Microsoft AI Releases Fara-7B: An Efficient Agentic Model for Computer Use
How do we safely let an AI agent handle real web tasks like booking, searching, and form filling directly on our own devices without sending everything to the cloud? Microsoft…
AI Interview Series #3: Explain Federated Learning
Question: “You’re an ML engineer at a fitness company like Fitbit or Apple Health. Millions of users generate sensitive sensor data every day — heart rate, sleep cycles, step counts,…
NVIDIA AI Releases Nemotron-Elastic-12B: A Single AI Model that Gives You 6B/9B/12B Variants without Extra Training Cost
Why are AI dev teams still training and storing multiple large language models for different deployment needs when one elastic model can generate several sizes at the same cost? NVIDIA…
Moonshot AI Researchers Introduce Seer: An Online Context Learning System for Fast Synchronous Reinforcement Learning RL Rollouts
How do you keep reinforcement learning for large reasoning models from stalling on a few very long, very slow rollouts while GPUs sit under used? a team of researchers from…
How to Design a Mini Reinforcement Learning Environment-Acting Agent with Intelligent Local Feedback, Adaptive Decision-Making, and Multi-Agent Coordination
In this tutorial, we code a mini reinforcement learning setup in which a multi-agent system learns to navigate a grid world through interaction, feedback, and layered decision-making. We build everything…
Google DeepMind Introduces Nano Banana Pro: the Gemini 3 Pro Image Model for Text Accurate and Studio Grade Visuals
Nano Banana Pro, also called Gemini 3 Pro Image, is Google DeepMind’s new image generation and editing model built on Gemini 3 Pro. It is positioned as a state of…
Perplexity AI Releases TransferEngine and pplx garden to Run Trillion Parameter LLMs on Existing GPU Clusters
How can teams run trillion parameter language models on existing mixed GPU clusters without costly new hardware or deep vendor lock in? Perplexity’s research team has released TransferEngine and the…
Meta AI Releases Segment Anything Model 3 (SAM 3) for Promptable Concept Segmentation in Images and Videos
How do you reliably find, segment and track every instance of any concept across large image and video collections using simple prompts? Meta AI Team has just released Meta Segment…
An Implementation of Fully Traced and Evaluated Local LLM Pipeline Using Opik for Transparent, Measurable, and Reproducible AI Workflows
In this tutorial, we implement a complete workflow for building, tracing, and evaluating an LLM pipeline using Opik. We structure the system step-by-step, beginning with a lightweight model, adding prompt-based…
How to Build a Fully Offline Multi-Tool Reasoning Agent with Dynamic Planning, Error Recovery, and Intelligent Function Routing
In this tutorial, we explore how to build a fully offline, multi-step reasoning agent that uses the Instructor library to generate structured outputs and reliably orchestrate complex tool calls. In…















