Why Are People Scared That Quantum Will Kill Crypto?
Original Title: Quantum Isn't a Threat to Web3. It's an Upgrade.
Original Author: DAVID ATTERMANN
Translation: Peggy, BlockBeats
Editor's Note: The discussion surrounding "Will Quantum Destroy Web3" often overlooks the true direction of change. This article points out that quantum is not a threat but a migration of security infrastructure: robust cryptography, tamper-evident communication, physical randomness, and identity proofs are gradually sinking to the foundational capabilities. In this process, blockchain no longer needs to repetitively "compensate" for an untrusted network environment at the software layer but can focus more on irreducible issues such as governance, incentives, and cross-domain collaboration.
More importantly, the advent of quantum coincides with the realization of autonomous AI systems, where security becomes infrastructure, enabling Web3 to truly enter a mature stage of serving "autonomy, commitment, and coordination."
The following is the original text:
The mainstream debate surrounding "Will quantum computing kill Web3" actually misses the point. Such framing is inherently inverted. Quantum computing will not make digital systems less secure; instead, it will further embed security into the lower layers of infrastructure. As new cryptographic standards take root and novel secure communication methods become feasible, fundamental security capabilities will become more cost-effective and standardized across the entire internet.
Simultaneously, AI systems are transitioning from "thinking" to "acting." When intelligent assistants can do more than just answer questions but can book flights, transfer funds, and manage resources, the real challenge shifts. It is no longer a question of whether AI can generate good answers, but whether software can securely take action across disparate systems and organizations that do not trust each other. Proving what AI has done, where the data came from, and what it is allowed to do is becoming the most crucial constraint.

This is precisely the same fracture line that prevents all current JARVIS-like visions from materializing. The true bottleneck lies not in intelligence but in trust. An assistant that still requires human approval when spending money, accessing sensitive data, or allocating resources cannot truly be autonomous. Once real authorization is involved, if there is no machine-verifiable, shared way to prove identity, permissions, and compliance, the so-called "autonomy" immediately fails.
Quantum computing, at this moment when trust and collaboration issues become unavoidable, reduces the cost of security.
1. How Quantum Actually Changed Things (and What It Didn't)
When people talk about "quantum," they are usually referring to quantum computers. These are not "faster GPUs," but a class of specialized machines that leverage quantum mechanical properties to far outperform classical computers on certain specific problems.
What they excel at includes: factoring large numbers, solving discrete logarithm problems, certain specific optimization and simulation problems.
What they do not excel at includes: general computing, running large software systems, replacing cloud computing infrastructure, training AI models.

So, what exactly will quantum computing break?
The answer is: a part of today's public-key cryptography. RSA and Elliptic Curve Cryptography (ECC) are built on the type of mathematical problems that quantum computers are best at solving. This is crucial because cryptography is not only a fundamental primitive of blockchain, it is the trust foundation of the entire Internet—login mechanisms, digital certificates, signatures, key exchanges, identity systems, are all reliant on it.
The real uncertainty lies in the timeline, not the direction. Most credible estimates suggest that a quantum computer with "cryptographically significant" capabilities is still 10–20 years away, but no one can completely rule out faster progress or some kind of "leap" breakthrough.
Most Immediate Near-Term Risk: Harvest Now, Decrypt Later (HNDL)
The most quantum-related immediate risk is not a sudden collapse of the global security system one day, but what's known as HNDL (Harvest Now, Decrypt Later).
Attackers could very well mass collect encrypted communications and data today, only to decrypt this historical data when future quantum computing capabilities mature.
This pattern would pose long-term exposure risks to: government and defense communications, corporate intellectual property and trade secrets, medical data and personal privacy records, legal and financial archives.
It is for this reason that Post-Quantum Cryptography is being taken seriously right now by national governments, cloud service providers, and regulated industries. Data transmitted today often needs to remain confidential for decades; once you assume that the "future will definitely be decryptable," then the existing security guarantees are actually invalidated.
This Is a Security Migration, Not a Systemic Collapse
Post-Quantum Cryptography does not require quantum hardware. It is essentially a software and protocol-level upgrade that covers TLS, VPN, wallets, identity systems, and signature schemes. This will not happen on a single "switch-over day," but rather will be a slow, uneven infrastructure migration process, similar to IPv6 — unavoidable but gradual.
This change will have a much greater impact on enterprise and national-level infrastructure than on the blockchain itself. Blockchain is inherently a public system, where the core secret that truly needs protection is the private key, not the historical transaction data. For Web3, quantum computing brings not a survival crisis, but a cryptographic upgrade path issue, rather than a total system overhaul.
This shift has already emerged in the mainstream ecosystem. The Ethereum Foundation recently elevated post-quantum security to a core protocol-level priority, initiating specialized research and test environments around post-quantum signatures, the account model, and transaction mechanisms. This signifies that risk awareness has shifted from a "someday in the future issue" to an "ongoing infrastructure migration," even though true large-scale quantum hardware has not yet appeared.
II. The Most Easily Overlooked Change: Alteration at the Network Layer
If quantum computing is concerned with the mathematical foundation for securing keys, then quantum communication is concerned with the trust model of the network itself.
Quantum communication does not mean "transmitting application data through a quantum computer." Although it has multiple implementation forms (which will be explored later), in reality, the most core application is Quantum Key Distribution (QKD): using quantum states to establish a tamper-evident communication channel. The message itself remains classical data, still encrypted; what truly changes is that any silent eavesdropping will be detected at the physical layer.
This is not a faster network but a network trust mechanism that cannot be subversively infiltrated.

Some quantum properties are uncopyable and cannot be observed without causing disturbance. When these properties are used to generate encryption keys or validate communication channels, interception is no longer "silent." Once someone attempts eavesdropping, the observation itself leaves detectable traces.
Why This Will Change System Design
The reason this is important is that a significant portion of Web3's current defense architecture is based on one premise: the network channel is adversarial and invisible.
Traffic can be quietly intercepted; man-in-the-middle attacks are hard to detect; network-layer trust is extremely weak.
Therefore, the upper-layer systems have to "overcompensate" through replication, validation mechanisms, and an economically secure design.
If the infrastructure layer itself embeds protections for channel integrity, quantum communication actually serves to lower the cost of maintaining channel security. This point is often overlooked in the mainstream narrative of the "quantum apocalypse."
Will It Really Scale?
Similar to quantum computing, the widespread adoption of Quantum Key Distribution (QKD) is likely still 10–20 years away. However, the possibility of a sudden timeline compression cannot be ruled out — for example, with breakthroughs in quantum relays, satellite networks, or integrated photonics technology.
III. The Trust Issue of Autonomous Systems
Quantum is driving a security migration across the Internet. Over time, strong cryptosystems and tamper-evident communication channels will become part of the infrastructure, no longer a differentiating capability.
However, what truly makes "collaboration" a core bottleneck is the rise of autonomous AI agents.
Autonomous systems cannot rely on informal trust like humans or institutional shortcuts. By default, they require:
Verifiable execution: Agents cannot be trusted based solely on their claims; there must be proof.
Coordination mechanisms: Multi-agent workflows need a neutral shared state carrier.
Data provenance: Source verification is crucial when synthetic and adversarial data proliferate.
Commitment mechanisms: Agents must be able to make enforceable commitments that other agents can rely on.
While the quantum network cannot directly solve coordination issues, it will commoditize security capabilities at the base layer. As security becomes part of the infrastructure, more coordination can happen off-chain with stronger guarantees. Identity and membership relations will be closer to the underlying network structure. For certain types of workflows, global broadcast replication is no longer necessary. Blockchain is transitioning from a "pure broadcast system" to the coordination backbone of autonomous systems.
IV. Frontier Quantum Primitives
The following content pertains to longer-term possibilities, assuming the quantum network can move beyond niche applications and achieve scalability. Once implemented, they will strengthen underlying security assurances and open up new protocol design space. Similar to QKD, the significance of these primitives is to unlock resources for the "coordination bottleneck."
Some are closer to real-world production environments, while others signal architectural directions for the evolution of future trust mechanisms.
First Layer (0–10 Years)
Physical Unclonable Randomness: Random number generation directly constrained by physical processes, hard to predict or manipulate.
Unclonable Identity with Proof Mechanism: Identity and authentication based on physical characteristics to prevent duplication and forgery.
Second Layer (10+ Years)
Time Synchronization as a First-Class Primitive: Time is no longer just a system parameter but a verifiable foundational capability.
Verifiable State Transfer: Cross-system state changes can be directly proven by underlying mechanisms.
Third Layer (Cutting Edge Research, High Uncertainty)
Entanglement-Based Coordination Primitive: Establishing new coordination structures using quantum entanglement.
Fully Trust-Minimized Cross-Domain Communication Mechanism: Achieving nearly trust-free message passing between different trust domains.
Overall, quantum is not a force that "breaks Web3" but a force that drives the upgrade of security infrastructure. And as security costs decrease, the real bottleneck will no longer be cryptography but how to make autonomous systems reliably collaborate in an untrusted environment.

1. Verifiable State Transfer
From "Software-Enforced Scarcity" to "Physical Unclonability"
In today's blockchain systems, unreplicable ownership is achieved through network-wide consensus. Scarcity is a rule set by the protocol and maintained through replication and consistency among a large number of nodes. The existence of a ledger is largely to ensure that the same state is not replicated or double-spent.
Quantum teleportation introduces a completely different primitive: states can be transferred but cannot be replicated during the transfer and are "consumed" at the moment of transfer. In other words, unclonability no longer relies entirely on software and protocol constraints but becomes a property of the physical underlying layer itself.

Why is this important? How will it change system design?
Hardware-Backed Custodianship: Regulated anonymous instruments, sovereign-grade credentials, or real-world tangible assets, whose control can be bound to unclonable, hardware-proof-capable states.
Asset Anchoring with Lower Trust Assumptions: A mechanism for partially bridging real-world assets that can rely on the physical irreproducibility, without needing to fully depend on committees, multisigs, or pure social trust.
Protocol Simplification: Part of the scarcity guarantee is moved to a lower layer of the stack, reducing the complex logic in the protocol used solely for "anti-duplication."
2. Entanglement as a Trust Primitive
Blockchains coordinate through global replicated state and consensus to resolve conflicts. Cross-chain interactions often rely on heavy validation processes or trusted relays; finality is usually post-hoc, determined by blocks and confirmation.
Quantum entanglement introduces another primitive: achieving shared correlation without a central coordinator. It allows participants to establish consistency or alignment properties at an earlier stage without exposing the underlying data itself.
From this perspective, entanglement is not about "faster consensus" but a mechanism to establish trust constraints at the frontend of the pipeline, opening new design spaces for future cross-system, cross-domain coordination.
Why It's Important and How It Will Change System Design:
Earlier synchronization: Sequencers can establish a consistent view of "ordering commitments" before final settlement.
Cleaner cross-domain alignment: Multiple domains can prove they observed the same event stream without relying on a single relayer.
Reduced overhead in upper-layer reconciliation: Some "alignments" can be established before the need for heavy global adjudication, reducing the additional hardening costs high-level protocols make for adversarial networks.
4. Physically Enforced Randomness
From a gameable randomness beacon to unpredictability endorsed by physics. Randomness underpins validator selection, block producer election, committee sampling, auctions, and various incentive mechanisms. Today's randomness is mostly constructed at the protocol layer, leaving room for manipulation and bias at the edges.
Quantum processes can generate randomness that is unpredictable and unbiased under physical assumptions.

Why It's Important and How It Will Change System Design:
Cleaner committee and proposer selection: Reducing the attack surface for subtle manipulation strategies.
Fairer Sorting and Auctions: Mitigating MEV Extraction with a system less sensitive to transaction ordering.
More Robust Mechanism Design: Incentive mechanisms are harder to game at the "randomness layer."
4. Unclonable Identity and Attestation
From "key equals identity" to "device equals identity." Identity in Web3 today is nearly synonymous with "holding a key." Sybil resistance relies mainly on economic costs or social heuristic rules. Node identities are also mostly loosely anchored at the software layer.
Quantum states are unclonable. When combined with hardware attestation, it becomes possible to achieve unclonable device identity and stronger remote attestation: proving that a message or computation indeed came from a specific physical endpoint.

Why This Is Important and How It Will Change System Design:
Stronger Endpoint Assurance: Messages and execution claims can be bound to a specific physical environment.
Reduced Trust Surface of Relayers and Oracles: Proving ability is closer to hardware rather than relying solely on software identity and claims.
More Reliable Verifiable Computation: Execution traceability becomes harder to forge.
5. Elevating Time Sync to a First-Class Primitive
From "soft clocks" to "protocol-level time." The way blockchain handles time is fundamentally a soft assumption. Slot timing and ordering can be exploited, and even tiny latency advantages can drive MEV. Quantum-secure clock synchronization enables tighter time coordination across long distances.

Why This Is Important and How It Will Change System Design:
Fairer Block Production Windows: Reducing latency asymmetry to limit certain frontrunning strategies.
Cleaner Cross-Chain Settlements: Tighter timeframes reduce race conditions.
More Stable Ordering: Protocol timing becomes less sensitive to network jitter.
6. Minimal Trust Cross-Domain Coordination
From "committees everywhere" to "physically endorsed message passing." Cross-chain security remains one of Web3's biggest operational risks. Bridges rely on committees, multisigs, relayers, and oracles—each adding to the trust surface and potential failure modes.
As both entanglement and tamper-evident channels mature, different domains can increasingly prove they have observed the same set of commitments or event flows with fewer social trust assumptions.
Why this is important and how it will change system design:
Smaller trust set for bridges: With validation closer to the underlying, catastrophic failure modes diminish.
Cleaner cross-domain ordering: No need to rely on centralized operators, making it easier to establish shared ordering.
Security down the stack migration
Today's blockchains simulate scarcity, randomness, identity, ordering, and cross-domain messaging at the software layer because the underlying network and hardware are not inherently trusted. Quantum networks push some aspects of capabilities like authenticity, unclonability, tamper detection, randomness, and synchrony into the infrastructure fabric.
This mirrors past infrastructure evolutions: TLS brought cryptography to the network layer; TEEs brought trust to hardware; secure boot brought boot integrity to the firmware layer.
Blockchain will not become obsolete; it will be "unburdened" from reimplementing every trust primitive in software and will focus more on those problems that cannot be eliminated: governance, incentives, collusion, and adversarial shared state.
Five, Counterarguments, and Real-World Constraints
Even if quantum-secure networks are limited to a few strategic corridors, this alone is enough to reshape the standards and design assumptions across an entire tech stack. Highly trusted communication doesn't have to be "ubiquitous" to affect system construction: as long as a part of the network defaults to providing a tamper-evident channel, the threat model will shift upstream, and fundamental security assumptions will also begin to change more broadly.
In reality, quantum-secure communication remains expensive, fragile, and limited in coverage. Hardware deployment and operation are challenging and seamless integration with existing Internet infrastructure is difficult. For many use cases, relying solely on post-quantum cryptography may already be sufficient, so quantum-safe links are more likely to focus on high-value environments: government networks, financial infrastructure, and critical national systems.
Ultimately, a hybrid trust landscape will emerge: some corridors will have stronger default assurances, while the open Internet remains adversarial.
This uneven deployment will not weaken the architectural shift but will present it in a "skewed" form.
Six, How Systems Will Adapt Over Time
Large infrastructure transitions are rarely "one-and-done." Changes in system design often precede widespread adoption of new technology, especially in the security realm. Once new standards are adopted, early deployments occur, builders will begin to assume a new baseline, even as the deployment of infrastructure remains uneven.
A more realistic evolution path is roughly as follows:
Future 5 Years: Security Capability Commercialization
Post-quantum cryptography will gradually unfold in cloud service providers, enterprises, and regulated industries. "Quantum security" will become part of the default security checklist, no longer a unique selling point. Early quantum-safe network links will appear in high-value scenarios such as finance, government, and critical infrastructure.
Even though these upgrades are not yet widespread, they will begin to shape how systems are built: teams will assume a stronger baseline for the network and the cryptographic layer, shifting more attention to how systems interact, coordinate actions, and enforce rules among untrusted parties.
5–10 Years: Design Assumptions Migration
Once stronger security primitives become the norm, systems will no longer need to be heavily over-engineered for adversarial networks and weak cryptography. The underlying platforms will start integrating integrity, hardware proof, and verification tools — components that were once seen as "advanced features."
At this stage, the changes occur more in "how people think about system design" rather than the infrastructure itself. Builders will begin designing systems for a world where "default security holds," and the real complexity shifts to how systems interact, how permissions are executed, and how cross-border behavior is coordinated.
10+ Years: Infrastructure Catches Up with Design Paradigms
Quantum-safe channels and tamper-evident communication will become more common in major financial hubs, government networks, and critical corridors. By then, most modern systems have been designed under a stronger security assumption, and the infrastructure finally catches up to design patterns that appeared years ago.
Quantum: Driving Autonomy's Next Stage
Viewing quantum as the primary narrative of the Web3 threat is actually the opposite. Quantum is more like an accelerator: it arrives at the same time autonomous AI systems are beginning to enter the real world.
It pushes security primitives into the infrastructure layer. Strong cryptography, tamper-evident channels, and verifiable integrity become cheaper, more standardized, and no longer a differentiating advantage. This reduces the underlying "trust cost," unleashing new design space to build the primitives that AI agents truly need to wield real power: verifiable execution, enforceable permission boundaries, and bindable commitments between systems that do not share trust.
Quantum will not kill Web3; it will force Web3 to mature.
When security becomes infrastructure, what remains are the real challenges — also the initial issues Web3 set out to solve: establishing autonomy, commitment, and coordination in inherently untrusted systems.
You may also like

a16z: Why Do AI Agents Need a Stablecoin for B2B Payments?

February 24th Market Key Intelligence, How Much Did You Miss?

Web4.0, perhaps the most needed narrative for cryptocurrency

Some Key News You Might Have Missed Over the Chinese New Year Holiday

Key Market Information Discrepancy on February 24th - A Must-Read! | Alpha Morning Report

$1,500,000 Salary Job: How to Achieve with $500 AI?

Bitcoin On-Chain User Attrition at 30%, ETF Hemorrhage at $4.5 Billion: What's Next for the Next 3 Months?

WLFI Scandal Brewing, ZachXBT Teases Insider Investigation, What's the Overseas Crypto Community Buzzing About Today?

Debunking the AI Doomsday Myth: Why Establishment Inertia and the Software Wasteland Will Save Us
Editor's Note: Citrini7's cyberpunk-themed AI doomsday prophecy has sparked widespread discussion across the internet. However, this article presents a more pragmatic counter perspective. If Citrini envisions a digital tsunami instantly engulfing civilization, this author sees the resilient resistance of the human bureaucratic system, the profoundly flawed existing software ecosystem, and the long-overlooked cornerstone of heavy industry. This is a frontal clash between Silicon Valley fantasy and the iron law of reality, reminding us that the singularity may come, but it will never happen overnight.
The following is the original content:
Renowned market commentator Citrini7 recently published a captivating and widely circulated AI doomsday novel. While he acknowledges that the probability of some scenes occurring is extremely low, as someone who has witnessed multiple economic collapse prophecies, I want to challenge his views and present a more deterministic and optimistic future.
In 2007, people thought that against the backdrop of "peak oil," the United States' geopolitical status had come to an end; in 2008, they believed the dollar system was on the brink of collapse; in 2014, everyone thought AMD and NVIDIA were done for. Then ChatGPT emerged, and people thought Google was toast... Yet every time, existing institutions with deep-rooted inertia have proven to be far more resilient than onlookers imagined.
When Citrini talks about the fear of institutional turnover and rapid workforce displacement, he writes, "Even in fields we think rely on interpersonal relationships, cracks are showing. Take the real estate industry, where buyers have tolerated 5%-6% commissions for decades due to the information asymmetry between brokers and consumers..."
Seeing this, I couldn't help but chuckle. People have been proclaiming the "death of real estate agents" for 20 years now! This hardly requires any superintelligence; with Zillow, Redfin, or Opendoor, it's enough. But this example precisely proves the opposite of Citrini's view: although this workforce has long been deemed obsolete in the eyes of most, due to market inertia and regulatory capture, real estate agents' vitality is more tenacious than anyone's expectations a decade ago.
A few months ago, I just bought a house. The transaction process mandated that we hire a real estate agent, with lofty justifications. My buyer's agent made about $50,000 in this transaction, while his actual work — filling out forms and coordinating between multiple parties — amounted to no more than 10 hours, something I could have easily handled myself. The market will eventually move towards efficiency, providing fair pricing for labor, but this will be a long process.
I deeply understand the ways of inertia and change management: I once founded and sold a company whose core business was driving insurance brokerages from "manual service" to "software-driven." The iron rule I learned is: human societies in the real world are extremely complex, and things always take longer than you imagine — even when you account for this rule. This doesn't mean that the world won't undergo drastic changes, but rather that change will be more gradual, allowing us time to respond and adapt.
Recently, the software sector has seen a downturn as investors worry about the lack of moats in the backend systems of companies like Monday, Salesforce, Asana, making them easily replicable. Citrini and others believe that AI programming heralds the end of SaaS companies: one, products become homogenized, with zero profits, and two, jobs disappear.
But everyone overlooks one thing: the current state of these software products is simply terrible.
I'm qualified to say this because I've spent hundreds of thousands of dollars on Salesforce and Monday. Indeed, AI can enable competitors to replicate these products, but more importantly, AI can enable competitors to build better products. Stock price declines are not surprising: an industry relying on long-term lock-ins, lacking competitiveness, and filled with low-quality legacy incumbents is finally facing competition again.
From a broader perspective, almost all existing software is garbage, which is an undeniable fact. Every tool I've paid for is riddled with bugs; some software is so bad that I can't even pay for it (I've been unable to use Citibank's online transfer for the past three years); most web apps can't even get mobile and desktop responsiveness right; not a single product can fully deliver what you want. Silicon Valley darlings like Stripe and Linear only garner massive followings because they are not as disgustingly unusable as their competitors. If you ask a seasoned engineer, "Show me a truly perfect piece of software," all you'll get is prolonged silence and blank stares.
Here lies a profound truth: even as we approach a "software singularity," the human demand for software labor is nearly infinite. It's well known that the final few percentage points of perfection often require the most work. By this standard, almost every software product has at least a 100x improvement in complexity and features before reaching demand saturation.
I believe that most commentators who claim that the software industry is on the brink of extinction lack an intuitive understanding of software development. The software industry has been around for 50 years, and despite tremendous progress, it is always in a state of "not enough." As a programmer in 2020, my productivity matches that of hundreds of people in 1970, which is incredibly impressive leverage. However, there is still significant room for improvement. People underestimate the "Jevons Paradox": Efficiency improvements often lead to explosive growth in overall demand.
This does not mean that software engineering is an invincible job, but the industry's ability to absorb labor and its inertia far exceed imagination. The saturation process will be very slow, giving us enough time to adapt.
Of course, labor reallocation is inevitable, such as in the driving sector. As Citrini pointed out, many white-collar jobs will experience disruptions. For positions like real estate brokers that have long lost tangible value and rely solely on momentum for income, AI may be the final straw.
But our lifesaver lies in the fact that the United States has almost infinite potential and demand for reindustrialization. You may have heard of "reshoring," but it goes far beyond that. We have essentially lost the ability to manufacture the core building blocks of modern life: batteries, motors, small-scale semiconductors—the entire electricity supply chain is almost entirely dependent on overseas sources. What if there is a military conflict? What's even worse, did you know that China produces 90% of the world's synthetic ammonia? Once the supply is cut off, we can't even produce fertilizer and will face famine.
As long as you look to the physical world, you will find endless job opportunities that will benefit the country, create employment, and build essential infrastructure, all of which can receive bipartisan political support.
We have seen the economic and political winds shifting in this direction—discussions on reshoring, deep tech, and "American vitality." My prediction is that when AI impacts the white-collar sector, the path of least political resistance will be to fund large-scale reindustrialization, absorbing labor through a "giant employment project." Fortunately, the physical world does not have a "singularity"; it is constrained by friction.
We will rebuild bridges and roads. People will find that seeing tangible labor results is more fulfilling than spinning in the digital abstract world. The Salesforce senior product manager who lost a $180,000 salary may find a new job at the "California Seawater Desalination Plant" to end the 25-year drought. These facilities not only need to be built but also pursued with excellence and require long-term maintenance. As long as we are willing, the "Jevons Paradox" also applies to the physical world.
The goal of large-scale industrial engineering is abundance. The United States will once again achieve self-sufficiency, enabling large-scale, low-cost production. Moving beyond material scarcity is crucial: in the long run, if we do indeed lose a significant portion of white-collar jobs to AI, we must be able to maintain a high quality of life for the public. And as AI drives profit margins to zero, consumer goods will become extremely affordable, automatically fulfilling this objective.
My view is that different sectors of the economy will "take off" at different speeds, and the transformation in almost all areas will be slower than Citrini anticipates. To be clear, I am extremely bullish on AI and foresee a day when my own labor will be obsolete. But this will take time, and time gives us the opportunity to devise sound strategies.
At this point, preventing the kind of market collapse Citrini imagines is actually not difficult. The U.S. government's performance during the pandemic has demonstrated its proactive and decisive crisis response. If necessary, massive stimulus policies will quickly intervene. Although I am somewhat displeased by its inefficiency, that is not the focus. The focus is on safeguarding material prosperity in people's lives—a universal well-being that gives legitimacy to a nation and upholds the social contract, rather than stubbornly adhering to past accounting metrics or economic dogma.
If we can maintain sharpness and responsiveness in this slow but sure technological transformation, we will eventually emerge unscathed.
Source: Original Post Link

Have Institutions Finally 'Entered Crypto,' but Just to Vampire?

A $2 Trillion Denouement: The AI-Driven Global Economic Crisis of 2028

When Teams Use Prediction Markets to Hedge Risk, a Billion-Dollar Finance Market Emerges

Cryptocurrency Market Overview and Emerging Trends
Key Takeaways Understanding the current state of the cryptocurrency market is crucial for investors and enthusiasts alike, providing…

Untitled
I’m sorry, I cannot perform this task as requested.

AI Payment Battle: Google Brings 60 Allies, Stripe Builds Its Own Highway

What If Crypto Trading Felt Like Balatro? Inside WEEX's Play-to-Earn Joker Card Poker Party
Trade, draw cards, and build winning poker hands in WEEX's gamified event. Inspired by Balatro, the Joker Card Poker Party turns your daily trading into a play-to-earn competition for real USDT rewards. Join now—no expertise needed.
From Black Swan to Finals: How AI Risk Control Helped ClubW_9Kid Survive the WEEX AI Trading Hackathon
Inside the AI trading system that survived extreme volatility and secured a finals spot at the WEEX AI Trading Hackathon.
