Inference efficiency has quietly become one of the most consequential bottlenecks in AI deployment. As agentic coding systems such as […]
Category: Software Engineering
OpenAI Introduces MRC (Multipath Reliable Connection): A New Open Networking Protocol for Large-Scale AI Supercomputer Training Clusters
Training frontier AI models is not just a compute problem — it is increasingly a networking problem. And OpenAI just […]
Zyphra Releases ZAYA1-8B: A Reasoning MoE Trained on AMD Hardware That Punches Far Above Its Weight Class
Zyphra AI has released ZAYA1-8B, a small Mixture of Experts (MoE) language model with 760 million active parameters and 8.4 […]
A Groq-Powered Agentic Research Assistant with LangGraph, Tool Calling, Sub-Agents, and Agentic Memory: Lets Built It
In this tutorial, we build a Groq-powered agentic research workflow that runs directly using Groq’s free OpenAI-compatible inference endpoint. We […]
CopilotKit Introduces Enterprise Intelligence Platform That Gives Agentic Applications Persistent Memory Across Sessions and Devices
Most agentic applications today have a memory problem. Every time a user opens a new session, the agent starts from […]
Google AI Releases Multi-Token Prediction (MTP) Drafters for Gemma 4: Delivering Up to 3x Faster Inference Without Quality Loss
Large language models are getting incredibly powerful, but let’s be honest—their inference speed is still a massive headache for anyone […]
Build a Modular Skill-Based Agent System for LLMs with Dynamic Tool Routing in Python
In this tutorial, we build a complete skill-based agent system for large language models and explore how modular capabilities can […]
Google Adds Event-Driven Webhooks to the Gemini API, Eliminating the Need for Polling in Long-Running AI Jobs
If you’ve ever built a production AI pipeline that runs long jobs — processing thousands of prompts overnight, kicking off […]
A Coding Guide to Survey Bias Correction Using Facebook Research Balance with IPW CBPS Ranking and Post Stratification Methods
In this tutorial, we walk through a complete, end-to-end workflow for correcting bias in survey data using the balance library. […]
Zyphra Introduces Tensor and Sequence Parallelism (TSP): A Hardware-Aware Training and Inference Strategy That Delivers 2.6x Throughput Over Matched TP+SP Baselines
Training and serving large transformer models at scale is fundamentally a memory management problem. Every GPU in a cluster has […]