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The AI Bubble Monitor is a tool tracking indicators and metrics related to potential overvaluation in the AI market.
Anthropic's Q3 revenue reportedly reached $16.8B, but monthly growth flattened between July and September, signaling a meaningful slowdown that could temper IPO expectations and pressure AI compute providers like CoreWeave.
The article argues there is no single AI adoption rate, comparing survey-based reach, transaction-based paid demand, production deployment, and financial-return measures from sources like McKinsey, Ramp, and the US Census, and explains why their differing denominators, visibility, and time periods make the figures non-comparable.
The author analyzes recent earnings reports from tech giants using a “two phases, three steps” framework, arguing that the current AI boom is primarily driven by investment rather than a surge in total factor productivity, and will use this framework to analyze the superconductivity industry chain.
A Chinese-language in-depth opinion piece exploring whether AI has truly created incremental value. Drawing on the recent sharp selloff in US equities (Intel down 28.6%, Google down 12.6%, Reddit down 29%) alongside rising hardware prices, collapsing token prices, and disappearing traffic, the author argues that AI is destroying value by making intelligence no longer scarce, and believes we are on the eve of an AI bubble bursting, with companies like ByteDance and Microsoft reinvesting nearly all of their profits into AI infrastructure.
A founder reflects on the wave of big-tech AI agent launches in ten weeks (xAI Grok Bot, Meta Muse, OpenAI Dots, Google Gemini agent, Anthropic Claude Duet), praising their individual strengths while arguing that repeated onboarding and fragmented context is the real problem — and pitching Vestra as a shared context layer where agents plug in.
Ed Yardeni warns that AI companies may end up bailing each other out as the industry becomes increasingly interconnected, with Anthropic potentially rescuing a struggling neocloud highlighting how even competitors may become too important to fail.
The author reiterates that their "two stages, three steps" investment analysis framework has been validated, noting that the five investment opportunities they identified earlier all rose within a week, with half of them gaining more than 10%, and reminds investors to take profits in batches while simultaneously building up cash reserves.
Apollo Global Management chief economist Torsten Slok argues that AI has delivered zero financial payoff to non-tech companies in the S&P 493, with flat profit margins and no evidence of productivity gains despite massive investments.
The tweet shares an analysis of the money flows in AI infrastructure for 2027, with detailed content provided mainly through an external link.
An analysis of the AI agents business landscape, splitting the market into generalist enterprise agents, specialist agents, and consumer agents, and arguing that startups like Lovable and Legora struggle against frontier labs that subsidize plans and own the model layer, relying on VC funding and workflow lock-in to survive.
CoinMarketCap's September 2026 Monthly Exchange Report shows spot volume rose 30.7% to $762.7B, roughly 2.7 times the growth of derivatives, while Binance's market share climbed to a sixth straight monthly increase at 44.03%.
Over the past two years, eight publicly listed U.S. AI security companies—Cisco, Palo Alto, Tenable, SentinelOne, F5, CrowdStrike, Zscolar, and Fortinet—have each acquired an AI-native firewall startup. The actual deal values were far lower than media reports suggested, with the cheapest deal costing just $40.6 million.
Someone open-sourced the KRONOS model, which treats each candlestick as a token to predict the next candle (pre-trained on 12 billion candlesticks). It can be integrated 100% free into Claude Code and TradingView to build a full AI crypto trading and prediction system.
Neoclouds are moving beyond pure GPU rental and building moats by acquiring software companies, because renting compute alone is no longer scarce and inevitably leads to price wars. Nscale, Nebius, IREN, CoreWeave, Crusoe and others are all making acquisitions to boost customer stickiness and product differentiation.
Gartner forecasts AI providers will spend nearly $1T on infrastructure in 2026 and $6T more from 2027 to 2030, warning that over $3.5T of that could face write-downs as revenue fails to cover costs. Asset-light AI-native providers and exposed neoclouds are highlighted as key risks, with AI-optimized IaaS growth deemed too slow to recoup investments before current chips are replaced.
A commenter analyzes the release of DeepSeek-V4.1-Flash-1017 as a positive for the AI industry's profitability: improved token cost-efficiency will drive up AI penetration and demand for cloud providers' infrastructure. Unlike the earlier DeepSeek shock, market conditions have since changed.
A commentary highlighting Prof. Van Nieuwerburgh's research that AI data centers require at least $3.5 trillion in annual revenue to service their debt, raising doubts about whether OpenAI, Anthropic, and others can generate returns fast enough to avoid a bubble.
Anthropic's performance reportedly fell short of market expectations, but combined revenue for OpenAI and Anthropic continues to show stable quarter-over-quarter growth.
文章探讨AI热潮可能以金融泡沫破裂而非技术失败告终：到2030年AI行业计划投入约7万亿美元基础设施建设，但收入难以支撑，Gartner预测算力收入与支出之间存在结构性缺口，且CoreWeave等公司的债务风险正在上升。