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The Meteorite Impact: A Cataclysmic Event What would it have been like to have lived through the meteorite impact that wiped out the dinosaurs 66m years ago? Writing in the Conversation, Michael Benton, of the University of Bristol, and Monica Grady, of the Open University, describe in vivid detail how it might have felt. The Initial Blast and Its Immediate Effects The first sign that something was amiss would have been a new star visible for about a week before the event. Upon its arrival, all living creatures near the impact site would have seen the bright fireball, heard its crackling noise and experienced a sonic boom before being swiftly incinerated. The Global Devastation Five minutes later, 100-metre-high mega tsunamis rolled across the Gulf of Mexico and, combined with the overheating, earthquakes, hurricanes and fires, wiped out everything within a 1,200-mile (2,000km) radius. The Long-Term Consequences Dinosaurs roaming forests on the other side of the world were still oblivious, but not for long. Within an hour, dust had circled the planet and skies had darkened. Within a day, global temperatures were dropping, and by the end of the week the world was 5C cooler. A ferocious winter lasted for more than a decade, eliminating about 75% of all species. A Warning for the Future Our ancestors were some of the lucky survivors but, sadly, Benton and Grady suggest our penchant for burning carbon is setting the scene for a similar scale of planetary catastrophe.

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.

Federal prosecutors in Brazil hailed a court ruling on Friday that obliges multiple government bodies to protect the abandoned 1928 Fordlandia site in the Amazon, calling it a “landmark” for cultural preservation.Landmark Court Decision Mandates Fordlandia PreservationJudicial order requires the federal government, the state of Pará, the municipality of Aveiro, and the National Institute of Historical and Artistic Heritage (IPHAN) to collaborate on site protection.The ruling follows decades of advocacy by historians, activists and local residents.Historical Context and Financial Footprint of FordlandiaFordlandia was founded in 1928 when Henry Ford invested nearly $20 million to build a self‑contained rubber town in the Amazon. The venture failed due to disease‑riddled plantations, strict worker regimes and competition in the automotive market. By 1945 the complex was sold to the Brazilian government for a modest $244,200. Today, the infrastructure is in advanced decay, with the hospital having burned down in 2012.Socio‑Economic and Environmental ImplicationsPoverty in Pará remains high – 39.3 % in 2023.Residents report unreliable water and loss of basic services.Preservation could anchor a sustainable tourism industry, offering economic alternatives to local communities.Protecting the site also contributes to broader Amazon conservation goals by preventing further illegal looting and degradation.What Lies Ahead for the Amazon Heritage SiteProsecutors argue the decision gives locals a legal right to demand restoration. Expected next steps include:Joint planning by federal, state and municipal authorities with IPHAN to assess structural stability.Funding proposals for tourism‑focused redevelopment.Monitoring mechanisms to ensure compliance with preservation standards.If implemented, Fordlandia could become a living museum of early 20th‑century industrial ambition and a catalyst for regional economic revitalization.

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.

The Vision for AI Coding Agents Cognition CEO Scott Wu made headlines again this week when his two-year-old AI coding agent startup raised $1 billion at a $26 billion valuation. Cognition is the maker of Devin, one of the first and, arguably, most successful AI coding agents. Devin, the CEO says, “naturally owns tasks end to end.” The Future of Software Development In fact, in the blog post announcing that raise, Cognition laid out a vision where “we are shifting to a world of self-driving software development.” So, could Devin replace, say, a mid-level L4 programmer? Yes, and no, Wu told TechCrunch. “We’ve never thought about it as replacing humans. I know it’s like a scenario, folks have said these things. It has never been our view.” Preserving the Joy of Programming Wu emphasizes that the goal is not to make human programmers obsolete. “We are all programmers ourselves,” he explained. “I started coding when I was nine.” He views agents as another layer of abstraction between envisioning a software product and producing it, similar to how visual development environments abstracted software creation away from machine instructions. The Role of Devin in Cognition Cognition says that Devin’s role in its own company is to ship nearly all the software. The company says that 89% of code committed by its engineers was committed by Devin, and the rest by local agents. Wu explains that his agent’s role is largely to do the kinds of long-tail maintenance tasks that many programmers don’t like to do anyway: bringing old software up to date; moving applications off one platform and onto another. The Future of AI Agents Wu predicts that agents will enter other fields where they will learn tasks, from customer service to medicine, but hopes the goal will be to augment human workers in those areas, too. “Code and software has been the first to move, but we’ll see this happen in all these other industries,” he predicts. “One thing that’s been clear to us since the beginning is, it should always be up to the human what to do … you really see this in software engineering, but I think it’s true in all these other professions too.”

The Final Call for Speakers at Disrupt 2026Applications to speak at TechCrunch Disrupt 2026 close tonight at 11:59 p.m. PT, giving founders, investors, operators, and technology experts only a few hours left to secure a spot on one of the year’s most influential tech stages.Event Overview: Dates, Venue, and Audience ScaleThe conference runs October 13–15 at Moscone West in San Francisco. More than 10,000 startup and VC leaders are expected to attend, creating a dense network of decision‑makers across AI, fintech, infrastructure, robotics, and broader innovation.Speaker Formats and Capacity MetricsBreakout Sessions: 30‑minute talks (up to 4 speakers) plus 20‑minute Q&A;, limited to 100 attendees.Roundtables: 30‑minute moderated discussions for up to 40 participants, slide‑free and focused on insight.Strategic Value for Founders, Investors, and Tech InfluencersSecuring a speaking slot offers direct exposure to a curated audience, the chance to shape the narrative around emerging technologies, and eligibility for the Audience Choice vote, which can amplify a session’s reach across TechCrunch’s readership.What to Expect from the 2026 Speaker Line‑upSelected speakers will likely spotlight actionable insights in AI, scaling strategies, and next‑gen infrastructure, setting the agenda for the industry’s post‑2026 trajectory. Applicants should emphasize real‑world experience to increase their odds of advancing to the final voting stage.