🚀 Sber has released two open-source MoE models: GigaChat-3.1 Ultra and Lightning

Both code and weights are available under the MIT license on HuggingFace.

👉 Key details:

• Trained from scratch (not a finetune) on proprietary data and infrastructure
• Mixture-of-Experts (MoE) architecture

Models:

🧠 GigaChat-3.1 Ultra
• 702B MoE model for high-performance environments
• Outperforms DeepSeek-V3-0324 and Qwen3-235B on math and reasoning benchmarks
• Supports FP8 training and MTP

⚡️ GigaChat-3.1 Lightning
• 10B model (1.8B active parameters)
• Outperforms Qwen3-4B and Gemma-3-4B on Sber benchmarks
• Efficient local inference
• Up to 256k context

Engineering highlights:

• Custom metric to detect and reduce generation loops
• DPO training moved to native FP8
• Improvements in post-training pipeline
• Identified and fixed a critical issue affecting evaluation quality

🌍 Trained on 14 languages (optimized for English and Russian)

Use cases:

• chatbots
• AI assistants
• copilots
• internal ML systems

Sber provides a solid open foundation for developers to build production-ready AI systems with lower infrastructure costs.

AI Agents for Beginners

This is Microsoft's official, structured course designed to teach AI agents from the ground up. 🎓 It provides a comprehensive curriculum covering fundamentals to deployment through exclusive video tutorials with hands-on code examples. The course is entirely free and accessible without registration. It is ideal for beginners and intermediate developers seeking to understand how AI agents reason, utilize tools, and automate real-world tasks. 🤖

Prerequisites: Basic command line experience is beneficial, though no prior AI experience is required.

📚 12 structured lessons
🏃‍♂️ Self-paced with immediate access
👨‍🏫 Created by: Microsoft Developer Team
🔗 Course Link
https://github.com/microsoft/ai-agents-for-beginners

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🚀 Thrilled to announce my latest strategic pivot into the exciting realm of Functional Programming with Python! 🐍✨

I am proud to share a transformative journey focused on elevating our codebase to new heights of readability and long-term maintainability. By aligning our development priorities with the core pillars of functional programming, we are unlocking a powerful new chapter in our engineering evolution. 💡📈

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Functional Programming with Python

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This bot will help you get a course that's available for free for a limited time so you can register before others.

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🔅 Getting Started with Vibe Coding

📝 Master the art of vibe coding, where you direct artificial intelligence to develop applications while the system manages the complex coding processes.

Привіт 👋
Запрошую тебе в канал SYBONE’S GIFTS 💎🎁
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Today, the public mint for Lobsters on TON goes live on Getgems 🦞

This is not just another NFT drop.
In my view, Lobsters is one of the first truly cohesive products at the intersection of blockchain, NFTs, and AI.

Here, the NFT is not just an image and not just a collectible.
Each Lobster is an NFT with a built-in AI agent inside: a digital character with its own soul, on-chain biography, persistent memory, and a unified identity across Telegram, Mini App, Claude, and API.

So you are not just getting an asset in your wallet.
You are getting an AI-native digital character that can interact, remember, and stay consistent across different interfaces.

What makes this especially interesting is the timing.

In the recent video Pavel Durov shared in his post about agentic bots in Telegram, the lobster imagery was right there. Against that backdrop, Lobsters does not feel like a random mint — it feels like a very precise fit for the new narrative:

Telegram-native agents + TON infrastructure + NFT ownership layer + AI utility

Put simply, this is one of the first real attempts to turn an NFT from “just an image” into a digital agent.

Public mint: today, 16:00
Price: 50 TON

👉 Mint your Lobster on Getgems 🦞🦞🦞