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The Guardian’s review of Pressure argues that the film’s competent cast cannot overcome a thin script and a repetitive structure, leaving it destined for a modest box‑office showing and a quick move to streaming.What “Pressure” Attempts to Capture: A WWII Meteorology ThrillerPressure centers on the final days before the Allied invasion of Normandy in June 1944, dramatizing the clash between chief meteorologist James Stagg (played by Andrew Scott) and American forecaster Irving Krick (Chris Messina). The narrative frames the historic operation as a high‑stakes weather‑forecasting battle, with Brendan Fraser portraying General Dwight Eisenhower, anxiously checking a weather app for the decisive storm.Release Schedule and Market PositioningThe film’s rollout is staggered across key territories, reflecting a modest commercial strategy:29 May 2026 – United States cinemas9 September 2026 – United Kingdom cinemas29 October 2026 – Australian cinemasThese dates suggest a focus on theatrical windows before the film likely migrates to streaming platforms, a path common for mid‑budget historical dramas.Why the Film Falters with Audiences and CriticsAccording to the review, the film’s shortcomings stem from:Repetitive character dynamics that recycle the same confrontations between Eisenhower, Stagg, and Krick.A visual palette dominated by “cool blues” and military‑jacket greens that feels formulaic.Insufficient exploration of the meteorological science that drives the plot, leaving the “nerdy” aspect under‑developed.Attempts to broaden scope with invasion montages that clash with the intended “pressure‑cooker” intimacy.While performances from Scott and Fraser are praised—Scott’s “gentle seething” and Fraser’s “fun” portrayal—their work is constrained by the script’s limited depth.Outlook: Streaming Prospects and LegacyThe review predicts that Pressure will likely enjoy a brief theatrical presence before becoming “arm‑chair nap material” on streaming services. Its niche appeal to “weather dads” and “history dads” may generate modest viewership, but the film is unlikely to achieve lasting cultural impact or become a reference point for WWII cinema.

The Lead Meena Kandasamy's novel "Fieldwork As a Sex Object" tackles the terrifying reality of deepfake technology and its use in online harassment, particularly targeting women in India's complex digital landscape. Through protagonist Amy Chaturvedi, the novel explores how fabricated content can destroy lives and how internet trolls exploit such content for misogynistic and political purposes. The Digital Hell of Indian Internet Culture The novel portrays India's internet as a particularly toxic environment, far exceeding the toxicity of Western platforms like X and Facebook. Kandasamy captures a world where caste, religion, and political extremism intersect with misogyny to create a dangerous space for women. The author describes how algorithms, far-right government influence, and societal tensions combine to create a digital hellscape where women are systematically targeted and harassed. The Deepfake Crisis and Its Victims The central plot revolves around Amy Chaturvedi, a privileged student activist living in London, who becomes the victim of a deepfake sex tape. Despite her sexual liberation and experimentation, Amy must confront a world that immediately judges and shames her based on the fabricated content. The novel explores how such digital violations can be used as weapons, not just for humiliation but also for political and social control. The Anatomy of Online Trolls Kandasamy provides a sharp, humorous, yet critical examination of the Indian internet troll, exposing their motivations, insecurities, and political alliances. The author portrays trolls as a "disparate bunch of Nazi-loving, Islamophobic vegetarian dicks" who use anonymity to spread hate, promote extremist ideologies, and attack those who challenge their worldview. The novel reveals how these trolls operate in coordinated campaigns to silence dissenting voices, particularly women and minorities. Literary Merits and Political Commentary As one of India's most outspoken writers, Kandasamy blends personal narrative with political commentary, creating a work that is both entertaining and thought-provoking. While the reviewer notes some stylistic choices that could be refined—particularly the Marxist theoretical framework and excessive internet jargon—the novel's power lies in its unflinching portrayal of online misogyny and its intersection with political extremism. The author's willingness to "not pull any punches" makes her a vital voice in contemporary Indian literature. The Future of Digital Rights and Literature "Fieldwork As a Sex Object" arrives at a critical moment when deepfake technology is becoming increasingly sophisticated and accessible. The novel serves as both a warning and a call to action, highlighting the urgent need for better legal protections and digital literacy. As internet culture continues to evolve, works like Kandasamy's will play an essential role in shaping public discourse about technology, power, and gender in the digital age.

The LeadSimon Rogers, Google's data editor, presents a fascinating exploration of human curiosity through the lens of search queries in his book 'What We Ask Google.' The compilation of anonymized search data from 2004 to the present offers a unique mirror into our collective concerns, from parenting questions to existential queries, though the review suggests the book presents a somewhat rose-tinted view of technology's role in our lives.The Book OverviewRogers, a former Guardian journalist who joined Google in 2015, organizes the search data into themed chapters that blend statistics with personal anecdotes. The book traces search trends back to 2004, when internet access was limited to less than half of UK households. Rogers posits that our search queries reveal something 'real and deep and meaningful about who we are as humans,' arguing that even brief searches indicate genuine care and concern.The Data InsightsThe book reveals intriguing patterns in human search behavior. Parenting-related queries like 'Why do babies get hiccups?' and 'How to tell kids about divorce?' appear frequently. Notably, in early 2023, searches for 'take care of parents' surpassed 'take care of kids,' reflecting the demographic pressures on the sandwich generation. The data also highlights geographical peculiarities, such as Austrians, Nigerians, and Canadians most frequently asking about back pain at night, and Americans in Kansas struggling to spell 'chaos' while their Missouri neighbors are stumped by 'unconscious.'The Critical PerspectiveThe review identifies significant limitations in Rogers' approach. As a 'company man' who joined Google from Twitter, the book presents an overly optimistic view of the internet and Google's role in society. There's minimal acknowledgment of the AI revolution's impact on search behavior and its consequences for content creators. The book also avoids addressing darker aspects of human nature reflected in search histories, political influences like Donald Trump, and how big tech may actually amplify parenting anxieties rather than alleviate them.The Cultural ImpactDespite its limitations, the book offers a diverting window into collective curiosity. It demonstrates how our search habits reflect societal concerns, from the practical ('How to fold a burrito') to the profound ('How often can you donate plasma?'). The reviewer notes that Rogers interprets this latter query as evidence of altruism rather than recognizing it as a symptom of US healthcare inequities. The book ultimately serves as an interesting, if selective, cultural artifact that captures our digital age's peculiarities and preoccupations, even if it doesn't fully confront the complexities of our relationship with technology.

The Rise of Techno-Colonialism In recent years, investigations have revealed that Israeli-linked AI systems, such as Lavender and Gospel, have been used to generate military targets in Gaza, marking a new era in warfare driven by algorithms, data, and surveillance technology. The Changing Nature of Conflict and Power Scholars and experts argue that these developments reflect a shift in how power is exercised in the modern world. No longer is it solely about military force, but also about technology, finance, and control over information. The Data Analysis: A Concerning Trend 44 countries face severe debt burdens, often aggravated by global conflicts. Global financial markets, algorithm-driven platforms, and foreign-controlled digital infrastructure increasingly define everyday life. The Impact Analysis: A New Form of Colonization Experts warn that dependence on Western technology, digital infrastructure, and global markets creates new forms of political and economic vulnerability, particularly across the Global South. This has revived debates around decolonization, with many arguing that colonial power structures never fully disappeared but evolved. The Prediction: A Future of Shared Responsibility As the world grapples with these changes, there is a call for a global order built not on hierarchy, but on shared responsibility. The burden should belong to humanity collectively, rather than being dictated by a handful of powerful tech companies and financial systems.

The Escalating Cost of Russia's War in UkraineEvidence of Russia's poor performance in its war in Ukraine, both militarily and economically, has been mounting over the past week. The US Defence Intelligence Agency (DIA) has confirmed earlier assessments that Russia has lost territory it previously occupied in Ukraine, while Ukraine has managed to reclaim approximately 400 square kilometers in and around Dnipropetrovsk – more territory than at any time since late 2022.Russia's Military Setbacks and Economic StrainRussia has still made a net territorial gain in 2026, but its advance is slowing down dramatically. According to the Institute for the Study of War (ISW), a Washington-based think tank, Russia advanced by a net 104 sq km between January 1 and May 26, 2026, compared to its seizure of 1,619 sq km during the same period last year.Ukrainian President Volodymyr Zelenskyy reported that Russian casualties had increased to 145,000 this year, of which 86,000 were killed and 59,000 troops seriously wounded. Ukraine's Defence Minister, Mykhailo Fedorov, highlighted that this meant 179 Russian losses per square kilometre of advance, compared to 67 last year – a rate higher than what Russia is currently able to replace through recruitment.Russia's war is also becoming increasingly difficult to finance. Having exceeded its entire 2026 budget deficit allowance by April, and depleted its foreign exchange reserves, Russia has been drawing down gold reserves at an unprecedented pace. According to its Central Bank, Russia has sold 27.9 tonnes of its gold reserves this year, worth more than $4bn, leaving reserves at their lowest since the beginning of the full-scale invasion in February 2022.Shifting Battlefield Dynamics and StrategiesThe DIA attributed Ukraine's territorial gains to Russia losing access to Starlink satellite services used for targeting and counter-battery fire. Ukraine attributes its success to its strategy of interdicting Russian logistics through mid-range drone and artillery strikes, which Fedorov described as a programme called "Logistical Lockdown" designed "to scale up middle-strike and systematically destroy Russian capabilities at the operational depth."This Ukrainian tactic has prevented reinforcements of men and equipment from reaching the frontlines, diminishing Russia's superiority in depth of resources and mass. The effectiveness of this strategy was demonstrated when Kherson occupation governor Vladimir Saldo restricted movement along the M-14 highway connecting Mariupol, Berdyansk and Melitopol, due to the number of vehicles being struck there.On the defensive front, Ukraine received a significant boost when Sweden announced it would donate 16 Gripen warplanes to Ukraine, which would also purchase an additional 20 through the EU's Ukraine Support Loan in a deal worth $2.9bn. Zelenskyy noted that "Gripen fighters with appropriate weapons, in particular Meteor missiles, which destroy targets at a distance of more than 200 kilometres, will help us push back Russian aircraft" against the approximately 3,000 Russian glide bombs dropped weekly.Simultaneously, Ukraine continued its long-range strikes on the Russian oil economy, which funds the war. On May 23-24, Ukraine struck oil depots and terminals at Novorossiysk and Tamanneftegaz on the Black Sea, as well as military and industrial sites including the Metafrax Chemicals plant in Perm and the Taganrog Airbase in Rostov.Russia's Response and Escalation TacticsIn response to Ukrainian advances, Russia pursued its own aerial tactic of striking Kyiv through massive combined attacks of drones and missiles. On May 24, Russia launched 600 long-range drones and 90 missiles against Kyiv and surrounding areas, including 36 ballistic missiles. Ukraine managed to shoot down 91 percent of the drones and 81 percent of the cruise missiles, though those that hit damaged government buildings, museums, and a market, injuring at least 87 people and killing two.Russia framed these attacks as retaliation for what it described as a terror attack on a college in occupied Luhansk, which it claimed killed six students and injured 39. Ukraine's General Staff countered that it was a strike on a centre for Advanced Unmanned Technologies run by Rubikon, Russia's unmanned systems force.Russian Foreign Minister Sergei Lavrov informed his US counterpart, Marco Rubio, that Russia would begin striking "military sites" in Kyiv in retaliation, warning foreign citizens, including diplomats, to leave. Moscow specifically mentioned using its newest Oreshnik intermediate range missile in the attacks, which it has also forward-positioned in Belarus.Future Outlook of the ConflictThe current trajectory suggests that Ukraine's strategy of targeted strikes on Russian logistics and supply lines, combined with enhanced air defense capabilities from international partners, will continue to challenge Russia's military advances. However, Russia's demonstrated willingness to escalate attacks on urban centers and its deployment of advanced weaponry indicate that the conflict may enter a more intense phase.As Russia depletes its financial resources and struggles to replace casualties, its ability to sustain current operations may diminish. Conversely, Ukraine's increasing success in securing international military support and refining its asymmetric tactics could shift the balance further in its favor, though the long-term outcome remains uncertain as both sides adapt their strategies.

Why a Living AI Glossary Matters NowArtificial intelligence is reshaping every industry, but its rapid evolution has spawned a parallel explosion of terminology that can leave even seasoned technologists feeling insecure. TechCrunch’s new glossary aims to provide a single, regularly‑updated reference that translates the most common AI buzzwords into plain language.Key Definitions from AGI to RLHFThe article walks readers through a spectrum of concepts, including:Artificial General Intelligence (AGI) – AI that outperforms humans on most economically valuable tasks, as defined by OpenAI and Google DeepMind.AI Agent – An autonomous tool that can perform multi‑step tasks such as expense filing, ticket booking, or code maintenance.API Endpoints – “Buttons” that let software components interact, enabling agents to automate third‑party services.Chain‑of‑Thought Reasoning – A technique that breaks problems into intermediate steps to improve accuracy.Compute – The hardware (GPUs, CPUs, TPUs) that powers AI model training and inference.Deep Learning – Multi‑layered neural networks that learn features directly from data.Diffusion – The process behind many generative AI models that learns to reverse noise‑added data.Distillation – A teacher‑student method for creating smaller, faster models like GPT‑4 Turbo.Fine‑Tuning – Adding task‑specific data to a pre‑trained model to improve performance.GAN – Generative Adversarial Networks that pit a generator against a discriminator to produce realistic outputs.Hallucination – When models generate inaccurate or fabricated information.Inference – Running a trained model to make predictions, often accelerated by specialized hardware.LLM – Large Language Models that power assistants such as ChatGPT, Claude, Gemini, and Llama.Memory Cache (KV Caching) – An optimization that stores intermediate calculations to speed up inference.Open Source vs. Closed Source – The debate over publicly available model code (e.g., Meta’s Llama) versus proprietary systems (e.g., OpenAI’s GPT).Parallelization – Executing many calculations simultaneously, a cornerstone of modern AI hardware.RAMageddon – The current shortage of memory chips driven by AI data‑center demand.Recursive Self‑Improvement (RSI) – Models that can redesign themselves, a potential step toward singularity.Reinforcement Learning from Human Feedback (RLHF) – Training models with reward signals to improve helpfulness and safety.Tokens & Throughput – The basic units of text processing that determine cost and performance.Quantifying the AI Vocabulary ExplosionThe glossary covers more than 30 distinct terms, each accompanied by concise explanations and links to deeper resources. By cataloguing this breadth, the piece highlights how quickly the AI lexicon has expanded within just a few years of mainstream adoption.Implications for Developers, Investors, and the PublicUnderstanding this terminology is no longer optional. For developers, clear definitions accelerate product building and reduce miscommunication when integrating APIs or deploying agents. Investors gain a sharper lens for evaluating startup pitches that hinge on concepts like fine‑tuning or distillation. Meanwhile, the broader public can better assess claims about “AGI” or “hallucinations,” mitigating hype‑driven misinformation.Future of AI Terminology and Industry AdoptionTechCrunch positions the glossary as a “living document,” promising regular updates as new techniques (e.g., emerging diffusion variants or next‑gen RLHF methods) appear. As AI systems become more autonomous and specialized, the vocabulary will continue to evolve, making ongoing education essential for anyone interacting with the technology.

The Rise of AI Psychosis in Corporate Decision MakingBox founder Aaron Levie has identified a troubling trend in corporate America: what he calls "AI psychosis," where executives and decision-makers become so enamored with artificial intelligence that they believe it can replace human jobs without understanding what those roles truly entail. This overenthusiasm for AI is leading to significant workforce reductions and a growing backlash from both employees and users.Workforce Reductions Fueled by AI AmbitionThe consequences of this AI psychosis are already becoming apparent in the tech industry. Productivity software company ClickUp recently cut 22% of its workforce, citing a shift toward AI agents. This move is part of a larger trend where tech layoffs in 2026 are already nearly matching the total number of layoffs seen throughout all of 2025. These cuts suggest that companies are prioritizing AI implementation over human talent, often without fully understanding the implications.User Backlash Against Forced AI IntegrationWhile companies push AI solutions, users are increasingly resisting. DuckDuckGo has seen a surge in installations from users who want Google to stop forcing AI into search results and simply provide traditional links. This user backlash highlights a disconnect between corporate AI strategies and actual consumer preferences, suggesting that not all AI implementations are welcome or beneficial.The Duality of AI AdoptionAs TechCrunch's Equity podcast hosts discuss, both the AI-pilled (those enthusiastically embracing AI) and the AI-skeptical (those questioning its implementation) may have valid points. The challenge lies in finding a balance where AI augments human capabilities rather than replacing them entirely, and where technology serves actual needs rather than being implemented for its own sake.Future of Work in an AI-Driven EconomyAs AI continues to evolve, companies must develop more nuanced approaches to workforce planning and technology implementation. The current trend of replacing human workers with AI agents may prove shortsighted if it leads to decreased product quality, poor user experience, and loss of institutional knowledge. The future likely lies in hybrid models where AI and humans collaborate, each bringing their unique strengths to the workplace.

Groq's New Funding Round Groq is looking to raise $650 million in new funding from existing investors, sources tell Axios, as it leans into its inference neocloud business that relies on its homegrown AI chip and systems. The Nvidia Deal and Its Impact In December, Groq struck one of those not-an-acquisition agreements with Nvidia for a reported $20 billion, which involved the departure of some top-level senior Groq employees to the chip giant and the licensing of Groq’s hardware technology to Nvidia. The Focus on Inference Cloud Business The new direction is led right now by Groq’s interim CEO and CFO, Adam Winter and Matt Eng, respectively. The company's inference cloud business lets developers and enterprises host their inference-hungry apps. Inference is the processing that happens after an AI prompt and is currently a much bigger need in the AI world than model training. The Funding Commitment Groq's backers Disruptive and Infinitium have agreed to fill the round should other existing investors not want their pro-rata shares. The $650 million in funding is essentially guaranteed.

Groq's Ambitious Funding Round Groq, an AI chip startup, is looking to raise $650 million in new funding from existing investors, sources tell Axios, as it leans into its inference neocloud business that relies on its homegrown AI chip and systems. The Nvidia Deal and Its Implications In December, Groq struck a not-an-acquisition agreement with Nvidia for a reported $20 billion, which involved the departure of some top-level senior Groq employees to the chip giant and the licensing of Groq's hardware technology to Nvidia. The Focus on Inference Cloud Business The new direction is led by Groq's interim CEO and CFO, Adam Winter and Matt Eng, respectively. The company's inference cloud business lets developers and enterprises host their inference-hungry apps. Inference is the processing that happens after an AI prompt and is currently a much bigger need in the AI world than model training. The Funding Dynamics Groq's backers Disruptive and Infinitium have agreed to fill the round should other existing investors not want their pro-rata shares. The $650 million in funding is essentially guaranteed. The funding round highlights the ongoing investments in AI chip startups and the growing demand for inference capabilities in the AI ecosystem.