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0:08
TikTok
janravnik
Email fail: forgot to delete ChatGPT note — what to do
Sent an email with a leftover ChatGPT prompt line? Read quick fixes, apology templates, and recovery steps to salvage the situation. #ChatGPT #email #worklife Jan Ravnik(@janravnik). WORK MOOD - SILLYBALOO. We've all been there... right? 😶
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Mello version // clips creds to; @mellooirl @scnnic @oonpledoople @ddanggeoji @⧽✟ ₘᵢₕₐₑₗ ₖₑₑₕₗ ₑₙₜₕᵤₛᵢₐₛₜ ✟⧼ // ax0728_ 2207410913 Dobrybuli on rednote #mello #llawliet #lightyagami #misaamane #deathnoteedit #deathnoteanime #deathnoteコスプレ
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The Daily Dev: Master System Design The Daily Dev is an app I built to help you master system design. You’ll learn the basics like caching, load balancing, networking, etc, then get tested on everything and improve over time. You also get access to a private discord community where you can directly ask me questions to level up. #systemdesign #coding #programming
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Build Your Own ChatGPT Bot in Python (in 60 Seconds) #python #coding #programming In this video you'll build a fully working ChatGPT bot from scratch using Python and the OpenAI API. Starting from a single API call, add user input function and then a full conversation loop with memory, all in under thirty lines of code. You'll learn how to initialize the OpenAI client, send messages to gpt-5.4-mini, and structure a growing message history so your bot actually remembers the conversation. All you
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Ready to take your coding game to the next level? Here's everything you need to know about Claude Code and how it can make development faster and smarter. Watch now and stay ahead in the AI coding revolution! #ClaudeCode #ArtificialIntelligence #Coding #Programming #AItools #Developers #TechNews #HishamSarwar
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Andrej Karpathy's explaination of Bigram Language Model explained Bigram LMs, though simple, it provides powerful insight into the inner mechanics of how tokens are processed in language models. This is a pre-amble for what's next: GPT, which is the 2nd part of the series The Bigram model here incorporates: Tokenization, Vocabulary, Negative Loss Function, Cross Entropy, Logits, SoftMax, Optimizer, and AdamW These are essential ingredients to understand in order to build our knowledge on how LLM
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Your reads and your writes want completely opposite things. CQRS stops them from fighting. 👇 Most apps use one model for everything. But writes and reads pull in different directions. Writes want a clean, normalized schema, split across many tables so nothing is duplicated and updates stay consistent. Reads want the opposite: everything pre-joined and denormalized so a query is a single fast lookup. Force them to share one model on one database and they contend for the same rows and locks, and
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