Welcome to Royfactory

Introduction Artificial intelligence stocks are experiencing a significant correction in November 2025. Palantir Technologies [finance:Palantir Technologies Inc.], despite delivering strong third-quarter earnings, has declined over 16% from its peak and is marking its worst month in two years. This selloff reflects broader concerns about AI industry valuations, slowing economic growth, and investors’ reassessment of cash flow expectations. With the Nasdaq down 7% and the S&P 500 down 4% from their October highs, the tech-heavy market is undergoing a dramatic shift in sentiment. This article explores the drivers behind the AI selloff, valuation concerns, and what lies ahead for investors. ...

Introduction TL;DR The explosive growth of AI video and image generation tools has collided with hardware reality. On 2025-11-28, OpenAI capped Sora free users at 6 videos per day; Google cut Nano Banana Pro to 2 images per day on 2025-11-21. Both companies explicitly acknowledged server overload—Bill Peebles, head of Sora, declared “Our GPUs are melting.” Users can now purchase additional generations, but the bottleneck reveals a fundamental tension: the promise of democratized AI infrastructure meets the economics of finite compute resources. ...

Introduction TL;DR On 2025-10-31, Japanese manga publisher Shueisha issued an official statement accusing OpenAI of copyright theft, calling generative AI “stealing with extra steps."[1][4] The publisher demanded enforcement measures beyond opt-out systems and national-level legal reforms, directly challenging OpenAI’s current approach to training data sourcing.[1][5] This incident reignites a fundamental debate about AI training ethics, copyright frameworks across jurisdictions, and the viability of balancing technological innovation with creator protection in the AI era.[2][10] ...

Introduction Valve is preparing to disrupt the living room gaming market with its newly announced Steam Machine, a compact gaming PC designed to bring PC flexibility to the TV. Expected to launch in Q1 2026, the device has already sparked intense speculation regarding pricing and performance. In a detailed analysis released on November 27, 2025, tech YouTuber Linus Sebastian and the Linus Tech Tips team provided the most concrete price prediction to date: $699.99, arrived at by sourcing actual component costs and factoring in Valve’s manufacturing efficiencies.[3][1][8][2] ...

Introduction TL;DR Meta Platforms will deploy Google’s custom Tensor Processing Units (TPUs) in its own data centers by 2027 and begin leasing TPU compute from Google Cloud as early as 2026. This announcement triggered Nvidia [finance:NVIDIA Corporation] stock to plunge 6.8% on November 25, 2025, with Advanced Micro Devices [finance:Advanced Micro Devices Inc.] falling as much as 9%, signaling a fundamental shift in AI infrastructure procurement. This is not merely a vendor change—it represents the disintegration of the semiconductor industry’s most critical monopoly and the emergence of a competitive, multi-vendor AI chip ecosystem. ...

Introduction TL;DR: AI-related stocks experienced significant declines in November 2025 due to China directives and executive warnings. Nvidia traded near $198 (down ~4%), while Palantir plummeted over 8%. Most alarmingly, 45% of global fund managers surveyed by Bank of America identified the AI bubble as the biggest tail risk to the global economy—a sharp increase from 33% just one month prior. This marks the first time in two decades that institutional investors have cited corporate overinvestment as a systemic concern. ...

Introduction TL;DR: In early 2025, Andrej Karpathy, a founding member of OpenAI, coined a term that perfectly captured the zeitgeist of modern software development: “Vibe Coding.” It describes a shift where developers stop writing code line-by-line and instead “give in to the vibes,” delegating the implementation entirely to AI. This post explores what Vibe Coding is, how it works, and why it represents a double-edged sword for the software industry. Vibe Coding is an AI-first approach where developers prompt LLMs and check if the output “vibes” (works), often without reading the underlying code. Tools like Cursor, Claude, and Bolt.new enable this loop of “Prompt -> Run -> Fix.” While it democratizes app creation and boosts speed, it risks creating unmaintainable, insecure codebases known as “spaghetti code.” What is Vibe Coding? Traditionally, coding required a deep understanding of syntax, logic, and libraries. Vibe Coding abstracts this away. As Karpathy tweeted, it involves “forgetting that the code even exists.” The developer acts less like an architect and more like a product manager, describing requirements in natural language and critiquing the result. ...

Introduction TL;DR: Google unveiled its Willow quantum chip achieving a 13,000x speedup over top supercomputers on scientific simulations. This milestone demonstrates verifiable quantum advantage. The chip accelerates AI-quantum computing fusion, promising innovation in science and industry, with Alphabet’s stock rising more than 5% after the announcement. Google’s Willow chip and Quantum Echoes algorithm excel in simulating quantum systems much faster than classical HPC, representing a step towards practical quantum computing. Willow Chip and Quantum Echoes Breakthrough Google Quantum AI team released results showing the ‘Quantum Echoes’ algorithm running on the Willow chip can solve complex quantum simulation problems 13,000 times faster than the best supercomputers on specific benchmarks. This represents a verifiable quantum advantage in scientific computing, marking a significant breakthrough beyond random sampling demonstrations. ...

Introduction TL;DR: Chinese open-source AI models such as Qwen, DeepSeek and GLM are rapidly spreading across Southeast Asia, the Middle East, Latin America and beyond, helped by low cost, flexible deployment and strong multilingual capabilities. In contrast, many U.S. and European executives still favor proprietary frontier models from OpenAI, Anthropic and Google’s Gemini 3 because of their benchmark performance and mature safety tooling, but this “build for perfection” mindset may limit their reach in cost-sensitive markets. Outside the U.S. and Europe, enterprises increasingly prioritize control over cost and data, which pushes them toward open-source Chinese models instead of top-tier proprietary systems. Alibaba’s Qwen series and other Chinese LLMs now power hundreds of thousands of derivative models, making them de facto infrastructure for local AI applications. Google’s Gemini 3 leads in reasoning, multimodal capabilities and agentic workflows, but its closed nature makes it harder for some regions to align with local data sovereignty and budget constraints. “Bridge powers” in Asia and other middle-income regions are exploring a mixed approach: combine Chinese open-source stacks with U.S. proprietary models to avoid technological dependence on either side. US Perfection vs Chinese Diffusion At the 2025 Fortune Innovation Forum in Kuala Lumpur, investors and operators repeatedly contrasted U.S. AI firms that “build for perfection” with Chinese players that “build for diffusion.” U.S. and European executives tend to value even an 8% performance edge on coding or reasoning benchmarks, arguing that such margins can decide whether an AI system clears the bar for large-scale deployment. ...

Introduction TL;DR: Anthropic released Claude Opus 4.5 on 2025-11-23 as its new flagship model, positioning it as one of the strongest options for coding, AI agents, and computer-use workflows. The model combines a 200K context window, hybrid reasoning modes, and improved vision, math, and coding to handle complex enterprise tasks and long-running automation. With input priced at 5 USD per million tokens and output at 25 USD per million tokens—about a 67% cut from the previous Opus generation—plus caching and batch discounts, it significantly lowers the cost of frontier intelligence. By emphasizing “practical efficiency” over pure benchmark bragging rights and offering broad cloud availability, Opus 4.5 marks Anthropic’s assertive entry into the frontier AI competition. Opus 4.5 appears throughout Anthropic’s documentation and media coverage as a premium model tuned for professional software engineers and knowledge workers, with key use cases around large-scale coding, agentic workflows, and high-stakes enterprise decision support. The launch messaging explicitly highlights cost-efficiency and agent capabilities alongside model quality, signaling a shift from experimental to production-first frontier AI. ...