Google Introduces Agentic Vision in Gemini 3 Flash for Active Image Understanding

Frontier multimodal models usually process an image in a single pass. If they miss a serial number on a chip or a small symbol on a building plan, they often…

A Coding Implementation to Train Safety-Critical Reinforcement Learning Agents Offline Using Conservative Q-Learning with d3rlpy and Fixed Historical Data

In this tutorial, we build a safety-critical reinforcement learning pipeline that learns entirely from fixed, offline data rather than live exploration. We design a custom environment, generate a behavior dataset…

How to Build Advanced Quantum Algorithms Using Qrisp with Grover Search, Quantum Phase Estimation, and QAOA

In this tutorial, we present an advanced, hands-on tutorial that demonstrates how we use Qrisp to build and execute non-trivial quantum algorithms. We walk through core Qrisp abstractions for quantum…

Qwen Team Releases Qwen3-Coder-Next: An Open-Weight Language Model Designed Specifically for Coding Agents and Local Development

Qwen team has just released Qwen3-Coder-Next, an open-weight language model designed for coding agents and local development. It sits on top of the Qwen3-Next-80B-A3B backbone. The model uses a sparse…

How to Build Multi-Layered LLM Safety Filters to Defend Against Adaptive, Paraphrased, and Adversarial Prompt Attacks

In this tutorial, we build a robust, multi-layered safety filter designed to defend large language models against adaptive and paraphrased attacks. We combine semantic similarity analysis, rule-based pattern detection, LLM-driven…

Google Releases Conductor: a context driven Gemini CLI extension that stores knowledge as Markdown and orchestrates agentic workflows

Google has introduced Conductor, an open source preview extension for Gemini CLI that turns AI code generation into a structured, context driven workflow. Conductor stores product knowledge, technical decisions, and…

The Statistical Cost of Zero Padding in Convolutional Neural Networks (CNNs)

What is Zero Padding Zero padding is a technique used in convolutional neural networks where additional pixels with a value of zero are added around the borders of an image.…

NVIDIA AI Brings Nemotron-3-Nano-30B to NVFP4 with Quantization Aware Distillation (QAD) for Efficient Reasoning Inference

NVIDIA has released Nemotron-Nano-3-30B-A3B-NVFP4, a production checkpoint that runs a 30B parameter reasoning model in 4 bit NVFP4 format while keeping accuracy close to its BF16 baseline. The model combines…

How to Build Memory-Driven AI Agents with Short-Term, Long-Term, and Episodic Memory

def openai_chat(system: str, user: str) -> str: resp = client.chat.completions.create( model=OPENAI_MODEL, messages=[ “ep_id”: eid, “score”: sc, “outcome”: e.outcome_score, “task”: e.task[:140], “lessons”: ” , “ep_id”: eid, “score”: sc, “outcome”: e.outcome_score, “task”:…

A Coding and Experimental Analysis of Decentralized Federated Learning with Gossip Protocols and Differential Privacy

In this tutorial, we explore how federated learning behaves when the traditional centralized aggregation server is removed and replaced with a fully decentralized, peer-to-peer gossip mechanism. We implement both centralized…