Pour le Daily Task 80, je vous parle de la supply fixe d’ITLG. Avec ses trois états — in App, on-chain, et vITLG — le total supply restera toujours à 100 milliards. Aucun nouvel ITLG ne peut être créé au-delà de cette limite. C’est une garantie de rareté et de stabilité à long terme. Quand ITLG change d’état, la quantité correspondante est verrouillée et bridgée. #InterLink #ITLG #ITL - @fanirisoa201

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"On turn 10 of a chat, the AI only reads my new message: about 10 tokens." Nope. Chat APIs are stateless: the app keeps the conversation and sends all of it, every turn, and the model reads it all again from the top. 📜🔁 We ran a 10-turn chat on a Mac mini (M4 Pro) with a small local model (qwen2.5:0.5b) through ollama's chat API, sending the whole history each turn, the way the API docs describe: - Turn 1 sent 1 message; turn 10 sent 19. The prompt the model read grew every turn: 36, 68, 93, 119, 147, 175, 227, 266, 300, 328 tokens. On turn 10, Dave's new message ("What's my name?") was 5 tokens; the model read 328. - Over 10 turns Dave typed 79 tokens. The model read 1,759. - The same question on turn 2, "What's my name?": with the chat sent along, "Your name is Dave." With only the new message: "Hello! I am Qwen, a large language model created by Alibaba Cloud. My name is Qwen." The model keeps nothing between requests. - Anthropic's docs say it plainly: "The Messages API is stateless, which means that you always send the full conversational history to the API." And "Anthropic's API bills and rate-limits by token counts": each request's input tokens include the history. Prompt caching makes the repeated part cheaper (a cache hit costs 0.1× the input price at the standard rate; a few models less), not free. Locally, ollama's cache served 313 of turn 10's 328 tokens; they were still part of the prompt. Fine print: our counts are qwen2.5's tokens and include ollama's built-in system prompt; other models count differently, and we show no prices. This tiny 0.5B model only used Dave's name on the first few turns: by turn 10 it answered with its own name even with the whole chat (we tried four wordings, all logged); without the chat it never knew it (0 of 13). We don't say how any particular chat app works inside: this is about the APIs, per their docs. Repeats gave identical numbers. Prices and multipliers from Anthropic's pricing page, fetched 2026-10-15. Sources: Anthropic, "Using the Messages API" (Multiple conversational turns), the Messages API reference (`usage`), the Pricing page (Prompt caching) and the Prompt caching guide; ollama's API docs (`prompt_eval_count`, `prompt_eval_cached_count`). Our scripts, every request and reply, and the quotes are in the facts file. Voices: ElevenLabs. Save this, and start a new chat for new topics. #ai #llm #chatbot #promptcaching #DaveWasWrong

😂 Коли їде перевірка з Головного управління — казарма переходить у режим МАКСИМАЛЬНОЇ БОЙОВОЇ ГОТОВНОСТІ 🫡🔥 🧹 Порядок наводиться зі швидкістю світла 🪖 Кожен раптом знаходить собі роботу 😂 Аж блищить усе, навіть те, що ніхто не чіпав місяцями! Хто служив — той знає 😂🤝 📲 Підписуйся на Kazarma 24/7 — армійське життя без прикрас! 🇺🇦 #Kazarma247 #Kazarma24_7 #армія #ЗСУ #військові служба 😂🔥

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Friday 09 October 2026 10:20:09 GMT

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