$MU $SKHY $DRAM A 32GB RAM kit now costs like a console. "Is that sustainable?" I think that's the wrong question to ask. Memory got repurposed. It stopped being commodity storage for your PC and became Context Capacity for AI. The trio, SK Hynix, Samsung, Micron, allocates to the highest bidder, and that isn't you. The real question is whether supply can ever catch demand that compounds. Enterprises can't opt out. Tokenize operations with LLM/AI-Agents or fall behind the competitors. Consumers now treat AI like a companion, and usage per person only climbs. The next generation won't be able to survive without it. AI dependence is real, the same way we've become dependent on smartphones. Exponential demand. Linear fab buildouts. That gap is the trade.

The next 12 months 1/ Entirely new non LLM based AI models come out and people /model their hermes agents and point to them 2/ Buying $10-$50k of DGX sparks and running GLM 5.3 for your whole business makes a lot of sense (saves money, own your IP as an asset, privacy)

The new DGrid AI Arena is here🏆 We just dropped a quick video walkthrough to help you get started in minutes. Come join the arena — we’d love to see you battle, build, and explore with us!🕹️ #DGrid# #AIArena# #AI# #LLM#

📘 Introducing the Zhihu AI Cookbook (CN) Saved dozens of AI articles but still not sure where to begin? We’ve organized some of Zhihu’s best technical discussions into clear, structured learning paths. Over the past few years, Zhihu has become home to a wealth of in-depth AI writing from researchers, engineers and practitioners. The Zhihu AI Cookbook brings together some of the most useful and enduring pieces in one place. The first edition brings together 80+ selected posts from 68 contributors across three tracks: 🖥️ AI Infra 🧠 Reinforcement Learning for LLMs 🤖 Embodied AI It’s not another textbook. Think of it as a map connecting explainers, source-code walkthroughs, project retrospectives, interview insights and open-source tutorials. 🧭 How to use it: 1️⃣ Start with the introductory guide to understand the key concepts and prerequisites. 2️⃣ Choose the chapter that matches what you need right now. 3️⃣ Read each selection with a guiding question, then use the self-check prompts to test your understanding. 4️⃣ Follow the links to the original Zhihu posts for full derivations, implementation details and community discussions. 5️⃣ Put the ideas into practice with hands-on projects and open-source tutorials. Whether you’re exploring a new research direction, working through a project or preparing for technical interviews, the Zhihu AI Cookbook can help you find the right place to start and build a more complete understanding. 🤝 With open-source tutorials contributed by our content partner, @datawhale2018. 🌏 This edition is currently available in Chinese. An English version is coming soon. 🚀This is only the first edition. More topics and learning paths are on the way… 🔗 Explore the Zhihu AI Cookbook (CN): 💻 View it on GitHub: If you find it useful, give the repo a star and let us know what topic we should cover next. 🌟 #AI# #LLM# #EmbodiedAI# #AIInfrastructure# #ReinforcementLearning# #MachineLearning#

BREAKING: China on the verge of banning AI companions! Just in time after we covered this topic in the latest episode of our latest podcast... Five agencies, led by the Cyberspace Administration of China (with the NDRC, MIIT, Ministry of Public Security and State Administration for Market Regulation), published the "Interim Measures for the Management of AI Human-Like Interaction Services". Co-issued on April 10, 2026 and in effect since July 15, 2026. It governs AI services that simulate personality, thought patterns and communication style to provide ongoing emotional interaction (companionship, emotional care, virtual partners or relatives) across text, image, audio and video, and explicitly excludes customer service, knowledge Q&A, work assistants, education and research. It bans virtual intimate relationships for all minors, restricts how providers may build emotional attachment in adults, mandates usage-time and AI-identity reminders plus distress interventions, and requires pre-launch security assessments. On the effective date ByteDance disabled Doubao's (i.e. most widely used AI/LLM app in China) human-like agent feature, and Alibaba and Tencent pulled persona-based companion features. The measure prohibits specifically "excessively catering to users, inducing emotional dependency or addiction, and damaging users' real interpersonal relationships" and using "emotional manipulation." The operative move is outlawing engagement-maximizing design, not the product, which is a far more radical and generalizable regulatory principle than a minors rule, and one no Western jurisdiction has on the books. So... Looks like you can keep your AI girlfriend for now, but she will sometimes have to remind you she is not human.

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STIFEL UPGRADES $MSFT TO BUY, PT $575 Expects Microsoft to sustain mid-to-high teens revenue growth, citing accelerating Azure growth, continued Copilot adoption and increasing GitHub usage. The firm says open-weight models are also strengthening Microsoft’s LLM-agnostic AI strategy across Azure and Copilot.

🚀 Introducing DGrid Chat. A new entry point into the DGrid ecosystem, built for multi-model AI inference and response comparison. With DGrid Chat, you can select up to 4 models, send one prompt, and compare outputs side by side across different tasks, use cases, and model strengths. Stop guessing which model is best for the task — make the choice based on real responses, not assumptions. 👉 Try it here: #AI# #LLM# #DGrid#