Hugging Face's logo
Ksenia Se's picture
1 100 3

Ksenia Se

Kseniase
bengii's profile picture FlavioD's profile picture jcmt2k's profile picture
·
https://www.turingpost.com/

AI & ML interests

None yet

Recent Activity

replied to their post 7 days ago
9 Recent advances in Multi-Agent Systems (all open-source) The idea to split tasks across multiple agents instead of relying on one universal agent is now seen as one of the most effective ways to build an AI stack. Concepts like “agent swarms” were highlighted at the AI Engineer Code Summit in NYC (Nov 20–21) as the winning architecture. And this trend is not only about coding and software. It applies across all AI domains. So here is some recent research that helps keep multi-agent systems (MAS) better and up-to-date: 1. LatentMAS → https://huggingface.co/papers/2511.20639 AI agents share their hidden "thoughts" directly in latent space instead of talking through text. This makes collaboration and reasoning way faster and accurate (no extra training needed) 2. Puppeteer → https://huggingface.co/papers/2505.19591 Uses a “puppeteer” LLM that dynamically decides which agents (“puppets”) to call and in what order. By learning this orchestration with reinforcement learning (RL), the system solves complex tasks more efficiently and with fewer compute costs 3. MADD → https://huggingface.co/papers/2511.08217 A MAS with 4 agents for drug discovery. It lets researchers describe a drug discovery task in plain language. Then MADD automatically builds and runs the full hit-identification pipeline, making AI-driven drug design a simple end-to-end workflow 4. Multi-Agent Tool-Integrated Policy Optimization (MATPO) → https://huggingface.co/papers/2510.04678 Lets one LLM act as multiple agents (like a planner and a worker) by using different prompts and training them together with RL. So you get the benefits of a multi-agent system without needing multiple models If you're interested in trends in multi-agent for software development of the future, explore my article with the emergent playbook. This is super interesting → https://www.turingpost.com/p/aisoftwarestack Also, subscribe to the Turing Post: https://www.turingpost.com/subscribe Read further below ⬇️
posted an update 7 days ago
9 Recent advances in Multi-Agent Systems (all open-source) The idea to split tasks across multiple agents instead of relying on one universal agent is now seen as one of the most effective ways to build an AI stack. Concepts like “agent swarms” were highlighted at the AI Engineer Code Summit in NYC (Nov 20–21) as the winning architecture. And this trend is not only about coding and software. It applies across all AI domains. So here is some recent research that helps keep multi-agent systems (MAS) better and up-to-date: 1. LatentMAS → https://huggingface.co/papers/2511.20639 AI agents share their hidden "thoughts" directly in latent space instead of talking through text. This makes collaboration and reasoning way faster and accurate (no extra training needed) 2. Puppeteer → https://huggingface.co/papers/2505.19591 Uses a “puppeteer” LLM that dynamically decides which agents (“puppets”) to call and in what order. By learning this orchestration with reinforcement learning (RL), the system solves complex tasks more efficiently and with fewer compute costs 3. MADD → https://huggingface.co/papers/2511.08217 A MAS with 4 agents for drug discovery. It lets researchers describe a drug discovery task in plain language. Then MADD automatically builds and runs the full hit-identification pipeline, making AI-driven drug design a simple end-to-end workflow 4. Multi-Agent Tool-Integrated Policy Optimization (MATPO) → https://huggingface.co/papers/2510.04678 Lets one LLM act as multiple agents (like a planner and a worker) by using different prompts and training them together with RL. So you get the benefits of a multi-agent system without needing multiple models If you're interested in trends in multi-agent for software development of the future, explore my article with the emergent playbook. This is super interesting → https://www.turingpost.com/p/aisoftwarestack Also, subscribe to the Turing Post: https://www.turingpost.com/subscribe Read further below ⬇️
replied to their post 14 days ago
6 Essential Reads on Spatial Intelligence In AI, spatial intelligence is basically the model’s “sense of space” – its ability to understand where things are, how they relate, and how they move. It lets an AI models navigate a room, interpret a scene, or figure out how objects fit together, like giving it a built-in mental map. For example, world models can't live without spatial intelligence. Here are 6 good reads to explore what spatial intelligence is and how it's evolving: 1. From Words to Worlds: Spatial Intelligence is AI’s Next Frontier by Fei-Fei Li → https://drfeifei.substack.com/p/from-words-to-worlds-spatial-intelligence Fei-Fei Li, the godmother of AI, is a key figure in spatial intelligence, since her work in computer vision, especially ImageNet, helped AI learn to recognize and understand objects in space. She's recently started a blog, and this post, in particular, argues that true intelligence requires grounding in space, understanding geometry, motion and consequences in the real world 2. Spatial Reasoning in Multimodal LLMs: A Survey of Tasks, Benchmarks and Methods → https://arxiv.org/abs/2511.15722 Breaks down how AI models handle spatial reasoning from a cognitive angle, maps all the existing tasks and benchmarks to that framework 3. What is Spatial Intelligence? → https://www.turingpost.com/p/cvhistory5 Our special article easily explains what spatial intelligence actually is, why it matters, and how researchers are trying to boost it so machines can better understand and navigate the physical world 4. From 2D to 3D Cognition: A Brief Survey of General World Models → https://arxiv.org/pdf/2506.20134 Shows how AI world models are evolving from simple 2D perception to full-on 3D understanding, explaining the tech behind it, what new 3D abilities these models gain, and where they’re used in the real world Read further below ⬇️ If you like it, also subscribe to the Turing Post: https://www.turingpost.com/subscribe
View all activity

Organizations

Turing Post's profile picture Journalists on Hugging Face's profile picture Social Post Explorers's profile picture Hugging Face Discord Community's profile picture Sandbox's profile picture