Generative AI is reshaping industries, but it’s not without its hurdles. Here’s a quick look at the key challenges we’re tackling.

LLMs are revolutionizing industries by enabling smarter chatbots, content creation, coding assistance, and so much more. The future of AI is here, and it’s only getting better! 🌟 What’s your favorite use case for LLMs? Let’s discuss in the comments! 👇

8️⃣ Feedback Loop: The output can be refined further by feeding it back into the model for iterative improvements.

7️⃣ Output Text: Voilà! The model generates a coherent and contextually relevant response.

6️⃣ Prediction Head: The model predicts the next word or sequence of words based on the processed data.

5️⃣ Attention Mechanism: The model focuses on the most relevant parts of the input to generate context-aware responses.

4️⃣ Transformer Layers: The magic happens here! Multiple layers of transformers process the data, using self-attention to understand relationships between words.

3️⃣ Embedding Layer: These tokens are converted into numerical vectors that capture their meaning and context.

2️⃣ Tokenization: The input text is broken down into smaller pieces called tokens (words or subwords).

1️⃣ Input Prompt: It all starts with you! You provide a prompt or question, and the LLM takes it from there.

Ever wondered how tools like ChatGPT or other Large Language Models (LLMs) generate such human-like text? Let’s break it down step by step! 🤖✨ #AI #MachineLearning #LLM #ArtificialIntelligence #TechInnovation #ChatGPT #DataScience #Transformers #FutureOfTech

#GenerativeAI #AIChallenges #EthicalAI #Innovation #TechForGood

Generative AI holds immense potential, but responsible adoption is key. Let’s collaborate to address these challenges and drive positive change. 💡 hashtag#GenerativeAI hashtag#AIChallenges hashtag#EthicalAI hashtag#Innovation hashtag#TechForGood

🎨 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 Balancing creativity & intellectual property Building user trust & interpretability Seamless integration into existing systems

📜 𝐑𝐞𝐠𝐮𝐥𝐚𝐭𝐨𝐫𝐲 Compliance with data laws & standards Ensuring transparency & accountability Establishing ethical guidelines

⚖️ 𝐄𝐭𝐡𝐢𝐜𝐚𝐥 Bias & fairness in response Privacy & data security Misinformation (deepfakes, fake news)

🔧 𝐓𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 Data quality (bias, noise, scarcity) Model complexity (training time, resources) Scalability (large datasets, real-time processing)

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I've just published a new blog post on building AI conversational search using IBM watsonx Discovery and the Granite model. Dive into the details here: https://t.co/mIYRQ0CiUt #AI #ConversationalAI #IBM #watsonx #GraniteModel