핵심요약

• 아마존 직원이 불필요한 AI 워크로드를 생성해 AI 리더십 보드가 폐지됨
• Gary Marcus씨는 토큰맥싱 감소로 대규모 언어 모델의 경제적 약점이 드러날 수 있다고 경고
• OpenAI와 Anthropic는 AI 모델의 상품화와 경쟁 심화로 수익률이 떨어질 수 있음
• NVIDIA는 토큰 소비 감소로 인한 시장 인식이 악화될 수 있음

도입

이 기사는 AI 산업의 핵심 동향인 '토큰맥싱'의 종말을 알리며, 투자자들에게 AI 관련 기업들의 미래 전망을 재검토할 필요성을 제기합니다. 특히 OpenAI, 앤트로픽, NVIDIA와 같은 주요 기업들의 경제적 구조가 어떻게 변화할지에 대한 통찰을 제공합니다.

본문 1: 토큰맥싱의 경제적 영향

토큰맥싱이 끝나면서 AI 도구의 투자 수익률이 중요한 평가 지표로 부상하고 있습니다. 아마존의 사례처럼 기업들이 AI 사용을 과도하게 장려한 결과, 불필요한 비용이 발생하고 있습니다. 이 현상이 지속되면 AI 산업 전체의 경제적 효율성이 떨어질 수 있습니다. 특히 대규모 언어 모델을 개발하는 기업들은 높은 개발 비용과 낮은 수익률 사이에서 고립될 위험이 있습니다. 투자자들은 이러한 기업들의 재무 건전성을 면밀히 검토해야 합니다.

본문 2: AI 산업의 경쟁 구조 변화

토큰맥싱의 종말은 AI 산업의 경쟁 구조에도 큰 영향을 미칠 전망입니다. OpenAI와 Anthropic는 AI 모델의 상품화와 경쟁 심화로 인해 수익률이 떨어질 수 있습니다. 이는 기업들의 R&D 투자 감소로 이어질 수 있어, AI 기술의 발전 속도가 느려질 가능성도 있습니다. 반면, NVIDIA는 토큰 소비 감소로 인한 시장 인식이 악화될 수 있어, 투자자들은 이 회사의 미래 전망을 신중하게 평가해야 합니다.

결론

AI 산업의 토큰맥싱 시대가 끝나면서 기업들의 AI 투자 전략이 변화하고 있습니다. 투자자들은 AI 관련 기업들의 경제적 구조와 시장 경쟁력을 면밀히 분석해야 합니다. 앞으로도 AI 산업의 동향을 주시하며, 기술 발전과 경제적 효율성 사이의 균형을 찾는 것이 중요할 것입니다.

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원문 링크: https://stocktwits.com/news-articles/markets/equity/tokenmaxxing-fading-what-it-means-for-nvidia-openai-anthropic/cZ0gpBnReHL?.tsrc=rss

‘Tokenmaxxing’ Is Fading, Say Experts: What It Means For Nvidia, OpenAI, Anthropic And The AI Boom

The term “tokenmaxxing” refers to companies encouraging their employees to use AI tools aggressively, with some firms reportedly tracking token consumption as a proxy for innovation and productivity.The practice fell victim to Goodhart's Law, where a metric loses its value once it becomes a target.AI researcher Gary Marcus argued that the decline of “tokenmaxxing” could expose broader weaknesses in the economics of large language models.A growing number of industry experts and analysts believe the era of “tokenmaxxing” may be fading, as companies increasingly scrutinize the return on investment of AI tools and large language models.The shift comes amid reports of companies scaling back the push for AI usage while burning through their annual budgets for the technology within months.What Is ‘Tokenmaxxing’?The term “tokenmaxxing” refers to companies encouraging their employees to use AI tools aggressively, with some firms reportedly tracking token consumption as a proxy for innovation and productivity.The practice fell victim to Goodhart's Law, where a metric loses its value once it becomes a target.Amazon.com Inc. (AMZN) employees generated unnecessary AI workloads simply to boost usage statistics rather than produce meaningful business outcomes, according to a report by The Financial Times. Amazon eventually shut down its AI leadership board.Why Experts Are ConcernedAI researcher Gary Marcus argued in a post on X that the decline of “tokenmaxxing” could expose broader weaknesses in the economics of large language models.Marcus suggested that OpenAI and Anthropic could face increasing pressure as AI models become more commoditized, competition intensifies, and profit margins shrink.“Most of the companies that invested massively in them will struggle to make back their investments,” he said, while adding that Nvidia Corp. (NVDA) will eventually decline, once the market widely recognizes the other effects of falling “tokenmaxxing.”Meanwhile, technology strategist Thierry Borgeat cited estimates suggesting that several hyperscalers may incur negative returns on AI-related capital expenditures under current assumptions, prompting comparisons to the dot-com era.“And remember: that's assuming zero costs. In reality, GPUs depreciate, power bills run, salaries get paid. The real returns are worse,” he said.Borgeat added that this is why the comparison to the dot-com bubble keeps coming up. “Incredible technology does not automatically mean sustainable economics. The internet survived. Most internet companies didn't,” he said.Ride-hailing platform Uber Technologies Inc. (UBER) confirmed last month that it had burned through its AI budget for 2026 in just four months, according to a report by The Information.Why This Matters For Nvidia, OpenAI And AnthropicFor Nvidia, the debate is significant because the chipmaker remains one of the largest beneficiaries of AI infrastructure spending.If enterprises shift from maximizing AI usage to optimizing AI costs, growth in token consumption could slow, potentially tempering demand growth for inference infrastructure sold by Nvidia and other AI hardware providers.Nvidia CEO Jensen Huang has been touting the current phase of AI as an agentic one. “I said, (it’s) completely opposite. And you can see it. (AI) agents is the going to create the largest opportunity for my partner companies,” he said at the ongoing Computex conference.IO Fund’s Beth Kindig stated in a note in March this year that Nvidia’s $20 billion acquisition of Groq is aimed at driving up token usage, which would boost the company’s revenue and profits.“Nvidia is preparing to position its GPUs to be among the best inference options available, utilizing Groq’s unique SRAM-based architecture to significantly turbocharge token throughput and accelerate inference performance,” she added.Cost Another Major Concern For Model Providers As Well As UsersFor OpenAI and Anthropic, growing pressure to control costs could lead enterprises to rely more heavily on cheaper models, smaller models or routing systems that reserve premium models for only the most complex tasks.According to pricing data compiled by Artificial Analysis, some of Anthropic's flagship Claude models rank among the most expensive frontier AI offerings, while OpenAI’s ChatGPT, Google’s Gemini, xAI’s Grok, and DeepSeek are among the more affordable models.This comes amid reports that Microsoft Corp. (MSFT) has begun canceling Claude Code licenses for its employees, instead turning to its in-house GitHub Copilot Command-Line Interface (CLI).In another hit to its users, Microsoft-owned GitHub announced today, June 1, 2026, that it is transitioning to usage-based billing.Copilot has changed significantly over the past year, evolving from an in-editor coding assistant into an agentic platform capable of handling extended, multi-step development tasks, the firm stated.It added that Copilot can leverage the latest AI models, work across entire code repositories, and independently iterate on complex workflows, resulting in substantially higher compute and inference requirements.The Invesco QQQ Trust (QQQ) is up 42% over the past 12 months, while the iShares U.S. Technology ETF (IYW) is up 59%.Also See: NVDA, AMD, MU, MSFT, ORCL: Dan Ives Lists Stocks In His Shopping Bag Amid Ongoing Memory SupercycleFor updates and corrections, email newsroom[at]stocktwits[dot]com.

Source: https://stocktwits.com/news-articles/markets/equity/tokenmaxxing-fading-what-it-means-for-nvidia-openai-anthropic/cZ0gpBnReHL?.tsrc=rss