Here is the #1# performing stock in the S&P 500 every single year since 2000: 2000: $DYN Dynegy +223% 2001: $ODP Office Depot +160% 2002: $BSX Boston Scientific +76% 2003: $AV Avaya +379% 2004: $AAPL Apple +199% 2005: $VLO Valero Energy +127% 2006: $ICE Intercontinental Exchange +196% 2007: $AMZN Amazon +140% 2008: $DLTR Dollar Tree +61% 2009: $XL XL Capital +395% 2010: $NFLX Netflix +216% 2011: $EXPE Expedia +184% 2012: $REGN Regeneron +203% 2013: $NFLX Netflix +298% 2014: $SWKS Skyworks Solutions +159% 2015: $NFLX Netflix +133% 2016: $NVDA Nvidia +224% 2017: $NRG NRG Energy +132% 2018: $AMD AMD +81% 2019: $AMD AMD +148% 2020: $TSLA Tesla +743% 2021: $DVN Devon Energy +194% 2022: $OXY Occidental Petroleum +119% 2023: $NVDA Nvidia +239% 2024: $PLTR Palantir +340% 2025: $WDC Western Digital +283% 2026 YTD: SanDisk +526% What's your pick for 2027?

🎓 Countries with the best-performing students 1. 🇨🇳 China*: 579 2. 🇸🇬 Singapore: 553 3. 🇹🇼 Taiwan: 531 4. 🇲🇴 Macao: 530 5. 🇯🇵 Japan: 522 6. 🇰🇷 South Korea: 516 7. 🇪🇪 Estonia: 511 8. 🇭🇰 Hong Kong: 499 9. 🇬🇧 UK: 498 10. 🇳🇿 New Zealand: 495 11. 🇨🇦 Canada: 495 12. 🇮🇪 Ireland: 493 13. 🇦🇺 Australia: 493 14. 🇨🇭 Switzerland: 490 15. 🇵🇱 Poland: 487 16. 🇺🇸 US: 485 17. 🇫🇮 Finland: 482 18. 🇦🇹 Austria: 480 19. 🇧🇪 Belgium: 479 20. 🇨🇿 Czechia: 478 21. 🇹🇷 Türkiye: 476 22. 🇮🇹 Italy: 475 23. 🇱🇹 Lithuania: 474 24. 🇩🇪 Germany: 472 25. 🇸🇪 Sweden: 472 26. 🇳🇱 Netherlands: 470 27. 🇩🇰 Denmark: 470 28. 🇵🇹 Portugal: 468 29. 🇫🇷 France: 466 30. 🇸🇰 Slovakia: 464 31. 🇭🇺 Hungary: 464 32. 🇸🇮 Slovenia: 463 33. 🇪🇸 Spain: 462 34. 🇭🇷 Croatia: 461 35. 🇱🇺 Luxembourg: 458 36. 🇳🇴 Norway: 458 37. 🇱🇻 Latvia: 453 38. 🇦🇪 UAE: 448 39. 🇮🇸 Iceland: 438 40. 🇮🇱 Israel: 437 Average of maths, reading and science scores among 15-year-olds. *China represents only Beijing, Shanghai, Jiangsu and Zhejiang. Source: OECD, PISA 2025 Results

I’ve had a lot of conversations with people who want to finance and trade compute as an infrastructure asset. One question I keep coming back to: once you’ve financed a GPU server for five to ten years, how do you actually know what you own—and what condition it’s in—throughout those five years? How do you independently verify which physical GPUs and components are actually there? How do you know those servers are being properly operated and maintained when they may sit in a data center thousands of miles away? And how do you know the equipment you financed on Day 1 is still performing as expected on Day 1,000? Physical inspection doesn’t scale. Self-reporting isn’t enough. You need third-party verification. That’s what we’re building with SiliconMark. We work with infrastructure providers to track machines down to component-level UUIDs—GPU, CPU and the broader system—and build a persistent identity and performance history for the asset. You can know what the machine is, its expected depreciation curve, how it is actually performing, its thermal behavior and quality history, with timestamped records over its lifecycle. And because our tests are open-sourced, the results are reproducible and independently verifiable. Think of it as a digital service record for compute infrastructure, maintained by an independent third party. For equipment financing, knowing the original purchase price isn’t enough. You need to continuously know what the asset is, that it exists, how it has been treated, how it is performing, and ultimately what it is worth. If GPUs are going to become a financeable and tradable institutional infrastructure asset class, this verification layer is a fundamental building block. Third-party verification is the trust layer between the physical GPU and the financial asset.