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Browse our collection of articles and blog posts on artificial intelligence, machine learning, and more.

Biophysical Brain Models Get a 2000× Speed Boost: Researchers from NUS, UPenn, and UPF Introduce DELSSOME to Replace Numerical Integration with Deep Learning Without Sacrificing Accuracy

Biophysical Brain Models Get a 2000× Speed Boost: Researchers from NUS, UPenn, and UPF Introduce DELSSOME to Replace Numerical Integration with Deep Learning Without Sacrificing Accuracy

Biophysical Brain Models Get a 2000× Speed Boost: Researchers from NUS, UPenn, and UPF Introduce DELSSOME to Replace Numerical Integration with Deep Learning Without Sacrificing Accuracy

OpenAI Introduces o3 and o4-mini: Progressing Towards Agentic AI with Enhanced Multimodal Reasoning

OpenAI Introduces o3 and o4-mini: Progressing Towards Agentic AI with Enhanced Multimodal Reasoning

OpenAI Introduces o3 and o4-mini: Progressing Towards Agentic AI with Enhanced Multimodal Reasoning

Model Performance Begins with Data: Researchers from Ai2 Release DataDecide—A Benchmark Suite to Understand Pretraining Data Impact Across 30K LLM Checkpoints

Model Performance Begins with Data: Researchers from Ai2 Release DataDecide—A Benchmark Suite to Understand Pretraining Data Impact Across 30K LLM Checkpoints

Model Performance Begins with Data: Researchers from Ai2 Release DataDecide—A Benchmark Suite to Understand Pretraining Data Impact Across 30K LLM Checkpoints

MIT Researchers Introduce DISCIPL: A Self-Steering Framework Using Planner and Follower Language Models for Efficient Constrained Generation and Reasoning

MIT Researchers Introduce DISCIPL: A Self-Steering Framework Using Planner and Follower Language Models for Efficient Constrained Generation and Reasoning

MIT Researchers Introduce DISCIPL: A Self-Steering Framework Using Planner and Follower Language Models for Efficient Constrained Generation and Reasoning

SyncSDE: A Probabilistic Framework for Task-Adaptive Diffusion Synchronization in Collaborative Generation

SyncSDE: A Probabilistic Framework for Task-Adaptive Diffusion Synchronization in Collaborative Generation

SyncSDE: A Probabilistic Framework for Task-Adaptive Diffusion Synchronization in Collaborative Generation

A Coding Implementation for Building Python-based Data and Business intelligence BI Web Applications with Taipy: Dynamic Interactive Time Series Analysis, Real-Time Simulation, Seasonal Decomposition, and Advanced Visualization

A Coding Implementation for Building Python-based Data and Business intelligence BI Web Applications with Taipy: Dynamic Interactive Time Series Analysis, Real-Time Simulation, Seasonal Decomposition, and Advanced Visualization

A Coding Implementation for Building Python-based Data and Business intelligence BI Web Applications with Taipy: Dynamic Interactive Time Series Analysis, Real-Time Simulation, Seasonal Decomposition, and Advanced Visualization

OpenAI Releases Codex CLI: An Open-Source Local Coding Agent that Turns Natural Language into Working Code

OpenAI Releases Codex CLI: An Open-Source Local Coding Agent that Turns Natural Language into Working Code

OpenAI Releases Codex CLI: An Open-Source Local Coding Agent that Turns Natural Language into Working Code

A faster way to solve complex planning problems

A faster way to solve complex planning problems

MIT researchers developed a machine-learning-guided technique to solve complex, long-horizon planning problems more efficiently than some traditional approaches, while arriving at an optimal solution that better meets a user’s goals.

SQL-R1: A Reinforcement Learning-based NL2SQL Model that Outperforms Larger Systems in Complex Queries with Transparent and Accurate SQL Generation

SQL-R1: A Reinforcement Learning-based NL2SQL Model that Outperforms Larger Systems in Complex Queries with Transparent and Accurate SQL Generation

SQL-R1: A Reinforcement Learning-based NL2SQL Model that Outperforms Larger Systems in Complex Queries with Transparent and Accurate SQL Generation

Transformers Can Now Predict Spreadsheet Cells without Fine-Tuning: Researchers Introduce TabPFN Trained on 100 Million Synthetic Datasets

Transformers Can Now Predict Spreadsheet Cells without Fine-Tuning: Researchers Introduce TabPFN Trained on 100 Million Synthetic Datasets

Transformers Can Now Predict Spreadsheet Cells Without Fine-Tuning: Researchers Introduce TabPFN Trained on 100 Million Synthetic Datasets