# Сопутствующие статьи по теме Innovation

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

Token Is Completely on Fire, Blockchain Is Heartbroken

Token, a term once central to blockchain's vision of decentralization and economic transformation, has now been popularized by the AI industry as a unit of computation and billing. With the rise of products like OpenAI's ChatGPT and Deepseek, Token has become widely recognized as a measure of API calls and computational power—essentially a "currency for compute." This shift has left the blockchain sector in an ironic position: while it long struggled to explain Token's potential for revolutionizing ownership and community governance, AI has repurposed the term into a practical, everyday concept devoid of cryptographic complexity. The blockchain community once championed "Tokenization of Everything," aiming to convert real-world assets and labor into tradable tokens. Instead, AI achieved a form of tokenization by breaking down text, audio, and video into Tokens for processing—without requiring users to manage private keys or understand consensus mechanisms. This practical adoption contrasts sharply with blockchain’s association with speculation and scandals, as seen in the rise and fall of NFTs and memecoins. Amid a broader crisis of faith in blockchain’s promise—with many innovators expressing disillusionment over the industry’s shift toward speculation—AI’s rapid growth has intensified this sense of irrelevance. However, there are positive signs: traditional assets like U.S. Treasuries and stocks are increasingly being tokenized, attracting major financial institutions like BlackRock and Fidelity. This may signal Token’s return to its original purpose as a vehicle of value, even as AI dominates its popular meaning.

marsbit03/25 02:14

Token Is Completely on Fire, Blockchain Is Heartbroken

marsbit03/25 02:14

People Laid Off by AI Won't Disappear; They Will Become the Creators of the Next Economy

The article argues that the real question surrounding AI is not whether it will cause unemployment, but what happens to the people displaced. AI is replacing not humans, but the standardized, replicable, and automatable parts of human work. This follows historical patterns where technological revolutions, from stone tools to computers, made old skills obsolete and dissolved old structures—but humanity adapted and reorganized. The author draws a parallel to China’s large-scale layoffs during state-owned enterprise reforms 30 years ago, which initially seemed catastrophic but eventually fueled the growth of a new private economy, new companies, and new types of jobs. Engineers, though among the first impacted, are also positioned to recover fastest. Their systemic understanding and proximity to new productive forces make them ideal candidates to adapt and create in the new economy. More importantly, AI is reshaping companies themselves—reducing organizational bloat, communication costs, and bureaucracy. This enables smaller, more agile teams and empowers strong creators who may have previously struggled with management rather than innovation. The core issue is not job loss, but self-definition: will individuals wait to be reassigned by the old system, or use new tools to reorganize production? AI accelerates differentiation—eliminating some jobs, shattering illusions for some, and offering others a chance to leap forward. The author’s view is that AI is dismantling an entire generation’s belief in stable career paths. Those laid off won’t vanish; instead, many will reinvent themselves—transitioning from employees in old systems to creators of the next economy. Every productivity revolution淘汰 (eliminates) not people, but those who refuse to rewrite themselves. The first to accept this and start building the new world will succeed.

marsbit03/23 10:31

People Laid Off by AI Won't Disappear; They Will Become the Creators of the Next Economy

marsbit03/23 10:31

The Self-Destruction of the Startup Bible: The More You Know, the Sooner You Fail

The article "The Self-Defeating Nature of Startup Dogma: The More You Know, The Sooner You Fail" argues that popular startup methodologies—such as Lean Startup, Customer Development, and the Business Model Canvas—have not improved startup survival rates over the past 30 years, based on U.S. government data. The core paradox is that once a methodology becomes widely adopted, it loses its competitive advantage as all founders converge on the same strategies, leading to homogeneity and increased failure rates in competitive markets. The author compares this to the Red Queen effect in evolutionary biology, where continuous adaptation is necessary just to maintain position. Despite the intuitive appeal and scientific claims of these frameworks, empirical data shows no improvement in the survival rates of either general U.S. businesses or venture-backed startups. In fact, the success rate for seed-funded startups securing subsequent funding has declined. The article explores three possible explanations: the theories might be fundamentally flawed; they might be too obvious to require formalization; or they might be self-defeating when universally applied. The author calls for a truly scientific approach to entrepreneurship, one that embraces experimentation, paradigm development, and differentiation rather than dogma. The conclusion is that to succeed, founders must often do the opposite of what popular playbooks advise.

marsbit03/23 08:13

The Self-Destruction of the Startup Bible: The More You Know, the Sooner You Fail

marsbit03/23 08:13

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