# Сопутствующие статьи по теме Future

Новостной центр HTX предлагает последние статьи и углубленный анализ по "Future", охватывающие рыночные тренды, новости проектов, развитие технологий и политику регулирования в криптоиндустрии.

Deutsche Bank's Blockbuster Report: The Two Ultimate Outcomes of AI - Marx's Prophecy and Musk's Vision

Deutsche Bank's report presents two extreme scenarios for AI's ultimate impact on the economy. The first, "Full Substitution," envisions AI fully replacing human labor, where capital becomes labor itself. This Marxian/Muskian outcome would render labor value and wages near zero, causing extreme wealth concentration. Classical economics would break down as the link between supply and demand fractures, leading to deflation, secular stagnation, and potential social upheaval. The second, "Augmentation," is a more familiar path where AI enhances human productivity without full replacement. New jobs emerge, policy adapts, and the economy continues similarly with moderate inflation and rising rates. The report concludes that the path taken depends on the speed of technological change versus institutional adaptation, with key indicators to watch being structural unemployment data and shifts in fiscal/antitrust policy.

marsbit02/27 09:06

Deutsche Bank's Blockbuster Report: The Two Ultimate Outcomes of AI - Marx's Prophecy and Musk's Vision

marsbit02/27 09:06

Will AI Really Cause an Economic Collapse in 2028? New Metrics Reveal Another Possibility

A response to Citrini Research's "2028 Global Intelligence Crisis" paper argues against its prediction of an AI-induced economic collapse. The author posits that while AI will destroy the income side of the economy (wages, jobs), it will simultaneously and more rapidly destroy the cost side, leading to a "deflationary prosperity." Traditional economic metrics like GDP and unemployment rates are becoming obsolete in this new "post-human economy." The key measure of future prosperity will be "intelligence output per unit energy," which is exponentially increasing. This transition, though potentially turbulent, is not a crisis but a radical evolution. AI and automation are also seen as necessary to fill a looming demographic gap from a declining global workforce. The new economy will shift value creation towards uniquely human traits like empathy, creativity, and connection, which are not captured by traditional indicators.

比推02/25 12:37

Will AI Really Cause an Economic Collapse in 2028? New Metrics Reveal Another Possibility

比推02/25 12:37

Vitalik Buterin is trying to fix crypto’s biggest blind spot: ‘The goal is to…’

Vitalik Buterin, co-founder of Ethereum, is shifting the focus of crypto conversations from price and performance to a more fundamental issue: the gap between user intent and a system's actual behavior. He argues that true security is about minimizing this divergence, as even simple actions involve complex human assumptions that are difficult to encode. Buterin extends this concern to the broader internet and AI, noting that the core challenge is not the ability to generate content or execute code, but the need for quality, judgment, and context. He envisions Ethereum evolving into a neutral coordination layer where AI agents can transact, prove actions, and build verifiable trust on-chain. This framework aims to create systems that don't just execute commands blindly but safely interpret human intent, making trustless and private interactions possible in an increasingly automated world.

ambcrypto02/23 19:03

Vitalik Buterin is trying to fix crypto’s biggest blind spot: ‘The goal is to…’

ambcrypto02/23 19:03

From Lloyd's Coffeehouse to Polymarket: Prediction Markets Are Reshaping the Insurance Industry

From the coffeehouses of 17th-century London to the blockchain-based prediction markets of today, the fundamental nature of risk management is being reimagined. The article begins with a contemporary crisis: major insurers like Farmers Insurance and State Farm are canceling hundreds of thousands of policies in states like Florida and California, a "great insurance withdrawal" driven by catastrophic losses from hurricanes and wildfires that have shattered traditional actuarial models. The narrative then returns to the origin of modern insurance at Lloyd's Coffee House, where merchants and shipowners gathered to collectively underwrite voyages, dispersing individual risk among a group. For centuries, this model of risk transfer, priced by expert actuaries, has dominated. However, climate change and unprecedented disasters are now exposing its limits. The article proposes looking beyond insurance to the financial concept of *hedging*—offsetting risk rather than transferring it. Examples include Ray Dalio's innovative solution for McDonald's to lock in corn and soybean meal prices to launch the McChicken, and Southwest Airlines' legendary fuel hedging strategy that saved it billions. This "elegant" mechanism turns future uncertainty into present-day certainty through open markets. The pivotal shift is embodied by Polymarket, a prediction market platform. Here, users can trade contracts on the outcome of real-world events, from elections to weather patterns. This creates a decentralized, real-time mechanism for pricing risk based on collective wisdom, not proprietary models. A homeowner in Florida could, for instance, buy a contract predicting a hurricane's landfall; its payout would act as a personalized hedge against damage. While prediction markets threaten to disintermediate insurers by eliminating information asymmetry and operational friction, they are not a complete replacement. They excel at pricing objective, verifiable risks (weather, events) but fail with complex, subjective ones (car accidents, health). The future likely holds a hybrid model: prediction markets serving as a foundational pricing layer and risk-hedging tool, while traditional insurers evolve to focus on personalized service, complex underwriting, and long-term risk management in areas where deep engagement is required. The piece concludes that we are witnessing a historic shift from passive risk acceptance to active risk trading, empowering individuals to become their own risk managers in an increasingly uncertain world.

marsbit02/21 08:12

From Lloyd's Coffeehouse to Polymarket: Prediction Markets Are Reshaping the Insurance Industry

marsbit02/21 08:12

After Dragonfly Raises $650 Million in New Funding, Haseeb Says 'Crypto Is Not for Humans,' AI Agents Are the Ultimate Users

Dragonfly Capital partner Haseeb Qureshi argues that cryptocurrency was not designed for human use, but rather for AI agents. Despite being a crypto-native firm, Dragonfly still relies on legal contracts over smart contracts due to their human-friendly design and legal enforceability. Traditional financial systems, though flawed, are built for human fallibility, whereas crypto’s complexity, security risks, and lack of intuition make it poorly suited for people. Qureshi posits that AI agents are the ideal users of crypto: they don’t tire, can verify transactions instantly, audit contracts rigorously, and prefer code-based certainty over the ambiguities of legal systems. Crypto’s deterministic, self-sovereign, and always-on nature aligns perfectly with AI’s operational needs. He envisions a future where "autopilot" wallets managed by AI handle financial tasks, navigating protocols and negotiating agreements autonomously. This shift will transform how crypto services compete and interact. Early examples, such as AI agents on platforms like Moltbook and Conway Research’s autonomous crypto-earning agents, already demonstrate this trend. In conclusion, crypto’s perceived flaws are not failures but indications that humans were never the intended users. With AI agents as the primary interface, crypto may finally realize its potential.

marsbit02/21 01:10

After Dragonfly Raises $650 Million in New Funding, Haseeb Says 'Crypto Is Not for Humans,' AI Agents Are the Ultimate Users

marsbit02/21 01:10

Dragonfly: Crypto Was Not Made for Humans

Crypto Was Not Made for Humans: A Summary Dragonfly Capital partner Haseeb Qureshi argues that cryptocurrency was not designed for human use, but rather for AI agents. Despite being a crypto-native firm, Dragonfly still relies on legal contracts over smart contracts for investments, highlighting that traditional systems are built for human fallibility—featuring safeguards, reversibility, and intuitive interfaces that crypto lacks. Crypto, with its rigid, deterministic, and code-based nature, is error-prone for humans, leading to fears around transactions, phishing, and irreversible mistakes. However, these very traits make it ideal for AI. AI agents can perfectly verify transactions, audit contracts, and operate within crypto’s 24/7, borderless, and self-sovereign environment. They prefer code over ambiguous legal systems, which are slow and unpredictable. Qureshi envisions a future of "self-driving" wallets where AI agents handle all financial interactions, navigating DeFi protocols on behalf of users. These agents will also transact with each other autonomously, forming an economy of non-human participants—a reality already emerging with projects like Moltbook and Conway Research. In conclusion, crypto’s perceived flaws are not shortcomings but indications that humans are not the intended users. Within a decade, direct human interaction with crypto may seem archaic, as AI agents become the primary interface, unlocking the technology’s full potential.

marsbit02/19 05:14

Dragonfly: Crypto Was Not Made for Humans

marsbit02/19 05:14

After Raising $650 Million, Dragonfly Believes Crypto Was Not Made for Humans

Dragonfly Capital partner Haseeb Qureshi argues that cryptocurrency was not designed for humans but is instead the ideal financial system for AI agents. Despite being a crypto-native firm, Dragonfly still relies on legal contracts over smart contracts for investments, highlighting that traditional systems are built for human fallibility—featuring safeguards, reversibility, and intuitive interfaces. Crypto, by contrast, is rigid, error-prone, and unforgiving, with complex addresses, gas fees, and irreversible transactions posing significant risks to human users. Qureshi posits that AI agents are the natural users of crypto: they operate with precision, trust code over ambiguous legal systems, and can verify transactions instantly. Unlike humans, AI can navigate crypto ecosystem autonomously, negotiating and executing binding agreements via smart contracts within minutes. Crypto’s global, permissionless, and deterministic nature makes it perfect for AI-to-AI economic activity, which is already emerging with projects like Moltbook and Conway Research’s autonomous agents. He predicts the future interface for crypto will be “self-driving” wallets managed by AI, which will handle financial tasks on behalf of users. This shift will transform how protocols compete and market themselves. In a decade, humans may look back in astonishment that they ever interacted directly with crypto—its true potential unlocked only when its complementary technology, AI, arrived.

Odaily星球日报02/19 05:10

After Raising $650 Million, Dragonfly Believes Crypto Was Not Made for Humans

Odaily星球日报02/19 05:10

How Can Ordinary People 'Survive' the Impact of the AI Wave?

In this urgent warning, HyperWrite CEO Matt Shumer argues that AI advancement is progressing far faster than most people realize, with transformative impacts imminent across all sectors. He draws a parallel to the rapid onset of the COVID-19 pandemic, suggesting the current technological shift is even more profound. Shumer, an AI industry insider, states that a small group of researchers at leading labs like OpenAI and Anthropic are driving exponential progress. He shares his personal experience: recent models like GPT-5.3 Codex and Claude Opus 4.6 can now autonomously build and test complex software applications from a simple English description, requiring zero human correction. This represents a qualitative leap from being an assistant to a superior executor. He emphasizes that this disruption, which began with coding, will soon affect all knowledge work—law, finance, medicine, writing, and analysis—within 1-5 years, not decades. Free versions of AI tools are outdated; the paid, cutting-edge models are vastly more capable. Metrics show AI's autonomous task-completion time is doubling every few months. Crucially, AI is now used to build and improve subsequent AI models, creating a self-accelerating feedback loop toward artificial general intelligence (AGI). Shumer's advice for "surviving" is to start using the most powerful AI tools *now*. Subscribe to premium models, integrate them into core professional tasks, and experiment daily. Financial prudence and developing adaptability are key. He concludes that while AI poses immense risks (from job loss to security threats), it also offers unprecedented opportunities for creativity and problem-solving if approached with curiosity and urgency. The time to prepare is immediately.

marsbit02/18 04:27

How Can Ordinary People 'Survive' the Impact of the AI Wave?

marsbit02/18 04:27

From Real Estate to the Internet, Where Lies the Wealth Code for the Next Decade?

The article explores where the next decade's wealth opportunities lie, arguing that each generation’s “wealth code” is shaped by its unique experiences—from real estate and manufacturing in the 70s to internet and tech stocks in the 80s and 90s. For Gen Z and beyond, the key may be virtual economies and digital assets, exemplified by platforms like Roblox. Roblox is not just a game but a financial training ground where young users learn business, economics, and investment through creating and trading virtual items. Examples include teens earning millions by developing games, learning pricing, team management, and ROI in the process. Roblox paid over $1 billion to creators in a year, with top earners making around $1 million annually. However, over 99% earn under $1,000, reflecting real-world economic dynamics. Traditional institutions like TD Bank are taking note, launching educational games on Roblox to engage youth where they are, recognizing that financial literacy is shifting from physical banks to digital environments. Meanwhile, brands like e.l.f. Beauty and fintech firms are also entering this space, blurring lines between industries. The piece highlights a generational shift in asset perception: virtual items (e.g., CS:GO skins valued at $5.8 billion) and cryptocurrencies are seen as legitimate assets by Gen Z, with 51% owning crypto and fewer than 50% holding traditional bank accounts. Trust is moving from institutions to digital consensus and code-based systems. Three forces drive this trend: cognitive lock-in (investing in familiar digital realms), intergenerational trust transfer (from physical assets to virtual consensus), and network effects (collective engagement boosting value). Roblox, often mislabeled as a game company, acts as a central bank, regulator, and economic infrastructure—issuing currency, taking transaction fees, and maintaining ecosystem stability. Its “losses” are strategic, akin to early-stage Alipay, investing in habit-forming infrastructure. The conclusion: the next decade’s wealth will be built where young people spend time—virtual worlds that blend entertainment, economy, and education. Understanding their redefinition of assets and trust is key to foreseeing future financial landscapes.

marsbit02/17 06:35

From Real Estate to the Internet, Where Lies the Wealth Code for the Next Decade?

marsbit02/17 06:35

Lost in Hong Kong

"Lost Hong Kong" explores the city's profound economic and social fragmentation, caught between its storied past and an uncertain future. Despite strong macroeconomic indicators—such as 3.2% GDP growth and a booming stock market—the reality for many residents is starkly different. Rising unemployment, widespread retail closures, and an exodus of locals seeking affordable services in mainland China reveal a deep divide between financial elites and ordinary citizens. This duality stems from Hong Kong’s "muscle memory" of past crises—the 1997 Asian Financial Crisis and 2008 Global Financial Crisis—which entrenched a regulatory obsession with stability. This cautious approach has stifled innovation, particularly in fintech and Web3. Initiatives like virtual banks and crypto ETFs have struggled under heavy compliance burdens, while legacy systems like HSBC’s PayMe and the government-backed FPS dominate digital payments. The city’s economy is fractured along three lines: finance vs.实体经济, elites vs. the public, and asset accumulation vs. innovation. While wealth management flourishes, R&D investment lags behind peers like Singapore and Shenzhen. Hong Kong’s attempt to embrace disruptive technologies like Web3 has been half-hearted, favoring controlled, institutional adoption over genuine decentralization. Ultimately, Hong Kong’s reliance on outdated models hinders its ability to adapt. The article concludes that without bold structural changes, the city risks being left behind as a new era of global innovation accelerates.

marsbit02/13 08:42