A recent study reveals that big tech companies like Amazon, Google, and Microsoft have generated more carbon emissions since 2019 than all Bitcoin mining operations combined. This finding challenges the narrative that Bitcoin is a major contributor to climate change. While Bitcoin's energy consumption has been a subject of debate, the study highlights that the rapid growth of artificial intelligence (AI) products and services, particularly in cloud computing and data centers, has significantly increased the carbon footprint of big tech.  Amazon, alone, emitted more carbon dioxide in 2021 than the estimated annual emissions of Bitcoin mining. When combined with Google and Microsoft's emissions, the total surpasses 100 million tons per year. This stark comparison suggests that the environmental impact of big tech, driven by AI advancements, is far greater than that of Bitcoin.  However, it's important to note that direct comparisons between company-reported emissions and Bitcoin's estimated emissions are not scientifically rigorous. Further research is needed to fully understand the carbon footprint of both sectors and develop sustainable solutions.

Bitcoin's carbon footprint is estimated to be much smaller than that of Amazon's alone, with other big tech firms increasing their carbon footprint by as much as 50% since 2019 due to the onset of the general artificial intelligence era. 

Big Tech's Carbon Footprint Dwarfs Bitcoin's: AI's Rise Outpaces Crypto's Energy Use

**Meta stock (META) tumbled 11% this week** after the company missed earnings and confirmed it would spend even more on artificial intelligence data centers. The tech giant now expects about $71 billion in capital expenditures, up from $69 billion, and warned that 2026 will be an even heavier year for spending. That guidance sent a clear signal that the **AI arms race is still far from cooling off**.

For investors, the message was unsettling. **Meta’s spending spree is swallowing more of its cash flow**, with no promise that the return on those investments will arrive soon. The company’s commitment to expansion may strengthen its long-term AI position, but it also deepens short-term balance-sheet pressure and tests shareholder patience.

## Big Tech Turns Toward Heavy Spending

The world’s largest tech firms once bragged about being "capital-light." This story is over. Companies like Meta, Amazon (AMZN), and Microsoft (MSFT) are now funding massive physical infrastructure, from data centers to custom chips, to train and deploy AI models. As Doug Kass of Seabreeze Partners notes, the hyperscalers have transformed from asset-lean platforms into capital-intensive builders.

That shift means tech companies are behaving more like industrial firms. They are laying foundations, buying land, and raising debt. The promise of AI revenue may be huge, but it now carries real financing risk if demand cools or returns take longer than expected.

## Meta Taps the Bond Market to Keep Building

To support its expansion, Meta launched the year’s largest investment-grade corporate bond deal, raising about $30 billion. Investor appetite was enormous, with more than $120 billion in orders for the debt, according to multiple reports. The sale reflects the credit market’s strong faith in tech’s ability to pay back, even as spending surges.

Meta is not alone. Bank of America estimates about $75 billion in AI-linked debt has been issued in just two months. Cheap credit has made it easy for Big Tech to finance growth, but it also increases exposure to higher interest costs if the credit cycle tightens.

## Analysts Warn That Cash Flow Is Getting Tight

Analysts at Bank of America (BAC) expect AI capital expenditures for the biggest tech firms to reach nearly 94% of operating cash flow next year, up sharply from 76% in 2024. This leaves little room for dividends or buybacks, forcing boards to choose between rewarding shareholders or funding expansion.

Companies could slow their buybacks or issue equity, but debt remains the preferred option. At the moment, investors are happy to lend. If markets shift or growth slows, that confidence could evaporate fast, leaving even the strongest tech giants scrambling to balance their ambitions with financial reality.

## Is META a Good Stock to Buy?

Despite the selloff, Wall Street’s conviction in Meta remains strong. Out of 42 analysts tracked in the past three months, 33 rate the stock a Buy, eight recommend a Hold, and only one says to Sell. The average 12-month META price target sits at $847, implying more than 30% upside from the recent price.

![META Analyst Ratings](https://blog.tipranks.com/wp-content/uploads/2025/11/Screenshot-2025-11-03-at-13-1024x337.png)

![META Price Forecast](https://blog.tipranks.com/wp-content/uploads/2025/11/Screenshot-2025-11-03-at-13-1-1024x256.png)

Meta stock ($META) tumbled 11% this week after the company missed earnings and confirmed it would spend even more on artificial intelligence data centers. The tech ...

Meta's AI Spending Spree Sparks Cash Crunch Fears: Is Big Tech's Debt-Fueled Growth Sustainable?

## Market Selloff Intensifies as Profit-Taking Takes Hold

Major cryptocurrencies, including **Bitcoin**, **Dogecoin**, and **Cardano**, slid up to 5% to start the week, extending a dismal run that made October the worst month for the market since 2015. Bitcoin hovered near $106,000 after briefly reclaiming $110,000 last week, while Dogecoin and Cardano's ADA led losses with 5% declines. Other tokens like Solana's SOL, BNB, and Ether also dropped up to 4%, with Tron's TRX remaining flat over 24 hours.

## Profit-Taking and Waning Momentum Drive Declines

The drawdown lacked immediate catalysts, pointing to **profit-taking** after recent price gains. Analysts noted that without new fundamental support, the market is leaning on technicals. Alex Kuptsikevich, chief market analyst at FxPro, highlighted Bitcoin's repeated failure to hold above $113,000 as a sign of **waning momentum**, with the market tracing lower highs. Despite this, the $3.5 trillion total market cap zone has attracted dip-buyers, and the start of a new month could offer a boost, though the historically positive 'Uptober' effect faded quickly.

## Long-Term Investors Increase Sales

Data from Glassnode shows that **bitcoin selling by long-term investors has tripled since June**, as those who bought near $93,000 take profits. However, spot trading volume in October topped $300 billion, the highest in a year, indicating strong two-way liquidity.

## Gold Pulls Back Amid Policy Shifts

Gold steadied around $4,000 per ounce after an early slide triggered by **China's decision to end tax rebates** for certain gold retailers. This policy shift could dent demand in one of the world's largest bullion markets, removing value-added tax offsets for sales from Shanghai exchanges. Gold's record rally in October, driven by retail frenzy and central bank accumulation, had already begun to fade, but prices remain over 50% higher year-to-date, reflecting persistent haven demand.

## Strengthening Correlation Between Bitcoin and Gold

The correlation between **bitcoin and gold** has strengthened in recent months, with both assets responding to shifts in monetary policy and geopolitical stress. The Fed's pause on tightening and prospects for cheaper capital might eventually revive risk asset demand, but traders are currently balancing safety and speculation.

Meanwhile, bitcoin selling by long-term investors has tripled since June, as buyers who entered near $93,000 take profits.

Bitcoin and Major Altcoins Plunge 5% as Long-Term Holders Cash In: What's Next for the Market?

## The Human Factor in Quantum Threats

**Bitcoin's quantum reckoning may still be years away, but the fear has already arrived.** Breakthroughs from Google, Caltech, and IBM have reignited debate over a looming "Q-Day"—the moment when a quantum computer could shatter the cryptography securing Bitcoin and decentralized finance.

Yet experts warn that the real danger may come first from people—not equations—with panic, premature market reactions, and slow developer preparation potentially shaking confidence long before any code actually fails.

## Fear Moves Faster Than Math

In crypto, **panic spreads faster than reason**. The market may run on code, but emotion still moves the price.

Yoon Auh, founder of post-quantum cryptography company BOLTS Technologies, warned that even one mistaken claim about quantum computers breaking Bitcoin could set off a chain reaction, pointing to a recent flash crash in the market last month.

"Crypto had a little flash crash," Auh told Decrypt. "A $50 to $100 million sell-off—basically nothing in traditional markets—triggered massive losses across blockchain assets. That shows how fragile the system still is."

Earlier this month, a single post from President Donald Trump threatening 100% tariffs on Chinese imports triggered the largest single-day crypto wipeout in history, erasing $19 billion in liquidations as Bitcoin briefly plunged below $102,000.

Auh said the same dynamic could unfold after a quantum scare: "Imagine hearing someone say, 'Elliptic-curve cryptography can be broken now, maybe not instantly, but soon.' Everyone would rush for the exit. The system would trip over itself."

The industry has seen it before. In 2017, a false 4Chan post claiming Ethereum founder Vitalik Buterin had died erased billions in market value before traders realized it was fake. The sell-off showed how quickly trust can collapse when information outruns verification.

## The Quantum Timeline: You Are Here

Quantum computers operate on principles that differ from anything in classical computing. Instead of bits that are either 0 or 1, qubits can exist in multiple states at once. When qubits become linked—a property called entanglement—they can process many possibilities simultaneously. That property makes certain kinds of math, like factoring and discrete logarithms, exponentially more efficient to solve.

In 1994, mathematician Peter Shor proved that a sufficiently powerful quantum computer could, in theory, break the encryption securing everything from credit cards to Bitcoin wallets. Bitcoin relies on **elliptic-curve cryptography (ECC)**, which turns private keys into public ones through equations that are easy to compute, but practically impossible to reverse.

A large-enough quantum computer could run Shor's algorithm to invert that math, revealing the private key behind any exposed public key on the blockchain.

Bitcoin's specific system, known as secp256k1, uses these elliptic-curve equations to generate and verify signatures. A quantum computer powerful enough to perform these calculations could recover private keys and empty wallets associated with visible public keys. A 256-bit elliptic-curve key provides roughly the same classical security as a 3,072-bit RSA key—extremely strong by today's standards.

For now, that danger remains theoretical. The world's largest quantum processors—IBM's Condor with 1,121 qubits and Caltech's neutral-atom array exceeding 6,000 qubits—are far from the millions of physical qubits needed to produce even a few thousand logical qubits for fault-tolerant computation.

Current research suggests that around **2,000 to 3,000 logical qubits** would be required to break Bitcoin's elliptic-curve encryption with Shor's algorithm. Reaching that level will likely take another decade or more, though optimistic projections by IBM and Google place such machines in the early to mid-2030s.

"The quantum threat to cryptography is real and serious," Edward Parker, a physicist at the RAND Corporation, told Decrypt. "Some people think quantum computers will never threaten encryption, and that might be true. But there's enough risk that we need to prepare well ahead of time."

That measured caution often gets twisted online, and warnings meant to spark discussion and preparation instead fuel a wave of alarmism, and exaggerated 'quantum apocalypse' rhetoric.

The U.S. government is already moving in that direction. A 2022 presidential directive, National Security Memorandum 10, ordered federal agencies to begin upgrading to post-quantum encryption—a rare case of long-term coordination across departments. Parker pointed to research in 2023 led by cryptographer Michele Mosca that put the median estimate for a cryptographically relevant quantum computer around 2037.

Research scientist Ian MacCormack agreed that public fear has run ahead of what the technology can actually do.

"Quantum computers are nowhere near powerful enough to break RSA-2048 or any encryption of meaningful size," he said. "Getting the error rates down and combining thousands of qubits to do something practical will take time, money, and trial and error."

MacCormack said the mystique of quantum computing, however, often amplifies fear.

"People hear about quantum computing and it sounds god-like or incomprehensible," he said. "But regardless of its potential, it's just an incredibly difficult engineering problem. Developing quantum-resistant encryption will almost certainly happen faster than building a quantum computer capable of breaking current encryption."

Coin Metrics co-founder and Castle Island Ventures Partner Nic Carter recently called quantum computing "the biggest risk to Bitcoin." In his essay "Bitcoin and the Quantum Problem," he notes that nearly a quarter of all Bitcoin—about 4 million coins—already sits in addresses that have exposed public keys. Those are theoretically vulnerable once practical quantum decryption arrives. Confidence in Bitcoin's unbreakable math could fracture long before the math itself does.

## Making Bitcoin Quantum-Resistant

Even though the threat is distant, experts say the time to act is now—but it depends on broad coordination.

Rebecca Krauthamer, co-founder and CEO of post-quantum cybersecurity company QuSecure, said the next step is clear: elliptic-curve cryptography has to go.

"You'd need to replace that with one of the post-quantum standardized algorithms like ML-DSA," she told Decrypt.

ML-DSA, short for Module Lattice-Based Digital Signature Algorithm, is a new post-quantum cryptography standard developed by the U.S. National Institute of Standards and Technology (NIST). It's built on lattice-based math, a branch of cryptography that hides information within multidimensional grids of numbers.

Cracking those grids would require solving what's known as the "Learning With Errors" problem—an equation so complex that even a powerful quantum computer can't untangle it efficiently. That makes ML-DSA far more resistant to decryption than the elliptic-curve systems used in Bitcoin today.

Only a few blockchains today are truly quantum-resistant, while most are still adapting to post-quantum cryptography.

Quantum Resistant Ledger (QRL) was built for quantum safety, using the XMSS hash-based signature scheme standardized by NIST. Cellframe and Algorand use lattice-based algorithms from the NIST suite—Crystals-Dilithium, FALCON, and NTRU—allowing flexible, modular upgrades as standards evolve. IOTA relies on Winternitz one-time signatures in its "Tangle" network, protecting transactions from quantum key recovery. Nervos Network combines classical and lattice-based systems in a hybrid model that enables gradual migration to post-quantum security.

Major chains such as Bitcoin, Ethereum, Cardano, and Solana remain in transition. Ethereum's 3.0 roadmap includes active research and testnets for post‑quantum signatures, while Bitcoin's modular Taproot and Schnorr upgrades provide the groundwork for integrating future quantum‑safe cryptography.

That kind of upgrade is feasible, but politically complex. Bitcoin's security model relies on network-wide consensus among miners, developers, and node operators. Any cryptographic change would require a fork, and that process takes years of discussion and testing.

"Quantum computing can sound abstract," Krauthamer said. "But the fix is surprisingly straightforward. We already have the math. Governments are mandating quantum-safe standards, and finance will follow. The hard part is making people care before it's urgent."

Most experts say the safest path is gradual: add post-quantum support now through new address types or hybrid signatures, get custodians and wallets to use them for new funds, and slowly migrate older wallets. That prevents the chaos of everyone rotating keys at once—a scenario that could damage confidence faster than any real quantum attack.

Bitcoin contributors have already explored post-quantum signatures and hybrid schemes in developer forums. The challenge isn't finding algorithms; it's deciding when and how to deploy them.

## The Governance Problem

Scott Aaronson, a computer science professor at the University of Texas at Austin, said Bitcoin's decentralized model makes upgrades difficult.

"With Ethereum and most other chains, someone can decide to migrate to quantum-resistant crypto when it becomes urgent," he told Decrypt. "With Bitcoin, you'd need a majority of miners to agree to a fork. And something like $100 billion worth of early coins are still protected only by ECC."

That lack of central authority could slow adoption. A split or rushed rollout might fracture the network. Still, many Bitcoin developers argue that once a viable upgrade path exists, consensus will form around working code.

Ethereum and Solana have more flexible governance and could adapt faster. Bitcoin's caution has protected it from bad ideas, but that same conservatism makes big changes hard to implement.

## How Close Is Q-Day?

A quantum computer powerful enough to break Bitcoin's encryption doesn't exist yet. Current prototypes count qubits in the thousands, but not the millions of error-corrected qubits required for stable, scalable attacks.

Late last month, Google announced a new milestone in its quantum research: Its 105-qubit "Willow" processor completed a physics simulation in just over two hours that would take the Frontier supercomputer more than three years to reproduce. The experiment used 65 active qubits across 23 circuit layers, and achieved median two-qubit gate errors near 0.0015. The result marked a verifiable quantum speed-up but posed no threat to encryption—progress, not peril.

Even researchers who view quantum computing as a long-term threat say the real danger is still years away.

"I think quantum computation has a reasonable probability—say, more than five percent—of being a major, even existential, long-term risk to Bitcoin and other cryptocurrencies," Christopher Peikert, a professor of computer science and engineering at the University of Michigan, told Decrypt. "However, it doesn't appear to be a real risk in the next few years. Quantum-computing technology and engineering still have too far to go before they can threaten modern cryptography."

The harder part, Peikert added, will be performance once post-quantum systems are deployed. "Post-quantum signatures use much larger keys," he said. "Since cryptocurrencies rely on many signatures for transactions and blocks, switching to post-quantum or hybrid signatures would significantly increase network traffic and block sizes."

As for near-term protection, Peikert said the best mitigation is behavioral, not technological.

"In the short term, one should avoid revealing public keys on a public network until absolutely necessary, and give those keys short lifetimes," he said. "Longer-term, core protocols should be carefully updated to incorporate post-quantum cryptography for the most important functionalities and assets."

Experts say the real danger to Bitcoin isn’t quantum machines—it’s human panic and slow preparation.

Quantum Panic: The Real Threat to Bitcoin That Could Crash Crypto Before Quantum Computers Even Arrive

Although the **cryptocurrency market** is cooling down, with most assets in a state of uncertainty, a trader boasting a **100% win rate** has once again gone long on **Bitcoin (BTC)**, **Ethereum (ETH)**, and **Solana (SOL)**.

Specifically, the trader currently holds 39,000 ETH worth $151 million at an average entry of $3,845.33, 1,070 BTC valued at $118 million at $110,114.10, and 569,050 SOL worth $105 million at $198.23, according to the latest on-chain [data](https://x.com/lookonchain/status/1984835387446214692) retrieved from *Lookonchain* by Finbold on November 2.

![Crypto trader’s long position](https://assets.finbold.com/uploads/2025/11/image-13-1024x483.png)
*Crypto trader’s long position. Source: Lookonchain*

He has also placed limit orders to add 40,000 SOL about $7.36 million to his long position at $184, showing confidence in **Solana’s potential rebound** despite recent volatility.

This move follows his previous set of [trades](https://x.com/lookonchain/status/1983713294704898200) on October 30, when he also went long on the same three assets, holding 1,039 BTC worth $114 million, 560,840 SOL valued at $109 million, and 13,419 ETH worth $52.66 million.

Interestingly, over an 18-day period, the trader completed **14 trades with a 100% win rate**, realizing more than $16 million in profit.

With the trader going long again, it appears he’s betting on a **market rebound**, signaling strong confidence in a potential rally.

## Bitcoin Fails to Make Major Moves

Notably, the market, led by Bitcoin, briefly rebounded after suffering steep losses earlier in the week, stabilizing around the $110,000 level as both bulls and bears showed little conviction to push prices decisively either way.

As of press time, Bitcoin was trading at $110,734, up about 0.5% in the past 24 hours, while Ethereum was at $3,872, down less than 0.1% over the same period.

Notably, the **bearish sentiment** follows Bitcoin’s first monthly loss since 2018, ending a seven-year streak that once made October a “lucky” month for crypto traders.

The broader market also mirrored declines in gold and equities, retreating from record highs amid rising **investor uncertainty**. The sell-off intensified after U.S. President Donald Trump imposed a 100% tariff on Chinese imports and hinted at export restrictions on key software, triggering the **largest crypto liquidation on record**. Despite easing trade tensions, the market has shown little sign of recovery.

Prices remain partly weighed down as institutional investors stay cautious, with **exchange-traded funds (ETFs)** witnessing notable outflows in the past week. A resumption of inflows could, however, trigger renewed **bullish sentiment**.

*Featured image via Shutterstock*

Although the crypto market is cooling down, with most assets in a state of uncertainty, a trader with a 100% win rate has once again gone long

Big Tech's Carbon Footprint Dwarfs Bitcoin's: AI's Rise Outpaces Crypto's Energy Use

Summary:

Big tech companies like Amazon, Google, and Microsoft have emitted more carbon since 2019 than all Bitcoin mining operations.

Amazon's carbon footprint in 2021 exceeded the estimated annual emissions of Bitcoin mining.

The rapid growth of artificial intelligence (AI) products and services, particularly in cloud computing and data centers, has significantly increased big tech's carbon footprint.

Direct comparisons between company-reported emissions and Bitcoin's estimated emissions are not scientifically rigorous.

Further research is needed to understand the carbon footprint of both sectors and develop sustainable solutions.

Comments

Join Our Community

BitcoinToday.app

Other Latest News

Meta's AI Spending Spree Sparks Cash Crunch Fears: Is Big Tech's Debt-Fueled Growth Sustainable?

Bitcoin and Major Altcoins Plunge 5% as Long-Term Holders Cash In: What's Next for the Market?

Quantum Panic: The Real Threat to Bitcoin That Could Crash Crypto Before Quantum Computers Even Arrive

Trader with 100% Win Rate Bets Big on Bitcoin, Ethereum, and Solana Amid Market Uncertainty

Other Latest News

Meta's AI Spending Spree Sparks Cash Crunch Fears: Is Big Tech's Debt-Fueled Growth Sustainable?

Bitcoin and Major Altcoins Plunge 5% as Long-Term Holders Cash In: What's Next for the Market?

Quantum Panic: The Real Threat to Bitcoin That Could Crash Crypto Before Quantum Computers Even Arrive

Trader with 100% Win Rate Bets Big on Bitcoin, Ethereum, and Solana Amid Market Uncertainty