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Digital Stories

Digital Stories

Di: Giulio Ranucci
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Episodi
  • S5 Ep. 8 - Our addition to social media lead me to write a Book

    S5 Ep. 8 - Our addition to social media lead me to write a Book
    Jul 25 2026
    Fifteen years after the smartphone revolution, we are finally asking the right question about social media platforms and their impact on human behavior.The debate about whether social media is addictive has effectively ended, Mark Zuckerberg testified in a California federal court in February 2026, facing allegations that Meta deliberately designed features to addict children to its platforms. The trial brings together lawsuits from dozens of school districts and families, centering on whether Meta knowingly exploited psychological vulnerabilities of young users to maximize engagement and profit.Meta CEO and Chairman Mark Zuckerber arrives at LA superior Court (February 18, 2026)Austria has banned social media for children under 14, while the UK is considering similar restrictions and Australia has already implemented them. The European Commission announced in January 2025 that it is opening formal proceedings against TikTok under the Digital Services Act, investigating whether the platform breached obligations to protect minors from addictive design.The question now is what we do with the knowledge that our attention was systematically engineered away from us through deliberate design choices. When we strip away the moral panic and regulatory theater, what remains is a case study in how incentive structures shape product design, how business models determine behavior, and how fifteen years of data reveal patterns we should have recognized sooner.This is not about whether individual users personally feel addicted to Instagram or any other platform, but It's about understanding the deliberate systems built to compete for human attention, and what that competition costs us collectively in terms of mental health, productivity, and wellbeing.The teams you don't seeMeta employs psychologists, as do TikTok, Instagram, and YouTube, though not for the purpose of helping users manage their mental health. These professionals are employed to optimize engagement by identifying exactly which stimuli trigger dopamine release, which interaction patterns create habit loops, and which notification strategies maximize time spent on the platform.Court filings in the current litigation detail how features like infinite scroll, autoplay video and algorithmic content recommendation were specifically designed to exploit psychological vulnerabilities rather than serve user needs.CR Biological InfographicThe discussions center not on how to help people connect meaningfully, but on how to increase daily active users. The focus is not on what value is being created for users, but on what the engagement rate metrics show. The metrics that matter are those that serve the business model, which means advertising revenue, which requires sustained attention, which requires time spent on the platform, which requires features that make leaving the platform psychologically difficult.These companies are not consumer technology businesses in the traditional sense. They are attention arbitrage operations that acquire your attention cheaply through free services and sell it expensively to advertisers. The product is not the application itself but rather you as a user, specifically your eyeballs and the time you spend viewing advertisements between content.Every feature decision flows directly from this business model. Autoplay exists because it reduces the friction between watching one video and starting the next one, thereby increasing total viewing time. Infinite scroll exists because stopping points create opportunities for users to leave the platform. Algorithmic feeds exist because chronological feeds have natural endpoints when you have seen everything new from the people you follow. Pull-to-refresh mimics slot machine mechanics because variable reward schedules create stronger habit formation than predictable ones.This is not accidental design or the unintended consequence of building useful products. It represents deliberate optimization by teams of PhDs in behavioral psychology, neuroscience, and addiction research who are specifically employed to maximize engagement regardless of the impact on user wellbeing.DesignLab - Creativity that connectsThe playbook from gambling and tobaccoThe techniques being used are not novel inventions but rather adaptations of proven methods from other industries. Slot machines use variable ratio reinforcement schedules because psychologist B.F. Skinner proved in the 1950s that unpredictable rewards create stronger compulsive behavior than predictable ones. The pull-to-refresh mechanism on social media feeds implements exactly this psychological principle, where sometimes you receive interesting content and sometimes you do not, creating the compulsion to keep pulling.iStockTobacco companies employed behavioral scientists for decades to optimize nicotine delivery, package design, and marketing strategies to maximize addiction among their customer base. Internal documents from those litigation cases ...
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    15 min
  • S5 Ep. 7 - Why future of computing might not be on earth

    S5 Ep. 7 - Why future of computing might not be on earth
    May 16 2026
    Elon Musk just merged xAI into SpaceX with a plan that sounds absurd until you run the numbers: build data centers in orbit.Not small experiments but industrial-scale computing infrastructure floating 340 miles above Earth (same distance of NASAs telescope Hubble), powered by solar arrays, cooled by the vacuum of space, training AI models that would potentially bankrupt terrestrial facilities.The immediate reaction is skepticism. Rockets are expensive. Space is hard. Servers belong in buildings, not orbit.But strip away the science fiction framing and what remains is a serious economic calculation that every executive should understand: sometimes the cost of working around a constraint exceeds the cost of eliminating it entirely.Nature.com - The development of carbon-neutral data centers in spaceThe constraint no one can optimize AI training has hit a wall. Not a technical wall. A physics wall. Training GPT-4 required approximately 50 gigawatt-hours of electricity. The next generation requires exponentially more. Frontier models now consume energy equivalent to small countries (es. Belgium), running for weeks or months continuously.Data centers already eat 1-2% of global electricity. AI is accelerating that dramatically. And here's the killer: in a typical hyperscale facility, cooling accounts for 38-40% of total energy consumption. For every watt your servers burn doing computation, you spend nearly another watt just preventing thermal failure.This isn't inefficiency but physics. Dense computing generates massive heat. Remove it continuously or the hardware dies.The industry has optimized relentlessly. Better airflow. Liquid cooling. Chip-level thermal management. But optimization has limits, and those limits are approaching faster than most realize. You can only pack so much compute into a building before cooling becomes impossible regardless of technology.Meanwhile, AI's appetite keeps growing. Meta, Google, Microsoft, and others are each planning to spend over $60 billion annually on AI infrastructure. Much of that goes to power and cooling.This is the constraint that changes everything. Not because it's insurmountable today, but because it's exponentially worsening and the traditional solutions don't scale.Haysfluidcontrols.comMath that makes orbit interestingMoving data centers to space sounds expensive until you compare it to the alternative.A 100-megawatt terrestrial AI facility costs $1-1.5 billion to build. Over ten years it consumes roughly 8,760 gigawatt-hours of electricity. At $60 per megawatt-hour, that's $525 million just for power. You spend 38-40% of that, approximately $200 million, on cooling alone. Add construction, land, taxes, maintenance and you're approaching $2 billion total cost of ownership.Now consider orbital economics: Historically (up to year 2000s), this calculation was laughable. Launch costs of $10,000-20,000 per kilogram made space infrastructure prohibitively expensive for anything except satellites and scientific missions.SpaceX's Starship changes this fundamentally. Current projections target $100 per kilogram to low Earth orbit, potentially as low as $10 per kilogram at full operational scale. That's not incremental improvement. It's two to three orders of magnitude cheaper.A server rack weighs 1,000-2,000 kilograms. At $100 per kilogram, launching one costs $100,000-200,000. At $10 per kilogram, it's $10,000-20,000. For comparison, the servers themselves often cost more than their launch at these prices.But weight adds up. A meaningful orbital data center requires thousands of racks, solar arrays, thermal radiators, communication equipment, structural elements. Even at optimistic weights, you're launching hundreds of thousands of kilograms.Here's where the calculation gets interesting. At $10-100 per kilogram, putting 100,000 kilograms of infrastructure in orbit costs $1-10 million for launch. The equipment itself might cost $50-100 million. Total upfront: $51-110 million.Made with Claude ProOperational costs nearly disappear. Power is free once solar arrays are deployed. Cooling requires zero energy because thermal radiation to space is passive. No property taxes. No grid fees. No atmospheric corrosion. Maintenance becomes the primary ongoing expense.Compare that to terrestrial alternatives where you're spending $200 million on cooling energy alone over a decade, and the economics start shifting.Problem 1: Maintenance The most legitimate objection to orbital data centers isn't launch costs or power but maintenance.Terrestrial data centers have technicians on-site twenty-four hours a day. When a server fails, someone swaps it within hours. When a cooling system malfunctions, engineers fix it immediately. When software needs updating, IT teams access the hardware directly. This operational flexibility is taken for granted, but it's fundamental to how data centers work.In orbit, none of this exists. You cannot send a technician to replace a failed drive. You ...
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    14 min
  • S5 Ep. 6 - EU Inc: Scaling or fading in the AI era

    S5 Ep. 6 - EU Inc: Scaling or fading in the AI era
    Apr 13 2026
    Full Article HEREEurope has never lacked talent. It has never lacked research excellence, engineering depth, or ambitious founders. What it has consistently struggled to build is something else, a reliable path from innovation to scale.For more than twenty years, the European tech story has followed a recurring arc. companies are founded, validated, and often celebrated locally. But when growth accelerates, capital intensity increases, and global ambition becomes unavoidable, gravity pulls them elsewhere. Most often, to the United States.As of the mid-2020s:the United States hosts 600+ unicornsEurope hosts roughly 130–150, spread across multiple hubs (Source: StartupBlink, Atomico State of European Tech).Between 2018 and 2021, Europe experienced a strong acceleration in unicorn creation. But sustaining that momentum proved difficult.The main reason is capital depth. According to Atomico and Crunchbase data:Europe consistently captures ~15–18% of global VC fundingthe US captures 50%+, with a dominant share of late-stage roundsSince 2015, Europe has missed out on hundreds of billions of dollars in growth capital compared to the US particularly in rounds above $50M, where scale is determined (Atomico, Sifted).This is not a failure of founders or ideas. It is the consequence of how the system is designed.Scale means crossing the AtlanticThe list is familiar. Spotify chose a direct listing in New York. Elastic went public on the NYSE. Farfetch and Adyen built their global investor base outside Europe. More recently, conversations around Klarna or Bending Spoons point in the same direction: when scale and liquidity matter, US markets remain the default option.This preference has little to do with patriotism or branding. It has everything to do with market depth. American public markets, especially Nasdaq, offer liquidity, analyst coverage, and a class of institutional investors that understand growth, technology risk, and long-term compounding. European exchanges, still fragmented along national lines, rarely offer the same combination. The result is predictable. Capital shapes outcomes, and exits follow capital.The capital gap in numbersData makes the pattern hard to ignore. Over the past decade, the United States has consistently hosted more than half of the world’s unicorns. Europe, by comparison, has produced a fraction of that number, despite comparable population size and strong academic output.The difference becomes even clearer at later stages. While Europe captures a meaningful share of early-stage venture funding, it systematically underperforms in large growth rounds. Capital above $50 million the kind that determines whether a company becomes regional or global remains far more abundant in the US.Since 2015, European scale ups have collectively raised hundreds of billions less than their American counterparts. This gap does not reflect weaker ideas. It reflects a thinner, more fragmented capital market.And once US investors enter the cap table, strategic gravity shifts. Board composition changes. Exit expectations evolve. Public listings, when they happen, increasingly take place outside Europe. Europe is not short on exits. What it lacks are exits that reinforce scale.Most European tech outcomes still come through acquisitions, often by American companies. Large IPOs are rarer and less repeatable. In the US, by contrast, public markets function as a continuation of the venture ecosystem, allowing companies to raise capital, stay independent, and keep growing after going public.Without this feedback loop, Europe repeatedly trains companies for someone else’s market.Fragmentation as a structural taxThis is where the problem becomes concrete. Europe operates across dozens of legal systems, tax regimes, labor laws, and capital market rules. Each difference is manageable on its own. Together, they slow everything down.Founders face complexity when issuing stock options across borders. Investors face friction when deploying capital at scale. Companies face operational drag precisely at the moment when speed matters most. This fragmentation acts as a hidden tax on ambition.Citi Institute released a report, “Reimagining European Capital Markets: From Fragmentation to Harmonization”, which focuses on post-trade challenges and fragmentation in the context of capital markets in Europe, and the key benefits of a unified European capital market.In a world of geopolitical and macroeconomic volatility, Europe has an opportunity to position itself as an attractive alternative for investment, innovation, and influence. The moment for incremental change has passed. Shahmir Khaliq, Head of Services, CitiThe report outlines how a unified European capital market could add hundreds of billions in annual investment, boost regional GDP and retain European savings in their own region. The research sheds light on the critical need to address the deep-seated fragmentation within European capital markets with ...
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    13 min
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