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12 articles
OpenAI's GPT-5.6 enhances AI efficiency across models, inference, and agentic workflows, delivering more useful intelligence per dollar. The update marks a significant step toward sustainable and cost-effective AI development.
Developers have successfully deployed the 1-bit Bonsai-27B language model using PrismML’s fork of llama.cpp, enabling efficient local inference with OpenAI-compatible workflows.
This article explains Mixture of Experts (MoE) AI models, how they work like teams of specialists, and why they're important for efficient AI performance.
Learn how Baidu's Unlimited OCR achieves efficient processing of dozens of document pages in a single pass by mimicking human memory and forgetting mechanisms.
This explainer explores how Un0, a new AI system from Databricks' former AI chief, achieves 1,000x energy efficiency improvements through novel architectural approaches that could revolutionize AI development and deployment.
Google DeepMind introduces DiffusionGemma, a 26 billion parameter open model using text diffusion to achieve up to 4x faster text generation on GPUs.
Learn how a new AI system enables faster and more efficient continual learning by running multiple experiments at once using LoRA adapters.
Learn how Parcae, a new AI architecture, helps language models become more efficient and powerful without needing to be twice the size. Understand how this breakthrough could make AI more sustainable and accessible.
Google's Veo 3.1 Lite cuts video generation costs by more than half while maintaining speed and performance, making AI video creation more accessible.
This article explains Alibaba's Qwen 3.5 Small Model Series, a new approach to AI model design that emphasizes efficiency and on-device deployment over traditional large-scale parameter increases.
Learn about SPCT (Sparse Prompt Compression Technique), a new method developed by DeepSeek AI that improves the scalability of reward models during inference, making AI systems more efficient and cost-effective.
As language models gain the ability to process massive context windows, experts argue that selective retrieval methods like RAG remain more efficient and reliable than simply dumping all data into prompts.
