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Why Fans Are the Smart Summer Cooling ChoiceThe Guardian’s award‑winning tech journalist measured 16 fans and several evaporative coolers to see how they perform against a typical portable air‑conditioner that draws 1,000W (about 26p per hour). Fans in the test consumed between 8W and 60W, delivering a far lower electricity bill and carbon footprint while still moving enough air to make a noticeable temperature drop.Power Consumption Numbers Show Fans Beat Air‑ConditionersAirCraft Lume – 18W on top setting; could run 56 hours for the cost of one hour of air‑con.Dreo TurboCool misting fan 765S – 22W, best overall cooling performance.Devola desk fan – 12W, cheapest at £64.99.Shark FlexBreeze Pro Mist – 30W, premium misting option at £249.99.Swan Nordic evaporative cooler – 15W, lowest‑energy water‑based cooler at £69.Cooling Comfort Meets Carbon Savings for UK HouseholdsRunning a fan instead of an air‑conditioner can cut summer electricity use by up to 95 %, translating into lower bills and reduced greenhouse‑gas emissions. For a typical UK home, swapping a 1,000W air‑con for an 18W fan saves roughly £23 per month and avoids about 0.12 tCO₂ of emissions.What’s Next for Home Cooling in a Warming Climate?As heatwaves become more frequent, manufacturers are likely to focus on quieter, smarter fans with integrated sensors that adjust speed automatically. Expect more hybrid designs that combine low‑energy misting with airflow optimisation, giving consumers a wider menu of carbon‑friendly cooling solutions.

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 AI-Driven Economic Surge Taiwan's economy is booming, with a growth rate that would be the envy of any country. The AI boom sweeping Taiwan has made it an exciting time to work in tech, particularly in the semiconductor industry, which produces about 90 percent of the most advanced chips used to power leading AI models. The Semiconductor Industry's Dominance Taiwan is a semiconductor powerhouse, with Taiwan Semiconductor Manufacturing Company (TSMC) accounting for more than 40 percent of the value of the island's stock market. Semiconductors alone account for more than 20 percent of Taiwan's GDP. The Uneven Distribution of Benefits Despite the impressive economic growth, concerns are rising about the uneven distribution of benefits. Many industries unrelated to tech do not seem to be feeling the benefits, with some individuals experiencing stagnant pay and rising living costs. The semiconductor industry employs only about 300,000 people in a workforce of 11 million. The Risk of a 'Dual Society' Economists warn that Taiwan's economic model has left it at risk of becoming a 'dual society' where tech sweeps up talent, funding, and resources at the expense of other industries. The wealth divide has grown over the decades, with Taiwan's Gini coefficient increasing from 0.308 in 1980 to 0.341 in 2024. The Future Outlook As Taiwan's economy continues to grow, the government faces challenges in addressing the uneven distribution of benefits and ensuring that the growth is inclusive and sustainable. The country's reliance on a single industry for growth marks a shift from the Asian Tiger era, when Taiwan's economy was driven by hundreds of thousands of small and medium-sized enterprises.

France Abandons the Controversial ‘Black Code’On 2026-05-29 the French government announced the termination of the ‘Black Code’, a framework that had drawn criticism for its impact on digital freedoms and platform operations.Implications for Digital Regulation in FranceThe repeal signals a shift in the nation’s approach to online content moderation, data handling, and platform accountability.Possible Policy Paths ForwardDeveloping a more transparent regulatory model.Engaging with industry stakeholders to craft balanced rules.Aligning French law with broader EU digital strategies.What to Watch in the Coming MonthsAnalysts expect debates in parliament, consultations with tech firms, and potential new legislation to emerge as France redefines its digital governance.

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.