World Financial Review

Around two months ago, Mark Zuckerberg and Priscilla Chan quietly detonated a debate that had been simmering for years beneath the surface of elite philanthropy. With a few carefully chosen words, they announced a major redirection of the Chan Zuckerberg Initiative’s mission. The pledge that once positioned itself as a sweeping effort to address social inequality, education, and community-based programs would now go “all in on AI-powered biology for our next chapter.” In a vacuum, that sentence sounds like a harmless shift in priorities, maybe even an inspiring one. But it landed like a thunderclap because it exposed something deeply uncomfortable about how modern charitable giving actually works, who it serves, and how much power it quietly removes from democratic systems. The public reaction was swift and angry. Critics were quick to point out the irony of a tech billionaire whose company is pouring billions into artificial intelligence now channeling most of his charitable efforts i...

For nearly six years after Jeffrey Epstein’s death, one deceptively simple question has refused to go away: how did he actually make his money? The number that tends to anchor the discussion is $577 million, the estimated value of the assets detailed in the will Epstein signed just two days before his death in August 2019. That figure alone would make him one of the wealthiest private financiers of his generation, yet unlike his peers, Epstein left behind no transparent record of business success, no clearly verifiable investment track record, no large firm with dozens of analysts and traders, and no obvious product that justified the extraordinary fees he claimed to command. What remains instead is a financial life defined by opacity, offshore entities, and relationships with some of the richest and most powerful people in the world, a combination that has made following the money extraordinarily difficult and deeply unsettling. Epstein was most often described in public as a financia...

For most of the past decade, Silicon Valley has been driven by a simple assumption: if you build enough computing power, intelligence will inevitably emerge. Bigger data centers, more GPUs, larger models, and more money poured into the system have become the industry’s default response to every competitive threat. Yet nowhere is this assumption being tested more aggressively—or more expensively—than at Meta, where Mark Zuckerberg has committed what may ultimately exceed six hundred billion dollars to an all-in pursuit of artificial intelligence that currently produces little direct revenue and no clear path to commercial payoff. Over the past three years, Big Tech as a whole has spent hundreds of billions of dollars expanding AI infrastructure. For companies like Microsoft, Google, Amazon, and Oracle, the logic is straightforward. They are cloud providers. They build enormous data centers, fill them with NVIDIA GPUs, and rent that computing power to customers ranging from startups to g...