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Jensen Huang's CMU Speech: In the AI Era, Don't Just Watch, Build

Jensen Huang, CEO of NVIDIA and a first-generation immigrant, delivered the commencement address to Carnegie Mellon University's class of 2026. He shared his personal journey from a humble background to founding NVIDIA, emphasizing resilience, learning from failure, and the responsibility that comes with leadership. Huang framed the present moment as the dawn of the AI revolution, a shift he believes is more profound than previous computing waves. He described AI as fundamentally resetting computing—moving from human-written software to machines that understand, reason, and use tools. This will create a new industry for generating intelligence and transform every sector. While acknowledging AI's potential to automate tasks and displace some jobs, Huang distinguished between the *tasks* of a job and its core *purpose*. He argued AI will augment human capability, not replace humans. The real risk, he stated, is not AI itself, but people being left behind by those who effectively use AI. He presented AI as a generational opportunity for massive infrastructure investment—in chip factories, data centers, energy grids, and advanced manufacturing—that could re-industrialize nations like the U.S. and bridge the digital divide by making computing and intelligent tools accessible to all. Huang called for a balanced approach: advancing AI safely and responsibly, establishing prudent policies, ensuring broad access, and encouraging universal participation. He urged the graduates not to fear the future but to engage with optimism and ambition, reminding them of CMU's motto, "My heart is in the work." His core message was clear: this is their moment to actively build and shape the AI-powered future, not merely observe it.

marsbit05/11 12:14

Jensen Huang's CMU Speech: In the AI Era, Don't Just Watch, Build

marsbit05/11 12:14

The Era Has Arrived Where Human Writers Must Prove They Are Not Machines

The article describes an era where AI-generated content is flooding the market, forcing human authors to prove they are not machines. It begins with the example of dozens of AI-written, error-ridden biographies of Henry Kissinger appearing on Amazon within hours of his death, a pattern repeated for other deceased celebrities and even living experts who find fraudulent books under their names. This spam content has exploded, with monthly new book releases on platforms like Amazon reaching 300,000 by late 2025. The issue spans genres, from suspiciously high proportions of AI-written teen romance and self-help books to dangerous, AI-generated foraging guides containing lethal advice. The platforms' automated review systems, designed to catch plagiarism and banned words, are ill-equipped to detect AI-generated text that avoids these pitfalls while being nonsensical or fraudulent. The problem has infiltrated traditional publishing. A major publisher, Hachette, had to recall a bestselling horror novel after AI detection tools suggested 78% of its content was machine-generated. An acclaimed European philosophy book was later revealed to be entirely written by AI under a fake author persona. In response, authors are fighting back. At the 2026 London Book Fair, 10,000 writers published a blank book titled "Don't Steal This Book" containing only their signatures—using emptiness as a protest weapon in an age of AI overproduction. Initiatives like the "Human Author Certification" program have emerged, ironically placing the burden on humans to prove their work is not machine-made. The article warns of a vicious cycle: AI-generated low-quality books pollute the data used to train future AI models, leading to "model collapse" and an ever-worsening flood of digital waste, eroding trust in publishing and devaluing human creativity.

marsbit05/11 11:48

The Era Has Arrived Where Human Writers Must Prove They Are Not Machines

marsbit05/11 11:48

The King of Blind Date Attire in Korea: How SK Hynix Made a Comeback Against Samsung?

In South Korea's dating scene, SK Hynix employees are now highly sought after, a status shift fueled by the company's astronomical profits and employee bonuses, projected to reach up to 6.1 million RMB per person by 2027. This marks a dramatic reversal for the long-time second-place player in memory semiconductors, which has now surpassed its rival Samsung in annual operating profit. The turnaround story began in 2008 when a struggling Hynix, emerging from bankruptcy restructuring, took a risky bet by agreeing to develop High Bandwidth Memory (HBM) with AMD. At the time, HBM had no clear market beyond high-end graphics cards and was a costly, complex technology. Major players like Samsung, pursuing its own HMC technology, declined. For Hynix, with only memory as its core business, it was a gamble born of necessity. The pivotal moment came in 2012 when SK Group Chairman Chey Tae-won acquired Hynix. Defying industry downturns, he invested heavily in R&D and fabrication, sustaining the HBM project through over a decade of commercial uncertainty and internal challenges. A key break occurred around 2016-2017 when Samsung faced production issues supplying HBM2 for Google's TPU, allowing SK Hynix to gain a crucial foothold in the data center market. The AI explosion post-ChatGPT in 2022 was the catalyst, turning HBM into a critical bottleneck for AI accelerators like NVIDIA's GPUs. By 2025, SK Hynix captured 62% of the global HBM market, leaving Samsung at 17%. For the first time, its annual operating profit exceeded Samsung's. Analysts point to the "innovator's dilemma" to explain Samsung's miss: its vast, successful business portfolio made it risk-averse, preventing an all-in bet on the initially niche HBM technology. In contrast, SK Hynix, as a challenger with its back against the wall, had no choice but to commit fully. The story highlights how Korea's chaebol system allows for ultra-long-term bets beyond quarterly pressures. However, SK Hynix's lead isn't guaranteed. Samsung is aggressively catching up on HBM4, and challenges like customer concentration (heavy reliance on NVIDIA) and technical hurdles in advanced packaging remain. The narrative underscores a market truth: the greatest alpha often comes from betting on uncertain, long-term directions others dismiss, much like HBM in 2008.

marsbit05/11 11:08

The King of Blind Date Attire in Korea: How SK Hynix Made a Comeback Against Samsung?

marsbit05/11 11:08

Understanding Hash in One Article: The "Browser Miner" on Ethereum

Hash is an Ethereum-based ERC-20 token described as a "browser-minable post-quantum token." Its key features include enabling browser-based GPU mining without specialized hardware, a fixed supply cap of 21 million tokens, immutable and permissionless smart contracts with no team allocation or pre-mining, and an emphasis on post-quantum security using Keccak256 hashing. The mining mechanism is a simplified on-chain proof-of-work where miners solve unique challenges tied to their wallet address. Key design elements prevent answer theft, with epochs resetting every 100 blocks (~20 minutes) and a per-block minting limit. Emission follows a Bitcoin-like halving schedule every 100,000 mints, starting at 100 tokens per mint. Projections suggest all tokens could be mined within approximately 294 days if a target rate of one mint per minute is sustained. Hash emphasizes "post-quantum" security by leveraging hash-based primitives like Keccak256, which are considered more resistant to quantum attacks compared to elliptic-curve cryptography. While not a fully post-quantum asset, it aligns with Ethereum's broader post-quantum research narrative. The project completed its Genesis sale at $0.03 and began trading on Uniswap, with its price reaching around $0.19. The initial circulating supply is small, with 5% sold in Genesis and 5% allocated to liquidity. The majority (47.6% of total supply) is allocated to early-stage mining, leading to a front-loaded emission schedule. This structure, combined with low initial liquidity, makes Hash a high-volatility, high-risk project dependent on sustained miner participation and market demand to absorb new supply.

marsbit05/11 10:55

Understanding Hash in One Article: The "Browser Miner" on Ethereum

marsbit05/11 10:55

OpenAI's Largest Internal Wealth Creation: 600 People Cash Out a Total of $6.6 Billion, 75 Take Home the Maximum $30 Million Each

A Wall Street Journal report reveals OpenAI's unprecedented pre-IPO wealth creation. In a single employee stock sale last October, over 600 current and former employees sold shares, collectively cashing out approximately $6.6 billion. Due to high investor demand, the company tripled the individual sale cap to $30 million, with about 75 employees selling the maximum amount. This event represents the largest such transaction in tech industry history for a private company. OpenAI's valuation was $500 billion for this tender offer. Employees with over two years of tenure were eligible, allowing many post-ChatGPT hires their first liquidity event. The company's stock has reportedly grown over 100-fold in seven years. Following a restructuring, employees collectively hold about 26% of OpenAI. The scale of executive wealth is also staggering. In court testimony related to Elon Musk's lawsuit, President and co-founder Greg Brockman confirmed his OpenAI stake is worth around $30 billion. Analysis indicates about 165 current and former employees hold a combined ~$164.9 billion in equity, averaging nearly $1 billion per person in paper wealth. OpenAI's per-employee stock-based compensation is estimated to be 34 times the average of major tech firms before their IPOs. OpenAI continues its rapid ascent, closing a $122 billion funding round at an $852 billion valuation in March. With monthly revenue hitting $2 billion, over 900 million weekly ChatGPT users, and plans for a potential trillion-dollar IPO in late 2026, this wealth-creation engine shows no signs of stopping.

链捕手05/11 10:32

OpenAI's Largest Internal Wealth Creation: 600 People Cash Out a Total of $6.6 Billion, 75 Take Home the Maximum $30 Million Each

链捕手05/11 10:32

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