Machine learning news — deep learning, reinforcement learning, neural architecture search, diffusion models, and new ML frameworks and libraries.
A front-end web developer with no prior machine learning background began learning ML from scratch using Andrew Ng’s specialization and a self-made study plan. Over the first 30 days, they focused on math foundations lik…
This article is a practical, production-oriented guide to building AI agents, focusing on engineering patterns rather than hype or specific products. It explains why agent demos often fail in production, defines an agent…
At Google I/O 2026, the company shifted its focus from conversational AI to autonomous "agentic" systems capable of reasoning, planning, and executing real-world workflows. Key announcements included Gemini Omni for unif…
This article summarizes research by Tasfin Mahmud on addressing observational bias in recommender systems using Graph Neural Networks (GNNs) and Causal Reinforcement Learning. The author implemented an open-source framew…
Adhi, an Artificial Intelligence & Data Science student, has introduced himself to the DEV Community, outlining his focus on AI, Machine Learning, Full Stack Development, Generative AI, and Data Science. He emphasizes a …
The article describes the "XiHan Snore Coach," a project that uses Google's Gemma 4 AI model to create a privacy-focused, offline sleep apnea monitoring system for edge devices. By processing all sensitive biometric data…
NVIDIA released Nemotron-Labs Diffusion on May 23, 2026, a family of diffusion language models (DLMs) that generate entire blocks of tokens in parallel and iteratively refine them, rather than producing one token at a ti…
The article introduces **llm-nano-vm v0.8.0**, a deterministic Finite State Machine (FSM) runtime for LLM pipelines that flips the typical architecture by making the runtime the orchestrator rather than the LLM. Key new …
This article describes a project called Smart Kitchen AI, a multimodal cooking assistant built using Google's Gemma 4 31B Dense model. The system allows users to upload a photo of their refrigerator, which the AI then an…
The article provides a technical deep dive into Google's Gemma 4 model, explaining how its 1.5 GB size achieves a 37.5% score on competition mathematics through a Mixture-of-Experts (MoE) architecture. It details the mec…
This article explains how to build a supervisor-based multi-agent architecture in pure Python without using external frameworks. It describes the "Supervisor Pattern," where a central orchestrator coordinates specialized…
The article describes a prototype integration between Hermes Agent and .klickd, an open portable memory format for AI agents, designed to reduce repeated context costs by allowing agents to load structured, encrypted, ve…
This article describes the development of an autonomous healthcare booking agent using LangGraph, Playwright, and OpenAI Functions. The agent analyzes lab reports to identify medical anomalies and, when necessary, autono…
The article describes a practical implementation of a multi-agent AI architecture where seven different AI models (including Claude Opus, MiniMax, Hermes, Gemini, and Groq Llama) work together autonomously 24/7, coordina…
The article describes the revival of NeuroScale, a broken MLOps platform that was abandoned in April 2026 after Backstage, ArgoCD, and KServe all failed. The author rebuilt it into a self-service AI inference platform us…
The article explains the ReAct (Reasoning and Acting) agent paradigm, introduced by researchers from Princeton and Google in 2022, which improves upon Chain-of-Thought (CoT) reasoning by allowing a language model to alte…
The article introduces Nemotron-Labs Diffusion, a family of language models that use a diffusion-based approach to generate multiple tokens in parallel and iteratively refine them, offering a faster alternative to tradit…
The article describes the creation of a Visual Regression & Patch Agent built on Google's Gemma 4 model, which combines multimodal vision reasoning with closed-loop patch validation to automatically diagnose and fix fron…
A production RAG system handling 12,000 queries per day suffered an estimated $40,000 in losses over three weeks due to silent errors caused by vector embedding drift. The root cause was an embedding model update from te…
The article describes the development of OkkanaiPai, a free, offline iOS app that predicts dangerous mahjong discards using a rule-based system calibrated against 4.97 million real hands from Tenhou's top competitive tie…