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This is how HOUND smells a market. Market data enters as raw signal. HOUND normalizes it into a feature vector, projects it across 32 synthetic odor channels, activates 971 receptor slots, generates a scent fingerprint, compares it against memory, then decides what deserves attention. Market data → Feature encoding → Synthetic odor → 971 receptors → Scent fingerprint → Memory → HOUND response. The point is not to predict the next candle. It is to give market behavior another sensory representation, so changes, similarities and unfamiliar patterns become easier to notice. Try here :

I am bewildered, and not very impressed, by the visceral, naked, irrational hatred spat out by some defenders of Jason Arday. If a Cambridge professor is accused of being an unqualified charlatan, the accusation might be racially motivated. On the other hand it might not, depending on the evidence. The correct question to ask is not, ”What is the colour of his skin” but “Is it in fact true that he is an unqualified charlatan?” Please examine the evidence before leaping to the assumption of racism. As for the idea that journalists “piled in on him” and “hounded him to his death”, most attacks were against Cambridge University. Jason himself was widely regarded as an unfortunate victim of foolish promotion way beyond his ability to cope. In appointing him to a professorship for which he was manifestly unqualified – in ludicrously describing him as “the best in the world” – certain senior members of the university showed a level of patronising condescension towards black people that could fairly be described as racism, while at the same time making him tragically vulnerable to such attacks as came his way.

Lord Hermer is gone. Good riddance to a man who hounded British soldiers in court and refused to apologise for it. He took the side of foreign terrorists over our veterans. It's utterly damning that Labour ever thought he was fit to be Attorney General.

推し活の巻🥺 最高でした。 つぐみがつぐみだった... 本当に憧れ尊敬素敵すぎた。 選曲神過ぎました。 明日は二の腕筋肉痛です。 ありがとうございます。 あーライブしたくなった。 わたしも頑張るわよ！ #Impishcrow# #DIGROCK# #ディグロ# #RUBIA# #HOUND# #つぐみ# ※宣伝拡散のため撮影許可OKでした♡

The Evolution of SGLang, 2024 → ∞: from a caching trick to the inference engine behind 330+ organizations | 2026 Under three years, twenty milestones: from RadixAttention (Jan 2024) to SGLang v1.0 and the SGLang Consortium (Nov 2026). Today SGLang is used by 330+ organizations, supported 217 models on day 0, and runs on hundreds of thousands of GPUs. Music only. Every frame and every note generated in code. Sources: LMSYS blog and @sgl_project (Nov 12, 2026), @lmsysorg (Nov 11, 2026), @radixark (Nov 12, 2026), SGLang Summit 2026 timeline wall and keynote slides. AI-generated content (视频由 AI 生成).

Is Shiba Inu gaining holders even as its price struggles? SHIB added roughly 150,476 net addresses between the start of 2026 and Nov. 13, according to daily Etherscan-based holder tracking. That puts its holder count at 1,699,106, just thousands short of 1.7 million. The growth continued through months of price weakness. Many days saw hundreds of new addresses enter the count. But there's a catch: holders aren't necessarily people. The figure includes exchange wallets, smart contracts and users with multiple addresses. Even wallets with tiny SHIB balances count. More addresses don't automatically mean stronger demand, fresh capital or a price recovery. Is SHIB's expanding holder base a sign of resilience, or is the market right to ignore it?

This is f*cking insane. Anthropic CEO Dario Amodei was asked what a kid finishing high school should do now. His answer: "AI can do entry-level law work. It can do entry-level finance. It can do entry-level consulting We can't deny that it will also eliminate jobs, and probably a large number of them" In a few minutes he names which jobs go first and the one skill that keeps you in the game His own prediction: 50 percent of entry-level white-collar jobs disrupted in the next 1 to 5 years Prompts → Agents → AI Coworkers → Entry-Level Work Done By AI Farming to factories took generations. This time AI hits every step of a career at once His advice fits in one line: "Of course, learn to use AI" The people who start this year won't be competing with AI, they'll be the ones running it Everything below is free. Start today: Anthropic - Prompt Engineering Interactive Tutorial: the fastest way to learn to direct a model Anthropic Courses: from your first prompt to running agents Anthropic Cookbook: real task recipes you can copy today Microsoft - Generative AI for Beginners: 21 lessons, no degree required Microsoft - AI Agents for Beginners: build agents that do the entry-level work for you Hugging Face - Agents Course: free and certified, start to finish Google Cloud - Generative AI: Google's own hands-on notebooks OpenAI Cookbook: code for every common task - Prompt Engineering Guide: the reference everyone links to Andrej Karpathy - Neural Networks Zero to Hero: understand what is under the hood CrewAI: run a small team of AI workers Microsoft - AutoGen: put several agents on one job Awesome LLM Apps: hundreds of real builds to learn from - Short Courses: free 1-hour courses from the people who teach this Total cost: $0 You don't need another year of tuition to learn this. You need to start telling AI what to do 95% will graduate and compete with AI for the same entry-level job The 5% who learn to run it this year will manage the agents doing that job Save this and send it to someone graduating this year

haltet fest an euren jobs fest man findet rr keine neuen mehr niemand will neu einstellen und wenn doch sind die anforderungen so dermaßen unrealistisch hoch dass der normale bürger keine chance hat arbeiten zu gehen dieses land geht vor die hunde

🚨 Viernes 13. 3:36 pm: EE. UU. frena todos los despegues del país. Dos horas después, esta luz cruza el cielo de México, Guatemala, El Salvador, Honduras y Colombia. Cinco países grabando lo mismo, la misma tarde. Lo que era 👇 #Viernes13# #Avistamiento# #FAA# #ÚltimaHora#