Dalio Warns: AI Boom Shows Signs of a Bubble, Day of Reckoning Will Be the Time of Burst

marsbitPublished on 2026-06-05Last updated on 2026-06-05

Abstract

Ray Dalio, founder of Bridgewater Associates, warns that the current artificial intelligence investment boom shows classic signs of a bubble, which he expects will eventually burst. In a Bloomberg Television interview, he noted that great technological revolutions often lead to capital inflows that create bubbles, making it difficult for investors and companies to calibrate their spending accurately—either overspending to capture market share or underspending and losing their competitive position. This caution comes amid significant rallies in AI-related assets, particularly chipmakers, driven by soaring demand for data centers and high-bandwidth chips, raising debates about overheating valuations. In contrast, Nvidia CEO Jensen Huang recently asserted that investors embracing the AI wave would see "crazy" returns and dismissed concerns over return on investment for data center spending as outdated. Dalio, however, focuses on the risks in the profit realization phase. He argues that bubbles tend to show signs of破裂 when markets transition from investment to the need for tangible returns, describing the burst as a process of converting paper wealth into cash. While acknowledging AI's intrinsic value, he expressed concern over the future profitability of some AI companies, suggesting the market is repeating a familiar pattern. The 76-year-old billionaire, who fully exited Bridgewater in 2025, has a net worth estimated at $21.5 billion according to the Bloomberg Billionaires I...

Source: Jinshi Data

Ray Dalio, founder of Bridgewater Associates, has issued a warning about market risks surrounding the capital frenzy driven by artificial intelligence, believing the current situation already shows typical bubble characteristics and anticipates that this phase will ultimately end.

In an interview with Bloomberg Television on Wednesday, Dalio pointed out that waves of technological change are often accompanied by excessive capital inflows. "All great technological revolutions create bubbles," he said, while emphasizing that it is difficult for investors to precisely gauge the scale of investment; companies either invest heavily regardless of cost to capture the market or lose their competitive position due to insufficient investment.

This judgment comes against the backdrop of a significant surge in AI-related assets. Driven by demand for data center construction, especially for high-bandwidth chips, chip companies have become a core target for Wall Street capital, propelling the overall market to new highs repeatedly. Alongside this rally, there has been intense internal market debate over whether valuations have become overheated.

NVIDIA CEO Jensen Huang recently expressed a different stance publicly. In his remarks this week, he stated that investors willing to bet on the AI wave will receive "crazy" returns.

In a speech the previous day, he also responded to concerns about valuations. Addressing voices worried that massive investments in data centers might fail to yield returns, he mentioned: "Remember last year when we gathered, the talk and narrative around this investment were all asking: What's the return on investment (ROI)?" He then countered: "Now give me an example, find me a crazy person who's still saying that. They would sound crazy."

In contrast, Dalio is more focused on the risks at the stage when profits need to be realized. He believes that once the market enters the stage where investments must translate into actual earnings, bubbles often show signs of bursting. "The process of popping the bubble is essentially the process of converting paper wealth into cash," he said, expressing concerns about the future profitability of some AI companies. Although he acknowledges that AI itself holds significant value, he also bluntly stated that the current market trend "is going down that same path."

Dalio, 76, is the founder of Bridgewater Associates, one of the world's largest hedge funds. He completed his full exit from the company in 2025, including selling all remaining shares and resigning from the board. According to the Bloomberg Billionaires Index, his personal net worth is approximately $21.5 billion.

Related Questions

QWhat warning about the AI investment boom does Ray Dalio issue in the article?

ARay Dalio warns that the current AI-driven capital boom is showing typical bubble characteristics, and he expects this phase will eventually come to an end.

QAccording to Dalio, what is a common outcome of great technological transformations in terms of investment?

AAccording to Dalio, all great technological transformations tend to create investment bubbles due to excessive capital pouring in.

QWhat does Nvidia's CEO Jensen Huang predict for investors who commit to the AI wave?

ANvidia's CEO Jensen Huang predicts that investors who commit to the AI wave will receive 'crazy' returns.

QWhat specific stage does Dalio identify as the point where an investment bubble often shows signs of bursting?

ADalio identifies the stage when the market needs to translate investments into actual profits as the point where a bubble often shows signs of bursting.

QWhat action did Ray Dalio take regarding Bridgewater Associates in 2025?

AIn 2025, Ray Dalio fully exited Bridgewater Associates by selling all his remaining shares and resigning from the board of directors.

Related Reads

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

Silicon Valley investor and "Godfather of Startups" Steve Hoffman warns that combining Web3 with AI is likely a trap, not a promising venture. In an interview, Hoffman argues that while AI is a foundational technology touching all industries, Web3 adds complexity, friction, and regulatory risk without solving mainstream consumer or business needs. He advises founders to focus on deep, specialized applications where startups can out-iterate giants, rather than on generic features easily replicated by large tech companies. Hoffman observes that Silicon Valley will lead foundational AI research, while China excels at rapid, large-scale application and commercialization, particularly in robotics. He stresses that AI-driven autonomous agents capable of collaborative, multi-step tasks are 2-4 years away, which will cause significant job displacement. The solution is not to slow AI but to redesign business models around human-AI collaboration and reform social systems like education and retraining. For startups, Hoffman recommends focusing on vertical, expertise-heavy domains to build defensibility. He sees major opportunities in AI fraud detection and cybersecurity. Key founder mindsets include systemic thinking over feature-focus, relentless customer centricity, building adaptive teams, and deeply understanding AI's capabilities and limits. Hoffman is also leading a non-profit initiative to establish university centers aimed at training future leaders in responsible, human-value-aligned AI innovation.

marsbit49m ago

Silicon Valley 'Startup Guru' Steve Hoffman: Web3 + AI Could Be a Trap

marsbit49m ago

Token Inefficient, Economy Tokenless

The article "Tokens Aren't Economical, Economics Aren't Tokenized" analyzes a pivotal shift in the AI industry from a technology-driven narrative to one dominated by capital efficiency. It highlights two concurrent trends: a severe capital shortage due to the exorbitant and recurring costs of compute (e.g., OpenAI's high burn rate) and a wave of corporate spin-offs where major tech companies are separating their AI units (like Kuaishou's Kling and Baidu's Kunlunxin). The core argument is that AI's "anti-internet" business model, where user growth increases costs rather than profits, has created a disconnect between high valuations and actual cash flow. Spin-offs address this by allowing AI assets to be valued independently. Within a parent company, they are seen as cost centers, but as standalone entities, they are priced based on their growth potential and scarcity in the primary market, leading to massive valuation premiums (e.g., Kling's estimated value tripling post-spin-off). The industry is at an inflection point, moving from "model worship" to "value realization." The competition is evolving from a pure compute (GPU) race to a broader focus on systemic efficiency and full-stack engineering (involving CPUs and orchestration) to achieve viable commercialization. The year 2026 is framed as a critical moment where the industry must definitively answer how to economically translate AI capability into tangible business value, reshaping the sector's future power structure.

marsbit53m ago

Token Inefficient, Economy Tokenless

marsbit53m ago

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

In 2026, a historic shift occurred in AI as major cloud providers' inference spending surpassed training spending for the first time, signaling a move from "building large models" to "using large models." This shifts the core challenge from computing power to the "memory wall"—the bottleneck of data movement (model weights, activations, KV Cache) between external DRAM and processors, where energy and latency from data transfer far exceed computation itself. Companies like Nvidia face GPU idle time due to bandwidth limits. In contrast, Cerebras Systems adopts a radical "wafer-scale" approach with its Wafer-Scale Engine (WSE). Instead of cutting a silicon wafer into many chips, Cerebras uses almost the entire wafer as one massive chip (WSE-3). This design provides 44GB of on-chip SRAM, delivering memory bandwidth thousands of times higher than traditional HBM (e.g., 21 PB/s vs. Nvidia B200). For LLM inference, weights are streamed layer-by-layer from external MemoryX storage to the chip, avoiding HBM bottlenecks. This results in token generation speeds 1.5–5 times faster than Nvidia's B200 in some models and significant advantages in first-token latency and long-context tasks. Additionally, Cerebras's architecture offers much lower interconnect power consumption (0.15 pJ/bit vs. GPU's ~10 pJ/bit). However, Cerebras faces challenges: SRAM scaling has slowed with advanced nodes, limiting future capacity gains; the chip requires specialized liquid cooling and custom software stacks; and its external I/O bandwidth (150 GB/s) is low compared to NVLink, hindering multi-system scaling for very large models. Competition is intensifying. Major players are pursuing three paths: 1) Developing proprietary inference ASICs (e.g., Google TPU, Microsoft Maia), 2) Leveraging advanced packaging (e.g., TSMC's SoW) to democratize wafer-scale-like integration, potentially eroding Cerebras's process advantage within a few years, and 3) Exploring optical interconnects for ultimate bandwidth. Commercially, Cerebras is transitioning from a hardware vendor to a service provider, facing the immense challenge of building high-power, specialized data centers to meet large contracts (e.g., 250MW/year from 2026–2028). In conclusion, the AI inference era presents a fundamental architectural trade-off. Cerebras opts for extreme physical optimization for low-latency, single-task performance, while Nvidia prioritizes versatility and massive cluster throughput. The path forward remains uncertain, with technology and business models still evolving in the race toward advanced AI.

marsbit59m ago

Crossing the 'Memory Wall': The Wafer-Level Revolution and Computing Power Routes in the AI Inference Era

marsbit59m ago

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

**Title: Has Bitcoin's Rebound Ended, Entering the Late Bear Market Phase?** **Summary:** Bitcoin's price has declined by 13% this week, signaling a potential return to late-stage bear market conditions. The price fell to around $67k, positioned between the Realized Price and Realized Cap Weighted Average. For the first time since early 2022, the Short-Term Holder cost basis has dropped below this key average, confirming a hallmark of late-cycle bear markets. Profitability metrics have collapsed sharply. The 7-day average of the Realized Profit/Loss ratio plummeted from a local high of 3.16 to 0.29, mirroring the February panic sell-off. Critically, the 90-day average never breached the threshold of 2, indicating the recent rally to $82k was a bear market bounce, not a structural shift. Realized losses surged to $1.35 billion daily, with $770 million coming from Long-Term Holders selling at a loss. This accelerating redistribution of supply from weak to strong hands is a necessary but ongoing process for a market bottom. The rally stalled almost precisely at the aggregate cost basis (~$83k) of US spot Bitcoin ETF investors, turning that level into strong resistance and leaving the average ETF holder underwater again. Spot market flows have turned decisively negative, showing sellers are dominating order books despite the price drop. While a significant futures long liquidation event cleared over $400 million in leverage, providing a potential reset, sustained spot demand is yet to materialize. Options markets continue to price in higher future volatility (Implied Volatility) than recent price action (Realized Volatility) has shown, with a persistent skew towards put options, indicating ongoing demand for downside protection. In conclusion, multiple metrics point to a fragile market structure. Resistance at the ETF cost basis, accelerating realized losses, dominant spot selling, and cautious options pricing all suggest the bear market trend persists. A sustainable recovery likely requires a resurgence of spot demand, ETF holders returning to profit, and a clear reduction in selling pressure.

marsbit59m ago

Has Bitcoin's 'Rebound Ended', Officially Entering the Late Bear Market Phase?

marsbit59m ago

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

In today's TechFlow Intelligence Briefing, several major tech stories highlight a growing theme of trust and credibility gaps across AI, crypto, and finance. AI company Anthropic has publicly called for a global pause in AI development, citing risks from Claude's "recursive self-improvement." Ironically, this coincides with reports the company is preparing for a massive IPO targeting a near $1 trillion valuation. This perceived hypocrisy, coupled with widespread user complaints about Claude's declining performance, is sparking debate over whether the safety warning is genuine or a competitive tactic. Meanwhile, in a substantive security move, Anthropic open-sourced a framework for AI-powered vulnerability discovery. In the crypto market, Bitcoin's price drop below $61,000 triggered over $1.16 billion in liquidations, flipping the market into a state where more BTC is held at a loss than at a profit, a historical bearish signal. On the corporate front, SpaceX's highly anticipated IPO is generating immense Wall Street excitement, with Goldman Sachs projecting 100x revenue growth by 2030. However, the S&P 500 has refused to fast-track the company's inclusion post-IPO, potentially limiting immediate institutional demand. Separately, ByteDance's AI app Doubao lost over 6 million monthly active users after introducing a subscription model, highlighting the challenges of AI monetization. Other notable developments include Nvidia certifying HBM4 memory from Samsung, SK Hynix, and Micron; Cloudflare's acquisition of front-end tooling company VoidZero; and its CEO warning that bot traffic now exceeds human traffic online. The underlying narrative connects these events: a trust crisis. From AI firms' contradictory actions and crypto volatility to the clash between SpaceX's hyped narrative and institutional rules, a pattern is emerging where stated intentions and actual practices are increasingly misaligned.

marsbit1h ago

TechFlow Intelligence Agency: Anthropic Calls for Global Pause in AI Development While Preparing for Trillion-Dollar IPO; SpaceX IPO Roadshow Heats Up, But S&P 500 Rejects Fast-Track Inclusion

marsbit1h ago

Trading

Spot
Futures

Hot Articles

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of AI (AI) are presented below.

活动图片

Top Questions