Ken Griffin, founder and CEO of the hedge fund giant Citadel, highlighted a significant shift in investor behavior during a Bloomberg interview.

He described how individuals and institutions are increasingly allocating capital to gold, silver, and Bitcoin as part of what’s being called the “debasement trade”—a strategy to hedge against the erosion of the U.S. dollar’s value due to inflation, excessive money printing, and rising sovereign debt risks.

This trend, Griffin noted, reflects broader efforts to “de-dollarize” portfolios and mitigate exposure to U.S. fiscal uncertainties, including an ongoing government shutdown and expectations of Federal Reserve rate cuts.

Griffin attributed the move to several interconnected factors: The U.S. dollar has declined about 10% year-to-date in 2025, its worst performance in decades, amid inflation running above the Fed’s 2% target and forecasts suggesting it will persist into 2026.

He likened the U.S. economy to being on a “sugar high” from recession-level stimulus measures, fueling asset inflation across markets like stocks, gold, and crypto—despite no actual recession.

With U.S. debt levels soaring and political gridlock (e.g., the shutdown), investors are seeking “non-sovereign” assets that aren’t tied to government promises.

Griffin called this dynamic “really concerning,” as it signals eroding global confidence in the dollar as the ultimate safe haven. This strategy has propelled gold, silver, and Bitcoin to new heights in 2025, with unusual correlations emerging between them and even traditional equities like the S&P 500.

Investors are increasingly viewing gold as a safer store of value than the dollar, with portfolios being “de-risked” against U.S. government debt and fiscal policies. Griffin noted that this includes a surge in crypto assets like Bitcoin, whose “unbelievable” appreciation underscores the trend.

He likened the U.S. economy to being on a “sugar high,” propped up by recession-like stimulus measures amid persistent inflation currently above the Fed’s 2% target and projected at 2-3% next year. Despite booming equities driven by AI and high-performance computing, underlying risks like a weakening dollar are being masked.

Griffin warned that this could erode global confidence in the U.S. as a financial hub, potentially accelerating moves by countries to settle trade in local currencies or digital assets. He also expressed concerns over policies like higher H-1B visa fees, which might deter international talent in STEM fields from coming to the U.S.

Gold and Bitcoin, in particular, have never before been the top two performing asset classes year-to-date, underscoring the novelty of this trade. Analysts like Yan Lee from Bitget describe them as “dual debasement trades,” emphasizing their scarcity and independence from central banks.

Wall Street echoes this: Goldman Sachs recently forecasted even higher gold prices, and ETF inflows into Bitcoin have accelerated, with firms like MicroStrategy pausing buys after amassing $79B in holdings.

While Griffin views this as a red flag for U.S. economic health, it validates Bitcoin’s maturation as a mainstream hedge—once dismissed by traditional finance, now grouped with gold and silver.

If the government shutdown drags on Polymarket odds favor it extending past October 15, or if inflation data disappoints, these assets could rally further, tightening their correlation and pressuring the dollar more.

For investors, it’s a reminder that in times of fiat uncertainty, “hard money” alternatives—physical or digital—are gaining traction as portfolio diversifiers.

Across the arc of human progress, I have divided the world economic history into three fundamental eras: the Invention Society, the Innovation Society, and the Accelerated Society. The Invention Society was when humankind discovered the building blocks of science— gravity, electromagnetism, and calculus—yet lacked the ability to commercialize them. The Innovation Society took those inventions and converted them into products—light bulbs, automobiles, vaccines, and transistors. But now, we are in the Accelerated Society: a civilization where ideas scale instantly through digital fabrics, where code replaces factories, and where intelligence—human or artificial—becomes the new oil.

For Africa, this transition offers the greatest promise in its history. The continent largely missed the full benefits of the industrial and early innovation ages. But in the Accelerated Society, the marginal cost of intelligence is near zero. The same AI algorithm that powers a Silicon Valley startup can also power a logistics company in Lagos or a healthcare agent in Nairobi. The barriers of geography, infrastructure, and even scale have been flattened. What remains is ambition, execution, and knowledge accumulation—three factors that now define competitiveness.

Startups in the Era of Acceleration

Future African startups will not merely copy Western models; they will reframe problems around the continent’s unique realities. A fintech in Lagos will not just digitize payments but reimagine credit scoring for people without formal data footprints. A logistics startup in Kampala will use predictive AI to organize informal transport routes. The startups that win will be those that combine deep local insight with universal intelligence systems.

The Accelerated Society demands that African founders become systems builders, not just app creators. They must design ecosystems—data, APIs, and algorithms—that make AI the engine of inclusion. Just as the Industrial Revolution rewarded those who owned steam and steel, the Accelerated Society will reward those who own intelligence pipelines: the datasets, domain expertise, and adaptive AI models built from Africa’s context.

AI as Africa’s Development Shortcut

Artificial Intelligence represents Africa’s most potent development shortcut. In the past, building national capacity required decades of industrial policy. Today, an AI-trained system can offer near-human diagnostic support to a rural doctor in Sokoto or recommend precision fertilizers to a farmer in Eldoret. This is the power of exponential systems: they compress time, democratize capability, and compound learning.

But to extract this dividend, Africa must build local AI capacity. That means universities that teach prompt engineering, startups that train models on African languages, and governments that deploy AI to predict floods, manage traffic, and optimize public finance. The AI age is not just about technology; it is about institutional redesign, where data becomes a national asset, and intelligence becomes a public utility.

The Future: From Adoption to Creation

In the coming decade, the defining African startups will not be those that merely use AI but those that create AI tuned to local nuances—voice agents that understand Pidgin and Swahili, credit models trained on market transaction data, and educational tutors that teach mathematics through local examples. These are not dreams; they are blueprints for AI-enabled prosperity.

My message is simple: while the West leads in invention and Asia perfects innovation, Africa’s chance lies in acceleration. By leaping over industrial bottlenecks and harnessing AI as the great equalizer, the continent can transform from consumer to creator, from imitator to innovator. The future startup in Africa will not just chase profit; it will code development itself.

OpenAI’s landmark deal with AMD marks one of the most significant GPU supply and equity partnerships in the artificial intelligence industry to date.

The deal, which is projected to generate tens of billions of dollars in revenue for AMD, underscores the fierce race among AI firms to secure the computing power required to sustain large-scale model training and deployment.

Under the partnership, AMD will provide multiple generations of its Instinct graphics processing units (GPUs), beginning with the Instinct MI450 series, which the company says will outperform Nvidia’s forthcoming Rubin CPX chips. The first gigawatt of capacity will be deployed in the second half of 2026, when the MI450 enters production.

AMD said the agreement extends beyond a traditional supply contract, describing it as a “strategic alignment” that integrates OpenAI’s software and hardware optimization feedback into AMD’s GPU design process. The collaboration is expected to shape AMD’s AI roadmap through 2030, with OpenAI serving as both a customer and a development partner.

The six-gigawatt supply commitment — enough to power about 4.5 million homes — marks one of the largest single orders in AMD’s history. AMD’s current Instinct MI355X and MI300X GPUs are already used in certain OpenAI workloads and are recognized for their performance in large language model (LLM) inference, thanks to their expanded memory bandwidth and capacity.

As part of the deal, OpenAI will also receive the right to purchase up to 160 million AMD shares — roughly a 10% equity stake — tied to performance milestones and chip deployment schedules. The first tranche will vest when OpenAI receives the first gigawatt of compute capacity, with subsequent tranches tied to additional purchases up to the full 6 GW.

OpenAI’s ownership stake will further depend on AMD’s stock performance, with the final tranche vesting once the stock hits $600 per share. AMD’s shares closed Friday at $164.67 but surged nearly 35% to $222.24 by Monday after news of the partnership broke — signaling strong investor confidence in AMD’s growing relevance in the AI compute space.

Dr. Lisa Su, AMD’s chair and CEO, described the partnership as transformative. “We are thrilled to partner with OpenAI to deliver AI compute at massive scale,” Su said. “This partnership brings the best of AMD and OpenAI together to create a true win-win enabling the world’s most ambitious AI buildout and advancing the entire AI ecosystem.”

OpenAI CEO Sam Altman echoed the sentiment, calling the deal “a major step in building the compute capacity to realize AI’s full potential.” Altman has made chip diversification a central part of OpenAI’s long-term strategy, seeking to avoid dependency on Nvidia, whose GPUs remain the backbone of most AI systems globally.

The AMD deal follows a wave of agreements OpenAI has announced in recent weeks as it races to secure AI compute infrastructure for its expanding “Stargate” network — a global buildout of supercomputing data centers with planned capacity exceeding seven gigawatts.

Last month, Nvidia agreed to invest up to $100 billion in OpenAI and supply at least 10 gigawatts of AI compute capacity. Around the same time, OpenAI and Broadcom signed a $10 billion deal to co-develop and manufacture custom AI accelerators. The company also inked partnerships with Samsung Electronics and SK Hynix to supply DRAM memory chips and support data center construction in South Korea.

Analysts say the AMD-OpenAI partnership signals a new phase in the global chip race, as OpenAI diversifies suppliers and AMD positions itself as a credible challenger to Nvidia’s near-monopoly in AI GPUs. The collaboration could also reshape competitive dynamics in AI infrastructure, especially as OpenAI pushes forward with projects designed to power the next generation of artificial general intelligence (AGI).

With this deal, AMD moves squarely into the center of the global AI buildout — one that could redefine its market standing and challenge Nvidia’s dominance over the most lucrative sector in modern computing.