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Bitcoin-Tech Stock Correlation Is Overblown, NYDIG

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Bitcoin’s recent price action has traced the footsteps of US software equities, driven more by macro liquidity conditions than a lasting structural link to the tech sector. In a note issued on Friday, Greg Cipolaro, NYDIG’s head of research, argued that the visual fit between BTC and software stocks is compelling but not evidence of convergence in their underlying drivers. He cautioned that the current rally reflects shared exposure to the ongoing macro regime—namely long-duration, liquidity-sensitive risk assets—rather than a genuine alignment of Bitcoin with AI or quantum-risk themes. The backdrop remains one of ongoing volatility as traders weigh risk-on sentiment against regulatory and on-chain dynamics.

Over the past week, Bitcoin rallied alongside US software equities, inviting readers to question whether the cryptocurrency is morphing into a proxy for the sector. Cipolaro’s assessment centers on the idea that correlation does not equal causation, and that the observed co-movement is more plausibly a function of broad liquidity conditions rather than a structural re-pricing of digital assets in relation to software equities.

“While the visual fit of their indexed price is compelling, the conclusion that Bitcoin and software equities have structurally converged, or that they share common exposure to themes such as AI or quantum risk, is overstated,” Cipolaro wrote in the note. He added that the tandem rally is better explained by the macro regime’s influence on long-duration, liquidity-sensitive assets rather than an intrinsic linkage between BTC and software stocks.

Bitcoin’s price is “unexplained by equities”

Bitcoin’s correlation with software stocks has risen on a 90-day rolling basis since its all-time high above $126,000 in early October, but Cipolaro noted that its correlations with the S&P 500 and Nasdaq have also increased, suggesting that the shift is not unique to software equities. Even with such correlations in place, he argued that the majority of BTC’s price movement remains unexplained by traditional stock indices. Statistically, only about a quarter of Bitcoin’s price movements are tied to stock-market correlations, while roughly 75% are driven by factors outside the realm of equities.

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He remarked that Bitcoin is not currently priced as a hedge against macroeconomic conditions, which helps explain the persistent frustration among observers that it has not fulfilled the “digital gold” narrative. Traders appear to be allocating across assets along a risk curve rather than purchasing BTC for a standalone monetary thesis. This nuance underscores how Bitcoin can diverge from gold-like behavior even as it remains subject to idiosyncratic forces.

In exploring the asymmetry between macro-driven moves and Bitcoin’s intrinsic drivers, Cipolaro pointed to Bitcoin’s on-chain activity, adoption trends, and the evolving regulatory landscape as evidence of its distinct market structure. While cross-asset correlations with equities can rise during risk-on periods, they do not dictate Bitcoin’s long-term returns. The unfolding dynamic, he suggested, reinforces Bitcoin’s role as a portfolio diversifier rather than a pure play on macro liquidity or AI narratives.

For context, a related observation has circulated in crypto media, linking Bitcoin’s price action to energy and geopolitical concerns that influence risk appetite. The broader takeaway is that BTC’s behavior sits at the intersection of macro liquidity, on-chain fundamentals, and policy developments—each contributing to its price path in different weights at different times.

Nevertheless, Cipolaro cautioned that Bitcoin’s market structure remains distinct. He cited network activity, adoption trends, and policy momentum as critical differentiators that can sustain Bitcoin as a unique financial asset even when correlations to software equities rise. The conclusion is not that Bitcoin has become a stock proxy; rather, the current co-movement reflects an overarching liquidity regime in which many asset classes move together, even as Bitcoin maintains its own, idiosyncratic underpinnings.

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In sum, the market appears to be pricing BTC within a broader risk-on market framework rather than as a discrete monetary instrument. The differentiated drivers—on-chain activity, adoption, regulatory signals—remain the backbone of Bitcoin’s case as a diversifier, even as short-term correlations with equities ebb and flow.

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Crypto World

AI Use in Workplaces Causing ‘Brain Fry,’ Say Researchers

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AI Use in Workplaces Causing ‘Brain Fry,’ Say Researchers

The excessive use and oversight of artificial intelligence in the workplace is giving workers “AI brain fry,” contrary to the technology’s assurance that it would ease job pressures.

Workers who are using AI tools report that the technology is “intensifying rather than simplifying work,” researchers from Boston Consulting Group and the University of California wrote in the Harvard Business Review on Friday.

A study of nearly 1,500 full-time US workers found 14% said they had experienced “mental fatigue that results from excessive use of, interaction with, and/or oversight of AI tools beyond one’s cognitive capacity,” or what the researchers called “AI brain fry.”

Respondents described having a “mental hangover” with a “fog” or “buzzing” and an inability to think clearly, along with headaches, slower decision-making, and difficulty focusing.

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Marketing and HR workers reported the highest levels of AI-induced “brain fry.” Source: Harvard Business Review

AI companies have pushed their products as a productivity booster, allowing workers to offload some or part of their workloads, a message that some companies have taken on and started to measure AI use as a performance metric.

Crypto exchange Coinbase CEO Brian Armstrong has said he fired engineers who didn’t want to use AI, and set a goal late last year to have AI generate half of the platform’s code.

“As enterprises use more multi-agent systems, employees find themselves toggling between more tools,” the researchers wrote. “Contrary to the promise of having more time to focus on meaningful work, juggling and multitasking can become the definitive features of working with AI.”

AI carries “significant costs,” but can improve burnout

The researchers said this AI-induced mental strain “carries significant costs in the form of increased employee errors, decision fatigue, and intention to quit.”

Study respondents who said they had brain fry experienced 33% more decision fatigue compared to those who didn’t, which researchers said could cost large companies millions of dollars a year. Those with AI brain fry were also around 40% more likely to have an active intent to quit.

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Those reporting AI brain fry also self-reported making nearly 40% more major errors than those who did not, with a major error defined as one with “serious consequences, such as those that could affect safety, outcomes, or important decisions.” 

The researchers found, however, that the use of AI to replace repetitive and routine tasks decreased burnout, a state of chronic workplace stress that leads to negative feelings about the job and decreased effectiveness.

Related: Anthropic reopens Pentagon talks as tech groups push Trump to drop risk tag

Respondents who used AI to reduce time spent on routine and repetitive tasks reported their levels of burnout were 15% lower than those who didn’t use AI in such a way.

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The researchers said company leaders looking to reduce AI brain fry should “clearly define AI’s purpose in the organization” and explain how workloads will change with the tool.