Auto Added by WPeMatico
Low-code and no-code platforms have moved from simple drag-and-drop builders to AI-native development environments. In 2026, most of them ship a built-in assistant that turns a text prompt into a working app, agent, or automation. This list covers 21 tools that AI practitioners use today, grouped by what they do best. Each tool name links […]
Most search agents are trained as policies over a growing transcript. The model decides how to search. It must also remember what it saw, which evidence matters, and which claims it checked. A team of researchers from University of Illinois Urbana-Champaign, UC Berkeley, and Chroma argues this asks too much. Reinforcement learning ends up optimizing
In this tutorial, we analyze NVIDIA garak as a practical framework for defensive LLM red-teaming. We start by setting up Garak, then move through plugin discovery, dry runs, real-model scans, multi-probe evaluations, report analysis, custom probe creation, custom detector creation, and AVID export. Instead of running only a single scan, we use Garak end-to-end to
This week, Google AI team released the Colab CLI. The tool connects your local terminal to remote Colab runtimes. It lets developers and AI agents run code on cloud GPUs and TPUs. You stay in your terminal the entire time. The CLI is open source under the Apache 2.0 license. What is Google Colab CLI
Moonshot AI has released Kimi Code CLI, an open-source coding agent that runs in the terminal. The tool reads and edits code, runs shell commands, searches files, and fetches web pages. It then chooses its next step based on the feedback it receives. The project is MIT-licensed and lives on GitHub.. Kimi Code CLI is
NVIDIA’s Nemotron Speech team has released Nemotron 3.5 ASR. It is a 600M-parameter streaming Automatic Speech Recognition (ASR) model. A single checkpoint transcribes 40 language-locales in real time. Punctuation and capitalization are built in natively. The model ships as open weights on Hugging Face. The license is OpenMDW-1.1. The architecture is a Cache-Aware FastConformer-RNNT. What
Google DeepMind released Quantization-Aware Training (QAT) checkpoints for the Gemma 4 family. The release targets local deployment on edge devices and consumer GPUs. It follows the Gemma 4 launch in April and a 12B model two days earlier. We compared the available Gemma 4 edge-model formats using only published numbers. The goal was simple. Show
In production inference deployments, demand fluctuates over time, requiring inference replicas to scale elastically. Cold-starting inference workloads on Kubernetes can take several minutes. During that time, GPUs are allocated but idle, generating no tokens and serving no requests. ‘Cold start’ means the full sequence a model server must complete before serving any request: pulling the
In this tutorial, we set up Microsoft Fara in Google Colab and run a browser-use workflow from start to finish. We begin by cloning the repository, installing the package, preparing Playwright, and verifying that the installed Fara files work even when the package layout changes. Instead of immediately relying on a heavy Fara-7B deployment, we
AI-first development is changing how software gets built. A new approach called “vibe coding” sits at the center of that shift. Developers describe what they want in plain language. An AI agent turns that description into working software. The term was coined by Andrej Karpathy. It captures a move away from line-by-line coding toward natural-language
15 Best Vibe Coding Tools in 2026 Compared: Pricing, Features, and Best Fit Read More »
