AI

In this tutorial, we use an advanced AI system using i CAMEL framework, organizing many specialized agents to jointly solve a complex task. We design a structured multi-agent pipeline that includes an editor, researcher, writer, critic, and rewriter, each with clearly defined responsibilities and outcomes limited by the schema. We combine tooling, adaptive sampling, systematic … Read more

Alibaba’s Qwen Team has released Qwen3.6-27B, the first dense open weight model in the Qwen3.6 family – and arguably the 27 billionth parameter model available today for coding agents. It brings major improvements in agent coding, a novel approach to Conservation Thinking, and a hybrid architecture that combines Gated DeltaNet direct attention with traditional attention … Read more

BATCH = 128 EPOCHS = 30 steps_per_epoch = len(X_train) // BATCH train_losses, val_losses = [], [] t0 = time.time() for epoch in range(EPOCHS): key, sk = jax.random.split(key) perm = jax.random.permutation(sk, len(X_train)) X_s, Y_s = X_train[perm], Y_train[perm] epoch_loss = 0.0 for step in range(steps_per_epoch): xb = X_s[step*BATCH:(step+1)*BATCH] yb = Y_s[step*BATCH:(step+1)*BATCH] model, opt_state, loss = train_step(model, opt_state, … Read more

How to make multiple agents work together as a special team – automatically dividing tasks, communicating effectively, and collaborating seamlessly? The openJiuwen community has released the latest version of JiuwenClaw, which adds support for AgentTeam — the ability to collaborate with multiple agents. It suggests that the next leap beyond Harness Engineering be Coordinating Engineering. … Read more

A year or two ago, using advanced AI models felt expensive enough that you had to think twice before asking anything. Today, using those same models feels cheap enough that you don’t even notice the cost. This is not just because “technology has advanced” in a vague sense. There are some reasons behind it, and … Read more

Design has traditionally required multiple roles working in sequence: strategist to describe the problemdesigner to prepare the solutionand engineers to build it. This means coordinating timelines, aligning ideas, and going through rounds of iteration before anything tangible is created. Claude Design removes much of this conflict by turning ideas into practical results. What once took … Read more

For all the progress made in AI agent development over the past few years, one key problem remains unsolved: most people never interact with agents. They live behind developer dashboards, inside special apps that users are asked to download, and in chat rooms that most people in the world will never visit. Beautiful models. Thinking … Read more

Debugging an AI agent that uses multiple steps: reading files, calling APIs, writing code, and updating the output, is not the same as debugging a normal task. Not a single stack trace can be read. Instead, developers are left staring at hundreds of lines of raw JSON, trying to reconstruct what the model was actually … Read more

Hugging Face is released ml-internis an open source AI agent designed to automate end-to-end workflows for large-scale linguistic models (LLMs). It is built on the company smolagents framework, the tool can automate literature review, dataset acquisition, scripting training, and iterative testing – tasks that typically require significant effort from ML researchers and developers. What does … Read more

Training powerful AI models relies on one resource that is running out of steam: specialized data. While the Internet has provided a seemingly endless supply of text and images to train today’s standard models, the next wave of AI breakthroughs – in cybersecurity, forensics, healthcare, and other niche domains – requires data that is not … Read more