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- ☑ 10 Mins AI Read: Microsoft AI Released Phi-4-Reasoning and DeepSeek Released DeepSeek-Prover-V2
☑ 10 Mins AI Read: Microsoft AI Released Phi-4-Reasoning and DeepSeek Released DeepSeek-Prover-V2
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Dive into the hottest AI breakthroughs of the week—handpicked just for you!
Top 5 AI News 🔥
Sponsored
🧵 Diagnosing and Self- Correcting LLM Agent Failures: A Technical Deep Dive into τ-Bench Findings with Atla’s EvalToolbox
⇧2,900 Likes
OpenSource
🧵 Meta AI Introduces ReasonIR-8B: A Reasoning-Focused Retriever Optimized for Efficiency and RAG Performance
⇧2,800 Likes
LLM & Reasoning
🧵 Microsoft AI Released Phi-4-Reasoning: A 14B Parameter Open-Weight Reasoning Model that Achieves Strong Performance on Complex Reasoning Tasks
⇧2,650 Likes
AI App
🧵 Meta AI Introduces First Version of Its Llama 4-Powered AI App: A Standalone AI Assistant to Rival ChatGPT. [Download the app]
⇧2,354 Likes
Open Source AI
🧵 DeepSeek-AI Released DeepSeek-Prover-V2: An Open-Source Large Language Model Designed for Formal Theorem, Proving through Subgoal Decomposition and Reinforcement Learning
⇧2,100 Likes
Coding Agents
🧵 Xiaomi introduced MiMo-7B: A Compact Language Model that Outperforms Larger Models in Mathematical and Code Reasoning through Rigorous Pre-Training and Reinforcement Learning
⇧1,800 Likes
Sponsored
🧵 Meet Parlant: The Fully Open-Sourced Conversation Modeling Engine
⇧1,500 Likes
Meta AI
Meta AI Introduces ReasonIR-8B: A Reasoning-Focused Retriever Optimized for Efficiency and RAG Performance
Meta AI has released ReasonIR-8B, a retriever model designed explicitly for reasoning-intensive information retrieval. Trained from LLaMA3.1-8B, the model establishes new performance standards on the BRIGHT benchmark, achieving a normalized Discounted Cumulative Gain (nDCG@10) of 36.9 when used with a lightweight Qwen2.5 reranker. Notably, it surpasses leading reranking models such as Rank1-32B while offering 200× lower inference-time compute, making it significantly more practical for scaled RAG applications.
ReasonIR-8B is trained using a novel data generation pipeline, ReasonIR-SYNTHESIZER, which constructs synthetic queries and document pairs that mirror the challenges posed by real-world reasoning tasks. The model is released open-source on Hugging Face, along with training code and synthetic data tools, enabling further research and reproducibility.
⇧ 1,449 Likes
LLM and Reasoning
DeepSeek-AI Released DeepSeek-Prover-V2: An Open-Source Large Language Model Designed for Formal Theorem, Proving through Subgoal Decomposition and Reinforcement Learning
A team of researchers from DeepSeek-AI has introduced a new model, DeepSeek-Prover-V2, designed to generate formal mathematical proofs by leveraging subgoal decomposition and reinforcement learning. The core of their approach utilizes DeepSeek-V3 to break down a complex theorem into manageable subgoals, each of which is translated into a “have” statement in Lean 4 with a placeholder indicating that the proof is incomplete. These subgoals are then passed to a 7B-sized prover model that completes each proof step. Once all steps are resolved, they are synthesized into a complete Lean proof and paired with the original natural language reasoning generated by DeepSeek-V3. This forms a rich cold-start dataset for reinforcement learning. Importantly, the model’s training is entirely bootstrapped from synthetic data, with no human-annotated proof steps used.
⇧ 1,449 Likes
Top 5 AI Coding Tutorials </>
🖥️ Building a REACT-Style Agent Using Fireworks AI with LangChain that Fetches Data, Generates BigQuery SQL, and Maintains Conversational Memory
🖥️ A Step-by-Step Coding Guide to Integrate Dappier AI’s Real-Time Search and Recommendation Tools with OpenAI’s Chat API
🖥️ How to Create a Custom Model Context Protocol (MCP) Client Using Gemini
🖥️ Tutorial on Seamlessly Accessing Any LinkedIn Profile with exa-mcp-server and Claude Desktop Using the Model Context Protocol MCP
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Top 5 Trending AI Guides/Reports 📖
⁍ Building the Internet of Agents: A Technical Dive into AI Agent Protocols and Their Role in Scalable Intelligence Systems
⁍ Microsoft Releases a Comprehensive Guide to Failure Modes in Agentic AI Systems
⁍ Beyond the Hype: Google’s Practical AI Guide Every Startup Founder Should Read
⁍ Anthropic Releases a Comprehensive Guide to Building Coding Agents with Claude Code
⁍ OpenAI Releases a Practical Guide to Identifying and Scaling AI Use Cases in Enterprise Workflows
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