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1:34
TikTok
mattfarmerai
Tabbit puts ChatGPT, Claude, and Gemini inside your browser Built a Skill that drafts my entire AI tool review. Made with @Tabbit #tabbit #tabbitbrowser #AIbrowser #aitools #ai 🔗
Matt Farmer | AI & Marketing(@mattfarmerai). original sound - Matt Farmer | AI & Marketing. Tabbit puts ChatGPT, Claude, and Gemini inside your browser Built a Skill that drafts my entire AI tool review. Made with @Tabbit #tabbit #tabbitbrowser #AIbrowser #aitools #ai 🔗 Try Tabbit:https://kzu.cc/a8GTFt
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le détails de mon alimentation : C'est une journée où je me suis fait plaisir et je n'ai pas fait très attention aux calories. Chaque personne a une routine totalement différente donc ce qui me correspond ne fonctionnera pas forcément pour vous 🙏🏻🤍 Pour les compléments 💊: matin : 2 magnésium, 1 oméga 3, 5g glutamine goût cola après la séance : 4g créatine citron 🍋🟩 soir : 1 dose clear whey goût carbean pineapple ( ca ressemble à une virgin piña colada 👀) , 2 magnésium, 1 oméga 3, 1 zinc
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Un modelo chino acaba de superar a Fable 5 en frontend: Kimi K3. Ojo, en Gaming Fable 5 sigue siendo el rey. Lo pruebas en 2 minutos, a mano, con OpenCode (open source, no es Claude Code). No es gratis: 19 $/mes. Soy team Claude, pero esto se prueba. ¿Te pasas o sigues team Claude? Paso a paso en pabloinpublic.com/recursos/probar-kimi-k3 #claudecode #iaparadevs #kimik3 #devtools #parati
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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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