🌅 Tekin Morning June 12, 2026: Historic SpaceX IPO, Apple AFM 3 AI & Massive Oracle Breach

Section 1️⃣: SpaceX Historic IPO — The Largest Public Offering Ever at $1.77 Trillion Valuation 🚀💸

June 11, 2026, will be remembered as one of the most significant days in the history of global financial markets. Elon Musk's SpaceX priced its IPO shares at $135, achieving a final valuation of $1.77 trillion and raising $75 billion—a record no company has ever achieved. According to reports from CNBC, Variety, and Business Times, SpaceX sold 555.6 million Class A shares on Thursday, with trading set to begin Friday morning, June 12, on Nasdaq.

This IPO is unprecedented not only in terms of capital raised but also because SpaceX has become the seventh most valuable U.S. company—even surpassing Tesla, Musk's other company. According to Wikipedia and Business Insider reports, this IPO has crowned Elon Musk as America's first dollar trillionaire, as he owns approximately 42% of SpaceX shares. With this calculation, Musk's wealth has exceeded $800 billion.

But why is this IPO so historic? To answer, we need to examine the nature of SpaceX's business. SpaceX is no longer just a rocket launch company; it's a multi-faceted space technology giant with three core divisions: (1) reusable Falcon and Starship launch services, (2) the Starlink satellite network with over 6,400 active satellites providing high-speed internet to more than 3 million subscribers worldwide, and (3) forward-looking programs like Starlink Direct to Cell, AI satellites, and even human missions to Mars.

According to reports from PitchBook and Axios, SpaceX's annual revenue reached $18 billion in 2025, with more than half coming from Starlink. This demonstrates that SpaceX has successfully transformed from a government-dependent contractor into an independent, profitable business. In fact, Starlink has become a financial "cash cow" capable of funding other ambitious programs like Starship and Mars missions.

What makes this IPO particularly remarkable is the timing and market conditions. Unlike many tech IPOs that struggle in volatile markets, SpaceX went public during a period of economic uncertainty and still commanded premium valuation. This speaks to investor confidence not just in Musk's vision, but in the fundamental business model SpaceX has built. The company's diversified revenue streams—launch services, Starlink subscriptions, and government contracts—provide stability that most space startups lack.

However, not everything is positive. Critics argue that SpaceX, at its current valuation, is significantly overpriced. Some analysts point out that comparing SpaceX's P/E ratio (price-to-earnings) with similar companies like Boeing or Lockheed Martin reveals that expectations for SpaceX are extraordinarily high. For instance, if SpaceX's annual revenue is $18 billion and net profit (hypothetically) is $2 billion, its P/E ratio would be around 885—while traditional aerospace companies typically have P/E ratios of 15-20!

The response to this criticism is that SpaceX is an aggressive growth company, not a traditional aerospace contractor. Investors are betting on SpaceX's future: Starship, which could reduce launch costs to 1/10th of current rates, Mars mission programs, and new markets like space tourism and asteroid mining. If SpaceX delivers on these promises, the current valuation will be justified. If not, early investors could face significant losses.

Section 2️⃣: Apple AFM 3 Models — Five Foundation Models Built with Google's Deep Collaboration 🍎🤖

At WWDC 2026, Apple unveiled its biggest transformation in a decade: the introduction of third-generation Apple Foundation Models (AFM 3), built through deep collaboration with Google and leveraging Gemini technology. This news would have seemed unbelievable just months ago—Apple and Google, longtime rivals, joining forces to build the future of artificial intelligence. According to reports from 9to5Mac, Apple Insider, and The Next Web, this collaboration represents a dual-track strategy: Google provided the foundational technology, while Apple customized its models through distillation and fine-tuning processes.

The AFM 3 family comprises five distinct models, each designed for a specific role. Two on-device models and three cloud-based models that together create a unified AI ecosystem for iOS 21, macOS 15, and all Apple products. Craig Federighi, Apple's Senior Vice President of Software Engineering, described this architecture as "a fundamental transformation in how users interact with technology."

The critical point to understand is that AFM 3 models are not simply rebranded Gemini models. According to Apple Insider and MacWorld reports, Apple used a process called "distillation" where large Gemini models act as teachers, and smaller AFM models learn from them. Apple then fine-tuned these models on its own data and optimized their performance for specific use cases. Thus, AFM 3 represents a hybrid of Gemini's knowledge and Apple's customization.

One of the most prominent features of AFM 3 Code Advanced is its sparse 20-billion-parameter architecture. Unlike traditional dense models that activate all parameters for each prediction, sparse models only activate a portion of the network, resulting in dramatic reductions in energy consumption and increased speed. This is the same technique used in models like Claude Mythos and GPT-5.5. Additionally, this model is natively multimodal, meaning it can simultaneously process text, images, audio, and video—something the old Siri never had.

The technical innovation extends beyond just model architecture. Apple has built a custom silicon infrastructure specifically optimized for AI inference. The M4 chips powering Macs and the A18 chips in iPhones include dedicated Neural Engine cores with up to 40 TOPS (trillion operations per second) of AI performance. This hardware-software co-design gives Apple a unique advantage: on-device models can run complex AI tasks without draining battery or compromising privacy.

One of the most intriguing aspects of AFM 3 architecture is Private Cloud Compute (PCC). Apple claims this system is "the world's most secure cloud infrastructure." According to MacStories and Lifehacker reports, PCC uses Apple's proprietary M4 Ultra chips, and all data is end-to-end encrypted. Even Apple cannot access user data. This means when Siri needs to perform a complex task, data is sent to PCC, processed, and immediately deleted—no long-term storage exists.

However, not everything is perfect. Critics note that Apple still lags behind competitors in certain benchmarks. According to published data, AFM 3 Code Advanced scored 79.1% on SWE-bench (a real-world coding test), while Claude Mythos 5 achieved 84.7% and GPT-5.5 scored 78.3%. This means AFM 3 is competitive but doesn't have a decisive advantage. Additionally, some advanced features like real-time voice interaction and advanced coding agents are currently only in beta and likely won't be fully released until fall 2026.

Section 3️⃣: Oracle PeopleSoft Massive Breach — ShinyHunters and CVE-2026-35273 Target 100+ Organizations 🛡️💥

Now we turn to one of the biggest cybersecurity disasters of 2026. The notorious hacking group ShinyHunters exploited a critical zero-day vulnerability in Oracle PeopleSoft, breaching over 100 organizations and stealing sensitive data from millions of individuals. According to reports from TechCrunch, The Hacker News, and Help Net Security, this attack occurred between May 27 and June 9, 2026, primarily targeting universities and educational institutions.

The vulnerability in question is CVE-2026-35273, a Remote Code Execution (RCE) bug in PeopleSoft's Environment Management component. This flaw, rated CVSS 9.8 (Critical), allows attackers to execute arbitrary code on PeopleSoft servers without any authentication, over the internet. In simple terms, anyone who knows the IP address of an organization's PeopleSoft server can hack it—no username, password, or special access required!

According to reports from Google Mandiant and Google Threat Intelligence Group (GTIG), ShinyHunters used this vulnerability to gain access to PeopleSoft systems and steal sensitive data including personal information, academic records, financial data, and even passwords. In one confirmed case, a major U.S. university reported that data from nearly 500,000 current and former students and employees was stolen. ShinyHunters then leaked this data and demanded ransom from victims.

The concerning aspect is that Oracle was initially unaware of this vulnerability's existence. When ShinyHunters began selling stolen data on the dark web, security teams realized a zero-day was being actively exploited. Oracle issued an out-of-band security alert on June 11, 2026, urging all PeopleSoft customers to immediately install the security patch. Unfortunately, many organizations were compromised before patches could be deployed.

What makes this particularly devastating is the perfect storm of factors that converged. First, PeopleSoft is legacy enterprise software from the 1980s, widely used by large organizations because replacing it is prohibitively expensive. Second, universities typically have smaller cybersecurity budgets compared to private companies and often run older software versions. Third, ShinyHunters is a sophisticated criminal group with a proven track record of high-profile breaches including AT&T, Ticketmaster, and now Oracle. They exploited the vulnerability with surgical precision, targeting the education sector where data is valuable but defenses are weaker.

The good news is that Oracle has now released a security patch, and all organizations using PeopleSoft must install it immediately. Additionally, Oracle has recommended that organizations should:

• Immediately install the CVE-2026-35273 patch
• Review PeopleSoft server logs from May 27 onwards to check for signs of compromise
• If compromise indicators are found, immediately reset passwords for all users
• Enable IDS/IPS systems to detect suspicious traffic
• Implement network segmentation to isolate PeopleSoft servers from the public internet
• Conduct forensic analysis to determine the full extent of data exfiltration
• Notify affected individuals and regulatory authorities as required by law

Section 4️⃣: Musk's Audacious Plan — 1 Million AI Satellites and the GigaSat Factory 🛰️🤯

If you thought SpaceX's historic IPO was Elon Musk's most audacious news today, think again! In interviews with Space.com and Tom's Hardware, Musk announced that SpaceX plans to launch one million AI-equipped satellites into Earth orbit by 2030 to create a network of space-based data centers capable of processing heavy AI workloads in space. To achieve this goal, SpaceX has opened an 11-million-square-foot (approximately 1 million square meters) factory called GigaSat in Bastrop, Texas.

According to Tom's Hardware, the GigaSat factory will begin mass-producing AI satellites by late 2027, targeting 1 gigawatt per year capacity. Each satellite will be equipped with dedicated AI chips (likely based on Nvidia or AMD) capable of processing large language models and AI workloads directly in orbit. Power will be supplied by solar panels that, in space, generate electricity continuously without any day-night or weather limitations.

But why does Musk want to move AI data centers to space? The answer is simple: the energy crisis. According to The Next Web and Forbes reports, the entire AI industry faces a major problem: large language models like GPT, Claude, and Gemini consume enormous amounts of electricity. For example, a large AI data center can consume 100 megawatts—equivalent to a small city's power consumption! In many countries, power grids cannot supply this volume, and electricity prices are rising.

Musk's solution? Move data centers to space! In space, the sun shines 24/7, there's no night or day, no clouds block the light, and energy is completely free. Additionally, cooling—one of the biggest challenges for terrestrial data centers—is much simpler in space because the temperature approaches absolute zero. Of course, this doesn't mean no cooling system is needed—space is a vacuum and heat transfer only occurs through radiation, but it's still far more efficient than terrestrial systems.

The economics are compelling on paper. Terrestrial data centers spend roughly 40% of their electricity on cooling alone. In space, passive radiative cooling can handle most thermal management. Solar panels operate at peak efficiency without atmospheric absorption. And with Starship's projected launch costs of $100/kg (compared to current $10,000/kg), the capital cost of deploying space infrastructure becomes manageable. A 1-gigawatt space data center could potentially be deployed for $100-200 billion—expensive, but not prohibitive for the scale of AI computing demand.

Section 5️⃣: Bezos' Prometheus — $12 Billion Investment to Build Artificial General Engineer 💰🤖

While Elon Musk conquers space, Jeff Bezos is conquering the physical industries of the world! Prometheus, the AI startup where Bezos serves as co-CEO, announced Thursday, June 11, that it raised $12 billion in Series B funding, achieving a $41 billion valuation. According to reports from TechCrunch, Semafor, and CNBC, this investment includes participation from financial giants JPMorgan Chase, Goldman Sachs, BlackRock, DST Global, and Arch Venture Partners.

But what is Prometheus and what does it do? Bezos says Prometheus aims to build an "Artificial General Engineer" (AGE)—an AI system capable of automating the entire engineering process from initial design to performance testing to final manufacturing. In simple terms, imagine an AI that can design a jet engine, a pharmaceutical drug, a computer chip, or an automotive part from scratch, simulate it, test it, and prepare it for manufacturing—without requiring a human engineer!

According to Financial Express and GeekWire, Prometheus currently employs about 150 people—most of them engineers and scientists with expertise in machine learning, computational physics, materials science, and CAD/CAM. In an interview with CNBC, Bezos said it's still "premature" to disclose technical details, but he indicated that Prometheus uses a combination of generative AI, advanced simulation engines, and optimization algorithms to "democratize" engineering.

The interesting aspect is that this is the first time since 2021 that Bezos has taken on the CEO role. He stepped down from Amazon in July 2021, and it was widely thought he would never return to active business. But Prometheus demonstrates that Bezos remains passionate about innovation—this time in a field that could fundamentally impact all physical industries.

The technical approach Prometheus is taking represents a significant departure from traditional CAD/CAM workflows. Instead of human engineers using software tools to design products, AGE systems autonomously explore vast design spaces using reinforcement learning and evolutionary algorithms. The AI generates thousands of candidate designs, simulates their performance using computational fluid dynamics, finite element analysis, and molecular dynamics, then iteratively refines designs based on multi-objective optimization criteria like cost, performance, manufacturability, and sustainability.

Section 6️⃣: Citi's Blockchain Revolution — Tokenizing Private Company Shares 🏦⛓️

Finally, we come to one of the most fascinating developments in the financial world. Citigroup announced Thursday that it has launched the world's first blockchain platform for buying and selling private company shares. According to reports from CoinDesk, CryptoNews, and Markets Media, this product is called Digital Depositary Receipts (DDR) and enables tokenization of pre-IPO company shares for wealthy and institutional investors.

The DDR structure is based on the traditional Depositary Receipts (DR) model that has been used in financial markets for years. In this model, the bank acts as custodian, holding the actual company shares, then issues substitute securities (DRs) representing ownership of those shares. The difference with DDR is that these securities are recorded on blockchain and can be traded faster, more transparently, and more cheaply.

According to Citigroup, DDR is built on SDX blockchain infrastructure—a permissioned blockchain operated by SIX Swiss Exchange. This means that unlike public blockchains like Ethereum where anyone can access, SDX is only available to authorized financial institutions. This model allows Citi to enforce KYC/AML (Know Your Customer and Anti-Money Laundering) regulations while still leveraging blockchain benefits like transparency and speed.

Of course, DDR has limitations. According to Wall Street Journal, this product is currently only available to non-U.S. investors due to complex SEC regulations. Additionally, only specific companies can tokenize their shares, not just any company. Citi hopes that in the future, other financial institutions will also use this structure and create an industry standard.