Artificial Intelligence & Machine Learning

🚀 GigaChat 3.5 Reasoning — a new open-source LLM that thinks before it answers. It breaks problems into stages, builds a plan, checks intermediate results, and self-corrects. Built on GigaChat 3.5 Ultra, it explores multiple step-by-step reasoning paths for math & coding, using automated verification to reinforce correct answers. ⚡️ Proprietary linear attention makes it highly efficient on long contexts, retaining key points without re-matching from scratch. It’s also token-efficient: uses 37% fewer tokens than DeepSeek V4 Flash Preview on math problems! 📈 Benchmark gains over non-reasoning version: • IFBench: 44 → 77 • Natural Plan: 64 → 80 • LiveCodeBench v6: 56 → 85 📦 MIT license. Weights on Hugging Face: fp8 | bf16

even though the wording isn't identical. 🔟 BUILD A SIMPLE RAG SYSTEM A beginner-friendly RAG pipeline looks like: 📄 Documents ↓ Split into smaller sections ↓ Create embeddings ↓ Store vectors ↓ User asks a question ↓ Find relevant sections ↓ Provide them to the model ↓ Generate answer You don't need to build the most sophisticated RAG system on your first attempt. Understand the basic pipeline first. 1️⃣1️⃣ ADD TOOLS WHEN NEEDED Suppose your AI assistant needs information it cannot know by itself. Give it tools. For example: 🔎 Search 🗄️ Database lookup 🌤️ Weather API 📅 Calendar 🧮 Calculator Now your application becomes more capable. 1️⃣2️⃣ DON'T CONFUSE CHATBOTS WITH AGENTS A chatbot may simply: Input → Model → Response An agentic application may: Goal → Plan → Tool → Result → Next action → Final response Agents are useful for multi-step tasks, but they also introduce additional complexity. 👉 Start simple before building agents. 1️⃣3️⃣ ADD VALIDATION Never assume the AI response is automatically correct. Validate important outputs. For example: If the model is extracting: Name → Email → Amount → Date your application should check whether those fields have valid formats. 1️⃣4️⃣ HAND

🤖💻 HOW TO BUILD YOUR FIRST AI PROJECT — A BEGINNER'S ROADMAP 🚀 You know Python. You've learned the basics of AI. You've experimented with prompts. Now comes the important question: How do you actually build an AI application? You don't need to start with a complicated AI agent. Start with a simple project and understand every layer. 1️⃣ START WITH A REAL PROBLEM Don't begin with: ❌ "I want to use an LLM." Begin with: ✅ "What problem can AI solve?" Examples: • Summarize documents • Answer questions about a knowledge base • Classify customer feedback • Extract information from invoices • Generate product descriptions • Analyze support tickets 👉 The problem comes before the technology. 2️⃣ CHOOSE YOUR INPUT Determine what information your application will receive. It could be: 📝 Text 📄 Documents 🖼️ Images 🎙️ Audio 📊 Structured data 🌐 API data Your input determines how your application should process the information. 3️⃣ CHOOSE THE AI MODEL Different tasks may require different model capabilities. For example: Text generation → Language model Image understanding → Vision-capable model Speech processing → Speech model Semantic search → Embedding model 👉 Don't choose a model simply becau

In the previous post, we learned about Python data types and how different kinds of data are stored. Now, let's learn how to interact with users by taking input and displaying output. 📖 Phase 1: Programming Fundamentals 📌 Topic 6: Input & Output Every program performs two basic operations: • Input – Receiving data from the user. • Output – Displaying information to the user. For example, when you enter your username and password on a website, that's input. When the website displays "Login Successful," that's output. Output in Python Python uses the print() function to display output on the screen. Example: print("Hello, World!") Output: Hello, World! You can also print numbers and variables. name = "Surya" age = 25 print(name) print(age) Output: Surya 25 Printing Multiple Values name = "Ajay" age = 25 print("Name:", name) print("Age:", age) Output: Name: Ajay Age: 25 Input in Python Python uses the input() function to accept input from the user. Example: name = input("Enter your name: ") print("Hello,", name) Sample Output: Enter your name: Deepak Hello, Deepak Taking Numeric Input By default, input() returns a string. age = input("Enter your age: ") print(type(age)) # To use it as

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