Post-training Large Language Models (LLMs) for long-horizon agentic tasks—such as software engineering, web browsing, and complex tool use—presents a persistent […]
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Google Introduces TurboQuant: A New Compression Algorithm that Reduces LLM Key-Value Cache Memory by 6x and Delivers Up to 8x Speedup, All with Zero Accuracy Loss
The scaling of Large Language Models (LLMs) is increasingly constrained by memory communication overhead between High-Bandwidth Memory (HBM) and SRAM. […]
Paged Attention in Large Language Models LLMs
When running LLMs at scale, the real limitation is GPU memory rather than compute, mainly because each request requires a […]
A Coding Implementation to Design Self-Evolving Skill Engine with OpenSpace for Skill Learning, Token Efficiency, and Collective Intelligence
In this tutorial, we explore OpenSpace, a self-evolving skill engine developed by HKUDS that makes AI agents smarter, more cost-efficient, […]
This AI Paper Introduces TinyLoRA, A 13-Parameter Fine-Tuning Method That Reaches 91.8 Percent GSM8K on Qwen2.5-7B
Researchers from FAIR at Meta, Cornell University, and Carnegie Mellon University have demonstrated that large language models (LLMs) can learn […]
Yann LeCun’s New LeWorldModel (LeWM) Research Targets JEPA Collapse in Pixel-Based Predictive World Modeling
World Models (WMs) are a central framework for developing agents that reason and plan in a compact latent space. However, […]
Meta AI’s New Hyperagents Don’t Just Solve Tasks—They Rewrite the Rules of How They Learn
The dream of recursive self-improvement in AI—where a system doesn’t just get better at a task, but gets better at […]
Luma Labs Launches Uni-1: The Autoregressive Transformer Model that Reasons through Intentions Before Generating Images
In the field of generative AI media, the industry is transitioning from purely probabilistic pixel synthesis toward models capable of […]
How BM25 and RAG Retrieve Information Differently?
When you type a query into a search engine, something has to decide which documents are actually relevant — and […]
Implementing Deep Q-Learning (DQN) from Scratch Using RLax JAX Haiku and Optax to Train a CartPole Reinforcement Learning Agent
In this tutorial, we implement a reinforcement learning agent using RLax, a research-oriented library developed by Google DeepMind for building […]