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  • Google's AI Brain Drain, SpaceX's Huge Quarter, Airtable's 90% Collapse, US Data Fuels China AI

    قبل يوم واحد

    Google's AI Brain Drain, SpaceX's Huge Quarter, Airtable's 90% Collapse, US Data Fuels China AI

    (0:00) Bestie intros! Brad Gerstner fills in for Chamath (2:16) Major shakeups at Google: AI brain drain or better strategy? (20:39) SpaceX's big quarter: Terafab, AI Capex, $1T revenue projection? (45:44) All-In Summit Speaker Announcements! (48:01) Airtable sells for a 90% discount: SaaSpocalypse? (1:05:56) Chinese AI labs are buying US training data to catch up Apply for Summit 2026: https://allin.com/events Follow Brad: https://x.com/altcap Follow the besties: https://x.com/chamath https://x.com/Jason https://x.com/DavidSacks https://x.com/friedberg Follow on X: https://x.com/theallinpod Follow on Instagram: https://www.instagram.com/theallinpod Follow on TikTok: https://www.tiktok.com/@theallinpod Follow on LinkedIn: https://www.linkedin.com/company/allinpod Intro Music Credit: https://rb.gy/tppkzl https://x.com/yung_spielburg Intro Video Credit: https://x.com/TheZachEffect Referenced in the show: https://x.com/the_ai_investor/status/2084687703707361429 https://x.com/Tesla/status/2085365278276284803

  • The Walt Disney Company

    ٢٢ يونيو

    The Walt Disney Company

    The Walt Disney Company is the most successful enterprise ever created for monetizing human nostalgia. Today it’s the king of global entertainment, holding the intellectual property rights to the childhood memories of billions of people (including, likely, all of you) and is a reliable, predictable profitable business. But it didn’t start that way. During Walt’s era, Disney operated like an unhinged moonshot factory, blowing its finances on one seemingly crazy project after another, like the very first feature-length animated film or a theme park inspired by Walt's fascination with model trains (spoiler: Disneyland). Walt’s relentless ambition to bet the company over and over again not only created some of the most monumental artistic achievements of the 20th century (Snow White, Fantasia, Disney Imagineering), but also resulted in the accidental invention of the modern “flywheel” business model. In this episode, we tell the story of the ultimate marriage of art, commerce, and engineering — The Walt Disney Company: Walt's Era. Sponsors: Many thanks to our fantastic Spring '26 Season partners: J.P. MorganWeAreDevelopers eventVercelServiceNowStatsigLinks: Sign up for email updates, get our takeaways and research photos from each episode, and vote on future topics!The Acquired Disney Companion PDFOur Disney column in WSJThe original 1958 WSJ “Flywheel” article"Walt Disney: The Triumph of the American Imagination by Neal GablerThe Animated Man by Michael BarrierWalt Disney: An American Original by Bob ThomasBuilding a Company: Roy O. Disney and the Creation of an Entertainment Empires by Bob ThomasThe Disney Version by Richard SchickelPBS American Experience: Walt DisneyDisneyland HandcraftedWalt's 1966 EPCOT pitch videoWorldly Partners' Multi-Decade Disney StudyThe Walt Disney Family MuseumAll episode sourcesCarve Outs: Brooks Vanguard sneakersDefunctland YouTube ChannelAnimagraffs YouTube ChannelVolvo EX30The San Francisco SymphonyMore Acquired: Get email updates and vote on future episodes!Join the SlackCheck out the latest swag in the ACQ Merch Store!00:00 Start01:10 Intro06:03 Walt's Early Life & Artistic Calling (1901-1919)12:22 From Commercial Art to Laugh-o-grams (1919-1923)23:05 Hollywood, The Alice Comedies & Oswald's Loss (1923-1928)43:27 Mickey Mouse & The Synchronized Sound Breakthrough (1928)01:01:21 The IP Flywheel & Mickey Merch Explosion (1929-1933)01:09:57 Flywheel Terminology Unpacked01:18:53 Snow White: Walt's $1.5M Folly (1934-1937)01:52:01 The Burbank Studio, Debt & Strike (1938-1941)02:04:28 The Animators' Strike & Walt's Disillusionment (1941)02:15:43 WWII, The Vault & Creative Slump (1941-1950)02:24:27 Post-War Slump to Cinderella's Comeback (1945-1950)02:33:48 Walt's Obsession: Model Trains to Disneyland (1950-1952)02:38:44 Financing Disneyland: ABC, SRI & Davy Crockett (1953-1955)03:17:05 Disneyland's Grand Opening & The Evolving Flywheel (1955-1958)03:41:55 The Florida Project & Walt's Last Dream (1961-1966)03:54:26 Walt's Untimely Death & Roy's Legacy (1966-1971)03:57:57 Roy Finishes Walt Disney World (1966-1971)04:01:09 The Post-Walt Slump & Corporate Raiders (1970s-1984)04:09:44 Analysis: Why No Other Disney Flywheels?04:17:15 7 Powers04:20:45 Quintessence04:23:50 Carve-Outs + Outro ‍Note: Acquired hosts and guests may hold assets discussed in this episode. This podcast is not investment advice, and is intended for informational and entertainment purposes only. You should do your own research and make your own independent decisions when considering any financial transactions.

  • How Magic Johnson Built a Billion-Dollar Portfolio in 30 Years

    ١١ فبراير

    How Magic Johnson Built a Billion-Dollar Portfolio in 30 Years

    a16z’s Chris Lyons speaks with Earvin "Magic" Johnson about his 30-year journey from athlete to billionaire businessman. They cover the art of deal-making, lessons from mentors Michael Ovitz and Dr. Jerry Buss, why boring businesses often make the best investments, and Magic's sports ownership portfolio, from the Dodgers to the Commanders to the Sparks. They also discuss what the next generation of athletes and entertainers should know about equity, building teams, and taking risks.   Resources: Follow Magic Johnson on X:  https://twitter.com/MagicJohnson Follow Chris Lyons on X: https://twitter.com/chrislyons   Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Podcast on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Podcast on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures. Stay Updated: Find a16z on YouTube: YouTube Find a16z on X Find a16z on LinkedIn Listen to the a16z Show on Spotify Listen to the a16z Show on Apple Podcasts Follow our host: https://twitter.com/eriktorenberg   Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

  • Vladimir Vapnik: Predicates, Invariants, and the Essence of Intelligence

    ١٤‏/٠٢‏/٢٠٢٠

    Vladimir Vapnik: Predicates, Invariants, and the Essence of Intelligence

    Vladimir Vapnik is the co-inventor of support vector machines, support vector clustering, VC theory, and many foundational ideas in statistical learning. He was born in the Soviet Union, worked at the Institute of Control Sciences in Moscow, then in the US, worked at AT&T, NEC Labs, Facebook AI Research, and now is a professor at Columbia University. His work has been cited over 200,000 times. This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon. This episode is presented by Cash App. Download it (App Store, Google Play), use code “LexPodcast”.  Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time. 00:00 – Introduction 02:55 – Alan Turing: science and engineering of intelligence 09:09 – What is a predicate? 14:22 – Plato’s world of ideas and world of things 21:06 – Strong and weak convergence 28:37 – Deep learning and the essence of intelligence 50:36 – Symbolic AI and logic-based systems 54:31 – How hard is 2D image understanding? 1:00:23 – Data 1:06:39 – Language 1:14:54 – Beautiful idea in statistical theory of learning 1:19:28 – Intelligence and heuristics 1:22:23 – Reasoning 1:25:11 – Role of philosophy in learning theory 1:31:40 – Music (speaking in Russian) 1:35:08 – Mortality

  • Jim Keller: Moore’s Law, Microprocessors, Abstractions, and First Principles

    ٠٥‏/٠٢‏/٢٠٢٠

    Jim Keller: Moore’s Law, Microprocessors, Abstractions, and First Principles

    Jim Keller is a legendary microprocessor engineer, having worked at AMD, Apple, Tesla, and now Intel. He’s known for his work on the AMD K7, K8, K12 and Zen microarchitectures, Apple A4, A5 processors, and co-author of the specifications for the x86-64 instruction set and HyperTransport interconnect. This conversation is part of the Artificial Intelligence podcast. If you would like to get more information about this podcast go to https://lexfridman.com/ai or connect with @lexfridman on Twitter, LinkedIn, Facebook, Medium, or YouTube where you can watch the video versions of these conversations. If you enjoy the podcast, please rate it 5 stars on Apple Podcasts, follow on Spotify, or support it on Patreon. This episode is presented by Cash App. Download it (App Store, Google Play), use code “LexPodcast”.  Here’s the outline of the episode. On some podcast players you should be able to click the timestamp to jump to that time. 00:00 – Introduction 02:12 – Difference between a computer and a human brain 03:43 – Computer abstraction layers and parallelism 17:53 – If you run a program multiple times, do you always get the same answer? 20:43 – Building computers and teams of people 22:41 – Start from scratch every 5 years 30:05 – Moore’s law is not dead 55:47 – Is superintelligence the next layer of abstraction? 1:00:02 – Is the universe a computer? 1:03:00 – Ray Kurzweil and exponential improvement in technology 1:04:33 – Elon Musk and Tesla Autopilot 1:20:51 – Lessons from working with Elon Musk 1:28:33 – Existential threats from AI 1:32:38 – Happiness and the meaning of life

  • #499 – Gary Gallagher: American Civil War, Slavery, Lincoln, Grant & Lee

    ٢٨ يوليو

    #499 – Gary Gallagher: American Civil War, Slavery, Lincoln, Grant & Lee

    Gary Gallagher is a historian of the American Civil War. Thank you for listening ❤ Check out our sponsors: https://lexfridman.com/sponsors/ep499-sc See below for timestamps, transcript, and to give feedback, submit questions, contact Lex, etc. Transcript: https://lexfridman.com/gary-gallagher-transcript CONTACT LEX: Feedback – give feedback to Lex: https://lexfridman.com/survey AMA – submit questions, videos or call-in: https://lexfridman.com/ama Hiring – join our team: https://lexfridman.com/hiring Other – other ways to get in touch: https://lexfridman.com/contact EPISODE LINKS: Gary’s UVA page: https://history.virginia.edu/people/gary-w-gallagher Gary’s Wikipedia: https://en.wikipedia.org/wiki/Gary_W._Gallagher The Confederate War (book): https://amzn.to/4yletel The Union War (book): https://amzn.to/3QT1jED Lee and His Generals in War and Memory (book): https://amzn.to/4fdrbD5 Causes Won, Lost, and Forgotten (book): https://amzn.to/4wFxk1X The Myth of the Lost Cause and Civil War History (book): https://amzn.to/4vsAogU The Great Courses – The American Civil War: https://bit.ly/4gDX3mQ SPONSORS: To support this podcast, check out our sponsors & get discounts: Upwork: Platform for hiring freelancers. Go to https://upwork.com/lex NetSuite: Business management software. Go to http://netsuite.ai/lex Shopify: Sell stuff online. Go to https://shopify.com/lex LMNT: Zero-sugar electrolyte drink mix. Go to https://drinkLMNT.com/lex BetterHelp: Online therapy and counseling. Go to https://betterhelp.com/lex Perplexity: AI-powered answer engine. Go to https://perplexity.ai/ Plaud: AI-powered note-taking devices and software. Go to https://plaud.ai/lex OUTLINE: (00:00) – Introduction (00:07) – Sponsors, Comments, and Reflections (08:36) – What caused the Civil War? (18:33) – Slavery (46:07) – Lincoln (1:01:03) – Grant vs Lee (1:09:57) – Could the Civil War have been avoided? (1:19:23) – The bloodiest war in US history (1:36:31) – How the Confederate Army could’ve won (1:57:05) – Key battles of the Civil War (2:20:07) – Best and Worst Presidents (2:34:06) – Robert E. Lee (2:53:40) – The most important battle of the Civil War (3:03:51) – The final showdown of the Civil War – Grant vs Lee (3:26:10) – Lost Cause and Confederate Monuments (3:43:37) – Extreme political division in US

  • Claude Code + Codex Can FINALLY Work Together (Buzz AI)

    ٣٠ يوليو

    Claude Code + Codex Can FINALLY Work Together (Buzz AI)

    Building an Agent Team on Buzz (Complete Guide) Subscribe to Vinny https://youtube.com/@stealtime?si=khW3yG-ovHdjYAtY Buzz is a new free platform, that feels exactly like Slack, except the agents aren't add ons, they are equals. and in 5 minutes you can create an agent team. And it works with your existing Codex and Claude Code subscriptions... So it's free to use. This video is divided into 2 parts: --- ⭐ Part 1 Conversation with Vinny (@hot_town on X) 00:00 Introduction 01:59 Why is Buzz Going Viral? 07:08 Creating Agents & Channels with Fizz 20:03 Adding Other Harnesses (OpenCode, Cursor) 21:25 The Buzz Mobile App 22:36 Payments & Shared Compute 25:36 Workflows & Projects: A GitHub Killer? 30:14 The Future of Buzz: An Open Cowork? 35:13 Automations, Triggers & Trusting Your Agents --- ⭐ Part 2 - Getting Started Tutorial (My workflow) 42:32 Tutorial and Breakdown 43:03 Downloading Buzz And Default Agents 43:35 Creating your first agent 45:13 Adding Agents to channels 45:43 Why I use Codex as Lead Agent 47:06 Using Codex, Claude Code and Grok for task 48:52 Adding Muse (Meta Model) using OpenRouter 51:23 iOS app is Free and easy to use 51:50 My management Channel (My #1 use case)

  • A Paradigm Shift in Cybersecurity: Mastering the 3 dimensions of cyber safety with Safe XDR

    ٠٥‏/٠٩‏/٢٠٢٤

    A Paradigm Shift in Cybersecurity: Mastering the 3 dimensions of cyber safety with Safe XDR

    Is your cybersecurity strategy obsolete? Join us as we disrupt conventional thinking and expose why traditional defences are failing. In this episode, we dive into Safe XDR—the world’s first AI-verified Extended Detection and Response (XDR) platform. Designed for Continuous Threat Exposure Management (CTEM), Safe XDR promises unmatched safety, security, and assurance by integrating the 3 critical dimensions: Coverage, Proactivity, and Mean Time to Respond (MTTR). Prepare for a paradigm shift: Proactivity: Are you waiting for a disaster? Learn why predictive insights are no longer a luxury but a necessity in today's aggressive threat environment. Discover how our Risk Operations Centre (ROC) and Security Operations Centre (SOC) leverage proactive, contextualised information to outpace threats and avoid incidents before they happen.

  • David Friedberg on the Economic Crisis Nobody Wants to Fix

    ٢٢ يوليو

    David Friedberg on the Economic Crisis Nobody Wants to Fix

    David Friedberg takes America's 250th anniversary as a starting point to ask where does the country actually stand? And how do the bottom 50% get left behind? He argues the wealth gap is widely misunderstood, pointing to roughly $183 trillion in total US household net worth, compared to about $8 trillion held by billionaires and $4 trillion by the bottom half of Americans. His view is that the rich didn't take everything. Instead, the bottom 50% never got to own the productive assets that created the last 50 years of wealth, and.. as Friedberg puts it: "The truth is that the bottom 50% were left behind because of bad tax policy." From there, Friedberg breaks down the policy decisions he believes created today's affordability crisis, including a tax code that taxes capital below labor, a Social Security system invested in Treasury bonds instead of equities since 1982, the shift away from pensions after ERISA, and government policies that drove housing, healthcare, and education costs higher. He argues those failures have created the conditions driving the rise of socialism in America. "Americans should feel good about America. We just have to fix the policies." David Friedberg: https://x.com/friedberg Molly O’Shea: https://x.com/MollySOShea  Sourcery: ⁠https://x.com/sourceryy 𝐄𝐏𝐈𝐒𝐎𝐃𝐄 𝐋𝐈𝐍𝐊 YouTube: https://youtu.be/LGkRR4ZNsEA 𝐒𝐏𝐎𝐍𝐒𝐎𝐑𝐒 • Brex—The modern finance platform, combining the world’s smartest corporate card with integrated expense management, banking, bill pay, & travel. https://brex.com/sourcery  • Turing—Turing delivers top-tier talent, data, and tools to help AI labs improve model performance—and enables enterprises to turn those models into powerful, production-ready systems. https://turing.com/sourcery  • VCX—VCX is the public ticker for private tech, allowing investors of all sizes to invest in venture capital. View The Portfolio at http://GetVCX.com   • Deel—Deel is the global people platform that helps startups hire, manage, pay, and equip anyone, anywhere. Trusted by more than 35,000 fast-growing companies, Deel is the people platform that just works, so teams can scale without the chaos. Visit: https://www.deel.com/sourcery • Public–Investing platform Public just launched Generated Assets, which lets you turn any idea into an investable index with AI. With Generated Assets, you can build, backtest, refine, and invest in any thesis with AI. Gone are the days of one-size-fits-all ETFs. https://public.com/sourcery   Follow Sourcery for the latest updates! https://www.sourcery.vc Disclosure Paid Endorsement. Brokerage services by Open to the Public Investing Inc, member FINRA & SIPC. Advisory services by Public Advisors LLC, SEC-registered adviser. Crypto trading provided by Zero Hash LLC, licensed by the NYSDFS. Generated Assets is an interactive analysis tool by Public Advisors. Output is for informational purposes only and is not an investment recommendation or advice. See disclosures at public.com/disclosures/ga. Matched funds must remain in your account for at least 5 years. Match rate and other terms are subject to change at any time. 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) David Friedberg, CEO at Ohalo Genetics & Co-Host at All-In (01:11) Is California functionally bankrupt? (02:28) The real reason Americans can't afford anything anymore (12:13) Why a wealth tax is really government theft (21:22) Why blaming billionaires is a political strategy, not a solution (25:33) How Socialism grows like a virus (30:40) Inside Trump Accounts: a 401(k) for every American (34:22) Why rational arguments can't compete with viral outrage (40:56) Jeff Bezos's radical fix for the wealth gap (45:47) 5 years till Social Security is bankrupt (46:35) Is AI actually coming for your job? (50:29) The K-shaped economy (55:39) Five things America needs to fix to survive (59:21) David's research process (1:02:54) "It's about making Americans feel good again"

  • The best AI agents cost less than you think | Eno Reyes, Factory

    ١٦ يوليو

    The best AI agents cost less than you think | Eno Reyes, Factory

    Eno Reyes is the co-founder and CTO at Factory, a $1.5 billion company turning signal into deployed code inside some of the world's biggest engineering orgs. Before founding Factory in 2023, he was an engineer at Microsoft and then Hugging Face. In this conversation, Eno unpacks why the harness matters more than the model running underneath it, how to build your own 24/7 software factory, and why he's "bullish on humans in the loop for a very long time.” – We also discuss: Why product management isn't going awayThe engineer who lint-checks Factory's own agentsWhy coding agents might become the best general agentsThe platonic representation hypothesisWhy Factory might hide when "memory" is happeningBuilding Factory's universal meta harnessTokenomics, and how routing cuts the bill– Timestamps: (00:00) Introduction (01:19) What a 24/7 autonomous software factory actually means (03:16) Why product management isn't going away (06:56) Alvin, the engineer who lint-checks Factory's own agents (10:16) "It makes me very bullish on humans in the loop for a very long time" (11:37) The Disney Epcot analogy for rolling out AI (16:47) Why coding agents might become the best general agents (20:54) The case against a model-independent harness, and Eno's counter (25:44) The platonic representation hypothesis explained (32:42) Why model quirks are like being left or right-handed (39:28) Why you could technically decompile Factory's entire harness (44:20) Why memory might be AI's most overused word (46:47) Inside AutoWiki and its Lore feature (55:32) Agent readiness: the deterministic feedback agents need (57:12) Missions: Factory's universal meta harness (1:01:12) "It's kind of turtles all the way down": validating the validators (1:04:37) Tokenomics: what missions cost, and how routing cuts the bill (1:11:08) Why Eno is bullish on open models (1:14:30) BenchBench, and why code review benchmarks might be broken – References: AiderAlvin SngAmpAndrej KarpathyAnthropicAnthropic: Emotion concepts and their function in a large language modelCursorDeep AgentsDeepWikiEpcotFactoryGLMHarborHugging FaceHuggingGPTKimiLangGraphLangSmithMiniMaxOpen Knowledge Format (OKF)OpenAIOpenRouter Model FusionRampSakana FuguSWE-benchTerminal-Bench– Where to find Eno: LinkedInTwitter/X– Where to find Harrison: LinkedInTwitter/X– Where to find LangChain: WebsiteDocs– Send feedback or questions to maxagency@langchain.dev

عروض جديدة

  • Inside Product at Cisco
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أفريقيا والشرق الأوسط، والهند

  • Algeria
  • Angola
  • Armenia
  • Azerbaijan
  • Bahrain
  • Benin
  • Botswana
  • Burkina Faso
  • Cameroun
  • Cape Verde
  • Chad
  • Côte d’Ivoire
  • Congo, The Democratic Republic Of The
  • Egypt
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  • India
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  • Nigeria
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  • Congo, Republic of
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  • Senegal
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  • South Africa
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  • Tajikistan
  • Tanzania, United Republic Of
  • Tunisia
  • Turkmenistan
  • United Arab Emirates
  • Uganda
  • Yemen
  • Zambia
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آسيا والمحيط الهادئ

  • Afghanistan
  • Australia
  • Bhutan
  • Brunei Darussalam
  • Cambodia
  • 中国大陆
  • Fiji
  • 香港
  • Indonesia (English)
  • 日本
  • Kazakhstan
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  • Lao People's Democratic Republic
  • 澳門
  • Malaysia (English)
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  • Myanmar
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  • Nepal
  • New Zealand
  • Pakistan
  • Palau
  • Papua New Guinea
  • Philippines
  • Singapore
  • Solomon Islands
  • 台灣
  • Thailand
  • Tonga
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  • Uzbekistan
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أوروبا

  • Albania
  • Armenia
  • Österreich
  • Belarus
  • Belgium
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  • Bulgaria
  • Croatia
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  • Czechia
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  • Deutschland
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  • Hungary
  • Iceland
  • Ireland
  • Italia
  • Kosovo
  • Latvia
  • Lithuania
  • Luxembourg (English)
  • Malta
  • Moldova, Republic Of
  • Montenegro
  • Nederland
  • North Macedonia
  • Norway
  • Poland
  • Portugal (Português)
  • Romania
  • Россия
  • Serbia
  • Slovakia
  • Slovenia
  • España
  • Sverige
  • Schweiz
  • Türkiye (English)
  • Ukraine
  • United Kingdom

أمريكا اللاتينية والكاريبي

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  • Antigua and Barbuda
  • Argentina (Español)
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  • Brasil
  • Virgin Islands, British
  • Cayman Islands
  • Chile (Español)
  • Colombia (Español)
  • Costa Rica (Español)
  • Dominica
  • República Dominicana
  • Ecuador (Español)
  • El Salvador (Español)
  • Grenada
  • Guatemala (Español)
  • Guyana
  • Honduras (Español)
  • Jamaica
  • México
  • Montserrat
  • Nicaragua (Español)
  • Panamá
  • Paraguay (Español)
  • Perú
  • St. Kitts and Nevis
  • Saint Lucia
  • St. Vincent and The Grenadines
  • Suriname
  • Trinidad and Tobago
  • Turks and Caicos
  • Uruguay (English)
  • Venezuela (Español)

الولايات المتحدة وكندا

  • Canada (English)
  • Canada (Français)
  • United States
  • Estados Unidos (Español México)
  • الولايات المتحدة
  • США
  • 美国 (简体中文)
  • États-Unis (Français France)
  • 미국
  • Estados Unidos (Português Brasil)
  • Hoa Kỳ
  • 美國 (繁體中文台灣)

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  • Benin
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  • Tajikistan
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  • Uganda
  • Yemen
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  • Afghanistan
  • Australia
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  • Brunei Darussalam
  • Cambodia
  • 中国大陆
  • Fiji
  • 香港
  • Indonesia (English)
  • 日本
  • Kazakhstan
  • 대한민국
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  • Lao People's Democratic Republic
  • 澳門
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  • Maldives
  • Micronesia, Federated States of
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  • Myanmar
  • Nauru
  • Nepal
  • New Zealand
  • Pakistan
  • Palau
  • Papua New Guinea
  • Philippines
  • Singapore
  • Solomon Islands
  • 台灣
  • Thailand
  • Tonga
  • Turkmenistan
  • Uzbekistan
  • Vanuatu
  • Vietnam

أوروبا

  • Albania
  • Armenia
  • Österreich
  • Belarus
  • Belgium
  • Bosnia and Herzegovina
  • Bulgaria
  • Croatia
  • Cyprus
  • Czechia
  • Denmark
  • Estonia
  • Finland
  • France (Français)
  • Georgia
  • Deutschland
  • Greece
  • Hungary
  • Iceland
  • Ireland
  • Italia
  • Kosovo
  • Latvia
  • Lithuania
  • Luxembourg (English)
  • Malta
  • Moldova, Republic Of
  • Montenegro
  • Nederland
  • North Macedonia
  • Norway
  • Poland
  • Portugal (Português)
  • Romania
  • Россия
  • Serbia
  • Slovakia
  • Slovenia
  • España
  • Sverige
  • Schweiz
  • Türkiye (English)
  • Ukraine
  • United Kingdom

أمريكا اللاتينية والكاريبي

  • Anguilla
  • Antigua and Barbuda
  • Argentina (Español)
  • Bahamas
  • Barbados
  • Belize
  • Bermuda
  • Bolivia (Español)
  • Brasil
  • Virgin Islands, British
  • Cayman Islands
  • Chile (Español)
  • Colombia (Español)
  • Costa Rica (Español)
  • Dominica
  • República Dominicana
  • Ecuador (Español)
  • El Salvador (Español)
  • Grenada
  • Guatemala (Español)
  • Guyana
  • Honduras (Español)
  • Jamaica
  • México
  • Montserrat
  • Nicaragua (Español)
  • Panamá
  • Paraguay (Español)
  • Perú
  • St. Kitts and Nevis
  • Saint Lucia
  • St. Vincent and The Grenadines
  • Suriname
  • Trinidad and Tobago
  • Turks and Caicos
  • Uruguay (English)
  • Venezuela (Español)

الولايات المتحدة وكندا

  • Canada (English)
  • Canada (Français)
  • United States
  • Estados Unidos (Español México)
  • الولايات المتحدة
  • США
  • 美国 (简体中文)
  • États-Unis (Français France)
  • 미국
  • Estados Unidos (Português Brasil)
  • Hoa Kỳ
  • 美國 (繁體中文台灣)