Machine Learning

AI Infrastructure

AI Model Hosting Guide: Local and Cloud Inference Strategies

Master the essentials of deploying AI models for efficient inference. This guide covers local hosting, cloud deployment options, and optimization strategies for production-ready AI systems.

LLM Agents

New Research Quantifies Cost vs Accuracy Tradeoffs in Agentic LLM

ArXiv paper examines how design decisions in agentic LLM search systems impact both accuracy and computational costs, providing quantitative framework for budget-constrained deployments.

AI Agents

Building Risk-Aware AI Agents: Internal Critics & Uncertainty

Learn to build AI agents that know when they're uncertain. This technical guide covers internal critic mechanisms, self-consistency reasoning, and uncertainty estimation for reliable AI decision-making.

LLM

LLM Quantization Explained: FP32, FP16, BF16, and INT8 Formats

Understanding numeric precision formats is crucial for deploying AI models efficiently. Learn how FP32, FP16, BF16, and INT8 quantization affects model performance, memory usage, and inference speed.

AI Safety

LLM Safety Judges Are No Better Than Coin Flips, Study Finds

New research reveals LLM-based safety evaluators fail to reliably measure adversarial robustness, raising critical questions about automated AI safety testing methodologies.

Andrej Karpathy

Karpathy's Autoresearch: AI Agents Run ML Experiments Solo

Andrej Karpathy releases Autoresearch, a 630-line Python tool enabling AI agents to autonomously run machine learning experiments on single GPUs, democratizing ML research.

Yann LeCun

LeCun Challenges AGI Definition, Proposes SAI Framework

Meta's Chief AI Scientist Yann LeCun argues AGI is fundamentally misdefined in new research paper, introducing Superhuman Adaptable Intelligence as alternative framework for measuring AI progress.

AI Research

Model Medicine: Diagnosing AI Systems Like Clinical Patients

New research proposes treating AI models as clinical patients, introducing systematic diagnostic and treatment protocols for understanding model behavior, identifying failures, and applying targeted interventions.

Machine Learning

Neural Network Collapse: Why AI Systems Forget What They Learn

New research investigates representation collapse in continual learning, revealing why neural networks catastrophically forget previous tasks and proposing mechanisms to understand this fundamental limitation.

AI Agents

SkillNet Framework Enables Modular AI Skill Networks

New research introduces SkillNet, a framework for creating, evaluating, and connecting modular AI skills that can be composed into complex agent capabilities.

LLM evaluation

New Method Automatically Discovers How LLM Judges Evaluate AI Con

Researchers introduce an automated framework for discovering the hidden concepts LLM evaluators use when judging AI outputs, enabling better understanding and improvement of AI content assessment systems.

LLM Agents

PlugMem: Modular Memory Architecture for Persistent LLM Agents

New research introduces PlugMem, a task-agnostic plugin memory module enabling LLM agents to maintain context across sessions without task-specific training.