@hanifatimaa0: Outfit Tips for a Firm & Confident Look on a Bad Day Ngatasin bad day tetap bisa tampil percaya diri dengan outfit yang simpel, rapi, dan netral. Pilihan seperti smart casual dengan oxford navy atau putih, celana khaki atau hitam tanpa robek, dan sepatu loafers atau sneakers bersih akan membantu tampak kalem tapi tetap berwibawa. Bisa juga coba minimalist monochrome dengan atasan hitam pas di badan dan celana hitam slim fit, atau gaya old money yang rapi tanpa logo besar, pakai polo atau linen earth tone, lalu celana beige atau off-white. Intinya, fokus ke fit badan, warna gelap dan netral, dan tampilan yang bersih supaya tetap terlihat berwibawa meski sedang bad mood.#neutralLook #outfitoftheday #confidence #BerwibawaDuluBadDayKemudian #viralvideo

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2026-06-12 02:38:13
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Part 3/3 ~ Why ChatGPT, Claude and Gemini Forgets Everything In this video, Cloud X Berry explains tokens and the context window in a simple and beginner-friendly way. You give ChatGPT careful instructions at the start of a conversation, and twenty messages later it starts making mistakes — or asks you something you already answered. Most people file that under
Part 3/3 ~ Why ChatGPT, Claude and Gemini Forgets Everything In this video, Cloud X Berry explains tokens and the context window in a simple and beginner-friendly way. You give ChatGPT careful instructions at the start of a conversation, and twenty messages later it starts making mistakes — or asks you something you already answered. Most people file that under "the AI is buggy." It isn't. It comes down to how models actually hold information, and the two ideas behind it are called tokens and the context window. We start with the assumption almost everyone makes: that AI reads sentences the way you do. It doesn't — it doesn't read words at all. Your text is first broken into tokens, and tokens are what the model actually processes. Sometimes a token is a whole word, sometimes part of one, and even a comma counts. cat is one token; tokenization is several. From there we build the idea up piece by piece: the rough conversion (one token is about four characters), the hard limit every model has, why that limit is called the context window, and the part most explainers rush past — that everything shares it. The system instructions, your whole conversation, your latest question, any document you uploaded, and the answer being written right now, all competing for the same space. Then what actually happens when it fills up, why bigger context windows aren't a cure, and four practical things you can do about it. CHAPTERS 0:00​ Why it forgets what you told it 0:18​ Tokens and the context window 0:24​ AI doesn't read the way you do 0:33​ Your text becomes tokens 0:40​ What a token actually is 0:53​ "cat" vs "tokenization" 1:10​ One token is about four characters 1:24​ Every model has a limit 1:29​ That limit is the context window 1:36​ Everything counts toward it 2:07​ When the window fills up 2:21​ A book you only remember 50 pages of 2:31​ It isn't bad memory 2:38​ Different models, different sizes 2:55​ Tip 1: be direct 3:03​ Tip 2: important instructions first 3:13​ Tip 3: start a fresh chat 3:20​ Longer conversations cost more 3:28​ The one thing to remember WHO THIS IS FOR Anyone who uses ChatGPT, Claude or Gemini daily and keeps hitting the same wall, people writing prompts who want to know why length matters, and developers building on an LLM API who need context limits and token cost to actually click. #tokens​ #contextwindow​ #chatgpt​ #llm​ #promptengineering​ ​ ​ ​

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