consumers from volatile fossil‑fuel markets and supports energy security as the North Sea declines. Comparisons to Spain’s renewable‑driven price stability reinforce the case for electrification as the “obvious route” to lower bills. What the Next Steps Mean for UK Energy Policy Government spokespersons confirm that no new exploration licences will be granted, focusing instead on managing existing fields for the remainder of their lifespan while accelerating the clean‑power mission championed by Energy Secretary Ed Miliband. If the current trajectory holds, the UK is likely to cement its position as a leader in renewable deployment, rendering calls to revive North Sea drilling increasingly marginal in policy debates.