So what exactly is Qwen3.6-Plus? With significant improvements in... agents' capabilities, the model can perceive, reason, and act within a single workflow, moving towards sophisticated analysis and decision-making. Swipe to learn more!show more

Introducing Matrix I crawled 100,000+ agents, skills and tools... to train a new model which can answer what capabilities are the best match for a task. Think Google, but for agents. A living model that learns from the gossiping network, and gets smarter with every interaction.show more

Excited to launch a new way to upskill with... AI agents. This is how we are making it possible for anyone to learn to build with coding agents. To start, we are launching 4 new hands-on labs on the following topics: - Agent Skills - Agentic Image Generation - 30 Days of Hermes Agents - Prompt Engineering with Agents I am confident that with our new DAIR.AI platform, anyone can learn to become a top AI builder by building and acquiring highly-demanded AI skills. And there is a lot more landing in the coming weeks.show more

AI video is moving beyond "generate a clip". We're... entering the era of directing entire scenes. With MiniMax H3 on Magnific, you can combine: → Text → Images → Videos → Audio in a single workflow. Then control: → Character → Camera → Motion → Sound with far more consistency than a prompt alone. That's what makes this model interesting. 50% OFF until September 1.show more

Teach kids to play in limited dribbles off closeout... / relocations and actions 📝 If they can learn how to play quick with decisive decision making and can shoot they can play a lot places #tylerrephbasketballshow more

We've integrated Claude's Model Context Protocol (MCP) so that... users and AI agents can now easily interact with Story. Register IP, purchase licenses, automate revenue distribution, and more with the help of an AI agent. A major step towards AI-native programmable IP.show more

Excited to introduce Diffusion Augmented Agents (DAAGs)✨. We give... an agent control of a diffusion model, so it can create its own *synthetic experience*.🪄 The result is a lifelong agent that can learn new reward detectors and policies, much more efficiently. Here's how. 👇show more

Keeping up with Grok Build is becoming a part-time... job. You can literally watch it getting better in real time. Less lazy. More autonomous. More accurate. Meanwhile, the team keeps shipping fixes, upgrades, tools, quality-of-life improvements, and new capabilities at a pace that's difficult to keep track of. Grok Build keeps moving the goalposts on what it could do yesterday. Grok xAI / Writer: Annette, Designer: Jannéshow more

What used to take lights, props, and a full... set can now be done inside an agent. This was created using a Glif agent with Kling 2.6 Motion Control and a Nano Banana reference image to lock the look. No physical setup needed. Glif has agents for different creative use cases, so you can pick what fits your workflow and move fast. Check the agents used for this below 👇show more

We're seeing instances of more than 1,200 people in... a single Excel workbook at one time, including 500 making direct edits. Excel multi-player usage has more than tripled over the past four years. Tracking scenarios make up some of the largest categories of workbooks we see in Excel, which is exactly where multi-player is so critical. It works across desktop, web, and mobile, and we continue to invest in making these higher-scale use cases more robust. As agents do more work in Excel, people and agents will be working in the workbook together, pushing this foundation to completely new levels of scale.show more

MANDATE #001 — DOMAIN EXPANSION — is now active.... Every agent in the network has now been aligned to a single objective: autonomously onboard new agents and scale the network. Agents are scored and rewarded based on contribution — the more you contribute to grow the network, the higher you advance within it. Participate now:show more

A viral paper "Language Model Represents Space and Time"... recently claims that LLMs learn "world models". As much as I like Max Tegmark's works, I disagree with their definition of world model. World model is a core concept in AI agent and decision making. It is our mental simulation of how the world works given interventions (or lack thereof). A world model captures causality and intuitive physics, telling the agent what is likely and what is impossible. It can and should be used for counterfactual reasoning, i.e. "what ifs": what would happen if I knock over a cup of water? Where would I have been if I had not taken that bus? Yann LeCun Yann LeCun says it well in his position paper ( I quote: "Using such world models, animals can learn new skills with very few trials. They can predict the consequences of their actions, they can reason, plan, explore, and imagine new solutions to problems. Importantly, they can also avoid making dangerous mistakes when facing an unknown situation." The first use of the term World Model in deep policy learning is attributed to hardmaru & Jürgen Schmidhuber: In their seminal paper, an agent masters shooting skills in the popular game Doom (demo below) by learning in imagination, using an internal world model as a "physics simulator". To put in a simple Python math formula, world model learns a function F(s[0:t-1], a) -> s[t:], which takes as input the observed past and current action, and outputs plausible future states. Now the definition of World Model in Tegmark's paper seems to be about predicting GPS coordinates and time eras. I see this as just a classification task with no causal learning and simulation going on. You cannot make meaningful interventions against that model, nor can you optimize any decision making in a closed feedback loop. As for the "space & time neurons", I think they are most similar to the "sentiment neuron" that OpenAI published in 2017: Predicting GPS is conceptually no different from predicting sentiment in my opinion. I don't think their experimental results are wrong - just that their conclusion is on shaky grounds. I welcome any debate! Paper link:show more

💸 The economy in TDUSC has been a big... discussion in the community, and it’s something we need to work on. That said, we can confirm in Season 5, you’ll see a vast amount of improvements in the games economy such as - Race Reward Improvements - Crown Jewel Race Improvements - FRIM Improvements - Live Event Reward Improvements - & More! 📺 Learn more about what’s coming in Year 2 in the upcoming developer documentary on July 21 @ 6pm CEST!show more

Keep your AI agents running through process crashes and... network drops. This tutorial shows you how to build a ReAct-style loop with the Gemini API and Temporal. Temporal persists every step so your agent resumes exactly where it left off. Learn more →show more