Learn how to run and optimize VLMs like SmolVLM on Intel CPUs using OpenVINO and Optimum with quantization techniques for better performance.
VLM on Intel CPUs: Can You Run Models Without a GPU? Read More »
Explore Kimina-Prover-RL, a Lean 4 training pipeline using reinforcement learning and structured reasoning to improve formal theorem proving models.
Kimina Prover RL: Is Reinforcement Learning the Key to Lean 4? Read More »
Can code models be trusted without execution? We compare LLMs with live code outputs to reveal the real top performers in AI-generated code.
Code Generation Models: Which One Truly Works? Read More »
Can AI really help you build games with vibe coding? Discover platform pros, cons, and how VibeGame tries to solve key issues in AI game dev.
Vibe Coding Games: Does It Actually Work? Read More »
Learn how to convert OCR models like dots.ocr from PyTorch to Core ML for on-device use with Apple Neural Engine and MLX.
Core ML OCR: Is Converting PyTorch Models Worth It? Read More »
Discover how TTRL search transforms theorem proving with reusable lemmas, error-fixing, and formal logic breakthroughs in Kimina-Prover-72B.
Test-Time Reinforcement Learning: Is TTRL the Future of AI Proving? Read More »
Discover how the RTEB benchmark improves retrieval evaluation for embedding models in real-world and enterprise AI scenarios.
Retrieval Evaluation: Is RTEB the New Gold Standard? Read More »
Can Qwen3-8B run faster with speculative decoding and pruning? Learn how Intel® Core™ Ultra boosts local agent performance using OpenVINO.
Qwen3-8B Acceleration: Is Speculative Decoding Worth It? Read More »
Scaleway is now a Hugging Face Inference Provider. Learn how it works, pricing, features, and if it’s right for your AI workflows.
Scaleway Inference Provider: Is It Worth It? Read More »
Swift Transformers 1.0 is here. Learn how this Swift library powers local AI on Apple devices with Core ML and MLX support.
Swift Transformers: Is It Ready for Developers? Read More »
