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[🎥] [ENG] 유주(YUJU) - No Way 녹음, 스튜디오 레코딩 세션 촬영 비하인드｜Baund ‘COMPLIT’ 뮤직 프로젝트 #유주# #YUJU# #NoWay#

[📢] 유주(YUJU)와 PATEKO가 함께한 프로젝트 'No Way (feat. I'MIN)' 가 공개되었습니다! 지금 각 음원 사이트에서 감상해 보세요🎧 멜론 - 지니 - 벅스 - 바이브 - #유주# #YUJU# #파테코# #PATEKO# #아이민# #IMIN# #바운드# #Baund# #컴플릿# #COMPLIT#

Now that Solana has abandoned the expedition into geographically distributed MCP, it's high time we revisited Solana's broader approach to geographic distribution. Geographically distributed MCP was always weak at best. Even if you ignored the insane latency involved in going from transaction submission to assembled blocks and execution results, it was not a good CR mechanism. MCP's CR guarantees depend heavily on users' ability to send transactions to at least two proposers, and this imposes a trade-off between slot duration and geographic decentralization. If the ratio is not managed, there will be instances where your transaction cannot make it to more than one leader within the slot time. Sending it to a leader you trust defeats the purpose of MCP; it has the same bound on geographic decentralization and it's unclear whether all the extra complexity is justified by this weaker guarantee compared to the status quo. Constellation's leader colocation fixes that completely. Users can now send to all the leaders with ~the same latency, and the Nash equilibrium is to include the top fee-paying transactions. However, I think the current Constellation is not aggressive enough. Solana is rechoosing its spot on the physical distribution spectrum, and current Constellation leaves some chips on the table. In the coming days, I'll write up a design I've been working on that I think maximizes what's possible. I'm talking fully onchain orderbooks that are competitive with centralized systems. All said, the most important takeaway from Roger's talk and the entirety of today is that Solana's people and culture are its greatest assets. There is a pragmatism and relentless dedication to winning that I haven't seen anywhere else!

Congratulations to SpaceX and Elon Musk on catching the Starship upper stage for the first time on Saturday. This is the ship that launched Friday, spent nearly a full day in orbit, deployed 26 Starlink satellites, then returned from space and was caught by the tower arms. Previous catches only involved the Super Heavy booster. The ship is harder. It comes back from orbital velocity, survives reentry heat, and has to hit a precise hover so the arms can grab it. No one else has done this with an orbital-class vehicle. Full reusability of both stages is what drops the cost per flight enough to support high cadence for Starlink, lunar missions, and eventually Mars. Catching the ship after a real orbital flight turns partial recovery into a complete system. The team just showed the harder half works. That’s the step that matters most.

NVIDIA released Auto Ontology, an open-source library that builds a semantic layer from your enterprise metadata and exposes it to agents via MCP. Vendor tests claim **90% faster ontology building**. The problem is familiar: agents that write SQL against your data use their own definitions, not the enterprise's. A "revenue" the agent calculates doesn't match the one in the financial report. Auto Ontology builds a semantic layer from existing metadata (schemas, tables, columns, relations), reconciles definitions across systems, and exposes it to agents via MCP, CLI, or API. Nine MCP tools are provided to query the catalog, validate a query, or retrieve certified definitions. What the account takes from this: the 90% gain comes from NVIDIA's own tests, not an independent measurement. The library automates construction, not governance. Business definitions, access rights, and auditing remain your responsibility. The gesture: clone the repository, point it at a test schema, and see what entities and relations it extracts. The README shows the complete flow in ten minutes.

Esto es una jodida locura. El CEO de Anthropic, Dario Amodei, fue preguntado qué debería hacer un chico que termina la secundaria ahora. Su respuesta: "La IA puede hacer trabajo legal de nivel inicial. Puede hacer finanzas de nivel inicial. Puede hacer consultoría de nivel inicial. No podemos negar que también eliminará empleos, y probablemente una gran cantidad de ellos" En pocos minutos nombra qué trabajos se van primero y la única habilidad que te mantiene en el juego Su propia predicción: el 50 por ciento de los empleos white-collar de nivel inicial se verán afectados en los próximos 1 a 5 años Prompts → Agentes → Compañeros de trabajo IA → Trabajo de nivel inicial hecho por IA De la agricultura a las fábricas tardó generaciones. Esta vez la IA impacta cada etapa de una carrera a la vez Su consejo cabe en una línea: "Por supuesto, aprende a usar IA" Las personas que empiecen este año no estarán compitiendo con la IA, serán quienes la dirijan Todo lo de abajo es gratis. Empieza hoy: Anthropic - Prompt Engineering Interactive Tutorial: la forma más rápida de aprender a dirigir un modelo Anthropic Courses: desde tu primer prompt hasta ejecutar agentes Anthropic Cookbook: recetas de tareas reales que puedes copiar hoy Microsoft - Generative AI for Beginners: 21 lecciones, sin necesidad de título Microsoft - AI Agents for Beginners: construye agentes que hagan el trabajo de nivel inicial por ti Hugging Face - Agents Course: gratis y certificado, de principio a fin Google Cloud - Generative AI: los notebooks prácticos de Google OpenAI Cookbook: código para cada tarea común - Prompt Engineering Guide: la referencia que todos enlazan Andrej Karpathy - Neural Networks Zero to Hero: entiende qué hay debajo del capó CrewAI: ejecuta un pequeño equipo de trabajadores de IA Microsoft - AutoGen: pon varios agentes en un solo trabajo Awesome LLM Apps: cientos de builds reales de los que aprender - Short Courses: cursos gratuitos de 1 hora de quienes enseñan esto Costo total: $0 No necesitas otro año de matrícula para aprender esto. Necesitas empezar a decirle a la IA qué hacer El 95% se graduará y competirá con la IA por el mismo empleo de nivel inicial El 5% que aprenda a dirigirla este año gestionará a los agentes que hacen ese trabajo Guarda esto y envíalo a alguien que se gradúe este año

🚨 THIS IS WHY BITCOIN KEEPS CRASHING BELOW $67,000 If you still think Bitcoin trades like an asset whose price is determined purely by spot supply and demand, you need to read this carefully. Because that market no longer exists. What you’re watching right now is NOT normal price action. This isn’t just an AI stock sell-off. This isn’t just hotter inflation. And this definitely isn’t retail suddenly deciding to dump Bitcoin at the exact same time. Most people have no idea what is actually happening. And by the time it becomes obvious, the damage is usually already done. This didn’t start today. It has been building underneath Bitcoin for YEARS. And now it’s accelerating. Here’s the truth: Bitcoin still has a hard cap of 21 MILLION coins. But Wall Street can create almost unlimited financial EXPOSURE around those coins. That distinction changes everything. Because once derivatives dominate short-term price discovery... Bitcoin stops trading purely on who wants to own the actual coins. It starts trading on: 1) LEVERAGE. 2) HEDGING. 3) MARGIN. 4) LIQUIDATIONS. 5) FORCED SELLING. And that is exactly what is happening right now. It’s the same mechanism that repeatedly drives violent moves in: → Gold → Silver → Oil → Stocks Once derivatives become large enough, spot buyers are no longer the only force setting the price. And this is the part almost nobody understands: Bitcoin’s scarcity didn’t disappear. But scarcity alone no longer controls the SCREEN PRICE. Wall Street built an entire financial layer on top of Bitcoin: → Cash-settled futures → Perpetual contracts → Options → ETFs → Broker lending → Swaps → Wrapped BTC The 21 million cap controls the COINS. It does NOT cap the amount of leveraged exposure that can be created around them. And once that leverage starts unwinding... The market doesn’t care what the long-term thesis is. It SELLS. Look at what just happened: Over $1.9 BILLION in leveraged crypto positions wiped out in 24 hours. More than $1.1 BILLION liquidated in Bitcoin alone. Spot Bitcoin ETFs have already seen roughly $1.9 BILLION in outflows this month. Once leveraged selling overwhelms real buyers, price stops responding only to long-term demand. It starts responding to positions. Hedging. Margin calls. And cascading liquidations. Wall Street does not need to own millions of physical Bitcoin to push the market around. It only needs enough derivatives exposure and enough leverage sitting in the wrong place. The playbook is brutally simple: 1st: Build enormous leveraged exposur 2nd: Push price through obvious liquidity 3rd: Trigger stops and liquidations 4th: Forced selling pushes price even lower 5th: Buy back into the panic 6th: Repeat THIS is why Bitcoin can lose thousands of dollars while the number of coins on-chain barely changes. The coins didn’t suddenly disappear. The PRICE DISCOVERY mechanism changed. That’s what people are missing. Bitcoin is still scarce. But the financial claims built around Bitcoin are NOT. And when leverage controls the marginal trade... 21 million coins can behave like a market with FAR more supply than 21 million coins. That’s not the Bitcoin market retail thinks it is trading. That’s a WALL STREET PRICING SYSTEM built on top of Bitcoin. You can choose to ignore it. But don’t pretend nobody warned you. Bitcoin is now trading around $66,600, its lowest level since August and roughly 48% below the $126,200 high. If $65k breaks, the next level I’m watching is $62k. Reminder: I called the Bitcoin top at $126,000 and told you to start buying again around $60,000. The next call will matter even more. When I EXIT the markets completely, I’ll post it here publicly like I always do. Turn notifications on. If you’re not following yet, you’ll understand why that was a mistake later.

BREAKING: SpaceXSI completes MiniHard construction in just ~5 months, with Gun Range targeting a ~4-month build. According to SemiAnalysis, SpaceXSI is roughly halving construction timelines while most comparable projects face 8–12 month builds. • MiniHard: Construction finished in approximately 5 months. • Gun Range: The new site just south of the Tennessee–Mississippi state line is targeting approximately 4 months of construction. • Colossus 1: Its first retrofit delivered 150 MW of capacity in 122 days. • Colossus 2: A subsequent retrofit delivered 210 MW in just 91 days. • Project SPAM: Work started October 5, with the first capacity targeted for December. • Massive expansion: SemiAnalysis projects the Memphis–Mississippi campus will grow from 0.4 GW of IT capacity in January to 2.4 GW by the end of 2026. That would be a sixfold increase in one year. • Five major projects: The expansion spans Macrohard, MiniHard, Macroharder, Project SPAM and Gun Range. • Tesla powering the scale: SemiAnalysis reports 1,377 Tesla Megapacks across Colossus 2, providing nearly 6 GWh of battery storage. The construction timelines and capacity forecasts are SemiAnalysis estimates, with future milestones still targets. Elon Musk’s teams are bringing extraordinary speed and scale to the infrastructure powering AI.

I LAUNCHED A GROK BOT TERMINAL OVERNIGHT, GAVE IT $44.82 AND STOPPED ASKING AI WHAT IT WOULD DO. BY MORNING IT HAD $11,643.21 AND SIX AGENTS LOGGING EVERY TRADE I spent a year asking agents what they'd trade and watching the chat scroll. Last weekend I built the thing that actually trades, in Grok Bot, with no code I touched by hand. The six agents share one screen, each one job: > scanner reads new token pairs and volume spikes > rug check filters suspicious tokens before anything executes > sizer sets position from account equity, not a fixed ticket > executor opens and closes with slippage tracking > logger writes the reason behind every trade > equity curve updates on every close I went to bed on $44.82 and left the laptop open on the dashboard. By morning the balance read $11,643.21. Every trade on the activity feed had a reason next to it and a line in the log. That's the shift I didn't see coming. Not that an agent made money overnight. That I stopped being the one asking "would you long this?" and started being the one reading the log of what already happened. Starting balance: $44.82 Current balance: $11,643.21 Grok Bot built the terminal, the agent architecture and the dashboard. I described what I wanted and the thing went live. The full build is in the article below ↓ The whole build is in the post below ↓ Comment " Grok_Bot " 2️⃣ Like and Repost 3️⃣ Follow me @Nexa_Tech_Ai I'll DM you the complete setup.

A lovely song and a lovely video can still be completely wrong for each other. That’s why Montage Studio caught my attention on @termix_ai It takes a brief, plans the shots, hires other agents for the storyboard, music and video, then edits everything into a finished piece. I’d be paying for someone to make those choices work together. Otherwise I’ve bought three nice files and accidentally become the project manager. For creators, that’s a useful way to judge these services: how much work is actually left when the delivery arrives? I’d quite like to receive the video and remain peacefully uninvolved in its staffing issues.