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YOLO26 — Built for Edge Deployment Ultralytics’ latest YOLO model shifts the focus from just accuracy to efficient, real-world deployment. In this carousel, I’ve highlighted: • Training-level improv
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Most Large Language Models generate text by predicting the next token. But fluency is not the same as understanding. Meta’s VL-JEPA takes a different approach — learning semantic representations, wh
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📢 Important Update for Code With Aarohi Followers My GitHub account was suspended, and I know many of you faced broken links — sorry for the inconvenience! You can now download tutorial codes dir
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🤖 Why are LLMs called autoregressive models? Because they generate text one token at a time, and each new token depends on all the previous ones. In simple terms — the model uses its own past output
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🧠 How does a computer actually understand language? When we read, we instantly know what sounds right — like “the tea is very hot” — but computers don’t understand language like we do. That’s where
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Ever wondered how computers understand language? Why does “The tea is very hot” sound right, but “Hot very is tea the” doesn’t? That’s exactly what language models learn — predicting the next word, o
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From Word Embeddings to Sentence Embeddings | AI Evolution Explained Earlier AI models like Word2Vec gave one vector per word — but that ignored context. Modern AI models like BERT and GPT changed eve
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Why LLMs Need Vector Databases? How do AI systems like ChatGPT store and find relevant information? They use Vector Databases — tools that store data as embeddings (vectors) and find similar meanings
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What Are Embeddings in AI? How does AI understand language? In this video, you’ll learn what embeddings are — the secret behind how models like ChatGPT, GPT-4, and Claude understand meaning. Embedding
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How does ChatGPT actually learn what humans like? What is RLHF? It’s not magic — it’s RLHF, or Reinforcement Learning from Human Feedback. In this short, I’ll explain how humans help train AI models b
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What’s the difference between Agentic AI and AI Agents? Both sound similar — but they’re not the same! 🧠 Agentic AI is the idea that AI shouldn’t just give answers — it should think, plan, and take
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Normal AI just answers questions… 🤖 But Agentic AI can plan, reason, and take action on its own! 🚀 #AgenticAI #ArtificialIntelligence #CodeWithAarohi #AITools #futureofai
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About @codewithaarohi

Aarohi | AI & Tech Creator is a Instagram nano influencer. With 1.4K followers and 39 posts, codewithaarohi's account shows a follower-to-following ratio of 20.9:1. View all content anonymously on Pictame - no login required.

codewithaarohi's engagement rate sits at 1.84%. For accounts with 1K-10K followers, the average is around 5%, so there's some room to grow — though every community is unique.

Out of the last 12 posts, 67% are videos and 33% are photos. Notably, videos tend to get 4.3x more engagement than photos. Content shows up about every 7 days. Captions lean moderate, averaging 477 characters.

1.84% engagement rate — room to grow compared to average for 1K-10K follower accounts.
67% videos, 33% photos. Videos get 4.3x more engagement here.
Posts about every 7 days.
20.9:1 follower-to-following ratio.

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codewithaarohi
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@codewithaarohi

Aarohi | AI & Tech Creator

Public
Posts
39
Followers
1.4K
Top Hashtags
#AI#MachineLearning#ArtificialIntelligence#ChatGPT#Python#LLM#DataScience#DeepLearning

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Popular Hashtags

#ootd#streetstyle#blogger#influencer#photographer#naturephotography#landscape#travelphotography#architecture#portrait#wanderlust
Following
66
Avg. Likes
23
Avg. Comments
2
Engagement
1.81%

🤖 Simplyfing Artificial Intelligence 💡 Learn Generative & Agentic AI 🔗 Watch full videos on YouTube 👇 🎬 YouTube: ...

www.youtube.com/@CodeWithAaroh...
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