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𝐀𝐈 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬 ⚡ ⭐ Bard becomes Gemini 📖 AI uncovers ancient texts 📸 Meta will label AI-generated images 🎵 Grammy's AI challenge 👯 OpenAI is developing 2 AI agents Take advantage of these exclusive insights! #LLMs #AI #MLOps #MachineLearning #TechInnovation #DataScience #webdev #webdeveloper #pythonprogramming #pythonquiz #ai #DataScience #CodeNewbies #CodingJourney #codinglife @ThePSF @Tesla_AI @ThePSF @OpenAIDevs @machinelearnTec @vaticanxx @coursera @udacity @startupindia

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Celebrating a Milestone: ChatGPT Hits 100 Million Active Users in Just 2 Months! 🚀🎉 Incredible news! ChatGPT has reached an astounding 100 million active users in a mere two months! Let's dive into how ChatGPT works, broken down into 5 simple parts: 🔹 Part 1: The Core of ChatGPT ChatGPT runs on sophisticated LLMs like GPT-3.5 or GPT-4. Take GPT-3.5, for example, with its 175 billion parameters across 96 layers, it's one of the most comprehensive deep-learning models around. Its fundamental technology? Transformer architecture, notable for its self-attention mechanism. 🔹 Part 2: Word Encoding and Self Attention The journey begins by converting input sentences into numerical embeddings, encapsulating the significance of each token. This transformation aids the model in understanding language in a format it can process. Self-attention then evaluates the importance of different parts of the input, interpreting relationships within the data. 🔹 Part 3: Reinforcement Learning from Human Feedback To mitigate undesirable outputs, GPT-3.5 undergoes fine-tuning through Reinforcement Learning from Human Feedback (RLHF). This method aligns the model more closely with human values, employing a reward model that steers it towards outputs that resonate with human feedback. 🔹 Part 4: The Training Process ChatGPT's training involves massive datasets of internet text, through which it learns patterns, contexts, and the intricacies of human language. Initial training on this vast data helps grasp general language patterns, followed by specific task-oriented fine-tuning. 🔹 Part 5: Low Latency Responses Achieving low latency hinges on advanced backend infrastructure. High-throughput, low-latency networks, bolstered by NVIDIA GPUs and linked by the NVIDIA Quantum-2 InfiniBand network, ensure efficient operations. ChatGPT also employs SSE for seamless, real-time updates from the server to the client. Astonishing progress for ChatGPT, and a big thank you to the incredible community that has supported this journey. Looking forward to more groundbreaking achievements! 💡✨ #openai #ChatGPT #Milestone #AI #Innovation #Technology @gdb @OpenAIDevs @OpenAI #LLMs #AI #MLOps #MachineLearning #TechInnovation #DataScience #webdev #webdeveloper #pythonprogramming #pythonquiz #ai #DataScience #CodeNewbies #CodingJourney #codinglife @ThePSF @Tesla_AI @ThePSF @OpenAIDevs @machinelearnTec @vaticanxx @udacity @_StartUpIndia @ChatGPTapp @Chain_GPT @dalle_openai @OpenAIDevs