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- ☑ 10 Mins AI Read: Aliaba's Qwen3 and Qwen2.5-Omni-3B released, Xiaomi Releases MiMo-7B....
☑ 10 Mins AI Read: Aliaba's Qwen3 and Qwen2.5-Omni-3B released, Xiaomi Releases MiMo-7B....
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Dive into the hottest AI breakthroughs of the week—handpicked just for you!
Top 5 AI News 🔥
Large Language Models
🧵 Alibaba Qwen Team Just Released Qwen3: The Latest Generation of Large Language Models in Qwen Series, Offering a Comprehensive Suite of Dense and Mixture-of-Experts (MoE) Models
⇧2,800 Likes
LLM & Infra
🧵 Alibaba Qwen Announce the Release of Qwen2.5-Omni-3B, Enabling Developers with Lightweight GPU Accessibility
⇧2,650 Likes
Agentic AI
🧵 Diagnosing and Self- Correcting LLM Agent Failures: A Technical Deep Dive into τ-Bench Findings with Atla’s EvalToolbox
⇧2,334 Likes
Language Models
🧵 Xiaomi Releases MiMo-7B, A New Language Model for Reasoning Tasks
⇧2,100 Likes
Coding Agents
🧵 Can Coding Agents Improve Themselves? Researchers from University of Bristol and iGent AI Propose SICA (Self-Improving Coding Agent) that Iteratively Enhances Its Own Code and Performance
⇧1,800 Likes
Editor’s Pick
🧵 Meet Parlant: The Fully Open-Sourced Conversation Modeling Engine
⇧1,500 Likes
New Release LLM
Alibaba Qwen Team Just Released Qwen3: The Latest Generation of Large Language Models in Qwen Series, Offering a Comprehensive Suite of Dense and Mixture-of-Experts (MoE) Models
Qwen3, the latest release in the Qwen family of models developed by Alibaba Group, aims to systematically address these limitations. Qwen3 introduces a new generation of models specifically optimized for hybrid reasoning, multilingual understanding, and efficient scaling across parameter sizes. The Qwen3 series expands upon the foundation laid by earlier Qwen models, offering a broader portfolio of dense and Mixture of Experts (MoE) architectures. Designed for both research and production use cases, Qwen3 models target applications that require adaptable problem-solving across natural language, coding, mathematics, and broader multimodal domains.
Empirical Results and Benchmark Insights
Benchmarking results illustrate that Qwen3 models perform competitively against leading contemporaries:
▶ The Qwen3-235B-A22B model achieves strong results across coding (HumanEval, MBPP), mathematical reasoning (GSM8K, MATH), and general knowledge benchmarks, rivaling DeepSeek-R1 and Gemini 2.5 Pro series models.
▶ The Qwen3-72B and Qwen3-72B-Chat models demonstrate solid instruction-following and chat capabilities, showing significant improvements over the earlier Qwen1.5 and Qwen2 series.
▶ Notably, the Qwen3-30B-A3B, a smaller MoE variant with 3 billion active parameters, outperforms Qwen2-32B on multiple standard benchmarks, demonstrating improved efficiency without a trade-off in accuracy.
⇧ 1,449 Likes
Top 5 AI Coding Tutorials </>
🖥️ How to Create a Custom Model Context Protocol (MCP) Client Using Gemini
⇧ 1,249 Likes
🖥️ Tutorial on Seamlessly Accessing Any LinkedIn Profile with exa-mcp-server and Claude Desktop Using the Model Context Protocol MCP
⇧ 1,139 Likes
🖥️ A Coding Guide to Different Function Calling Methods to Create Real-Time, Tool-Enabled Conversational AI Agents
⇧ 1,049 Likes
🖥️ Implementing Persistent Memory Using a Local Knowledge Graph in Claude Desktop
⇧ 1,031 Likes
🖥️ A Coding Tutorial of Model Context Protocol Focusing on Semantic Chunking, Dynamic Token Management, and Context Relevance Scoring for Efficient LLM Interactions
⇧ 945 Likes
5 Trendning AI Guides/Reports 📖
⁍ Microsoft Releases a Comprehensive Guide to Failure Modes in Agentic AI Systems
⇧ 835 Likes
⁍ Beyond the Hype: Google’s Practical AI Guide Every Startup Founder Should Read
⇧ 815 Likes
⁍ Anthropic Releases a Comprehensive Guide to Building Coding Agents with Claude Code
⇧ 785 Likes
⁍ OpenAI Releases a Practical Guide to Identifying and Scaling AI Use Cases in Enterprise Workflows
⇧ 675 Likes
⁍ OpenAI Releases a Practical Guide to Building LLM Agents for Real-World Applications
⇧ 575 Likes
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