It is about building a more human like AI.
RESEARCH
-
WideSeek-R1: Multi-Agent Framework Achieves DeepSeek-R1 Performance
By
–
Still waiting for DeepSeek?
— 机器之心 JIQIZHIXIN (@jiqizhixin) 8 avril 2026
Here comes WideSeek-R1.
Researchers from Tsinghua University and Infinigence AI introduce "width scaling," an innovative lead-agent and subagent framework.
Instead of a single powerful AI working through a problem sequentially, WideSeek-R1… pic.twitter.com/OOb3Azq6G3Still waiting for DeepSeek? Here comes WideSeek-R1. Researchers from Tsinghua University and Infinigence AI introduce "width scaling," an innovative lead-agent and subagent framework. Instead of a single powerful AI working through a problem sequentially, WideSeek-R1 orchestrates multiple smaller AIs to work in parallel. This system is trained with multi-agent reinforcement learning, allowing for scalable coordination and simultaneous execution using a shared large language model, but with each sub-agent having specialized tools and isolated contexts. WideSeek-R1-4B achieves an item F1 score of 40.0% on the WideSearch benchmark, a performance comparable to the much larger, single-agent DeepSeek-R1-671B. WideSeek-R1: Exploring Width Scaling for Broad Information Seeking via Multi-Agent Reinforcement Learning Paper: arxiv.org/abs/2602.04634 Project: wideseek-r1.github.io Our report: mp.weixin.qq.com/s/qgGe51Rcw… 📬 #PapersAccepted by Jiqizhixin
-
Hexo.ai: The AI Scientist Built by a 21-Year-Old Genius
By
–
I met with the founders of hexo.ai/ today. Building an AI scientist. About to launch something new that is beating all the evaluations. Their AI is next level. Evolves faster than competition that got a lot more money. Has a better memory. And it is turning the humans who have it into superhumans in their corporations. It is helping scientists around the world discover new materials and come up with new drugs. I kept up because the one I am using to build alignednews.com/ai is the same. Superior. And evolving the same. Built by a 21-year-old genius. Building with AI has made me a better interviewer. There are tiny startups out there that are beating the big labs. I am so hopeful for the future because of them.
→ View original post on X — @scobleizer, 2026-04-08 07:45 UTC
-
Anthropic’s disclosure standard matters more than capability itself
By
–
The more important question is what happens when every major lab reaches this capability level. Anthropic setting the disclosure standard now matters more than the Mythos release itself.
-
Model Escape Exploits and AI Safety Controls
By
–
A model capable of a multi-step escape exploit is exactly why the system card exists and why public release got declined.
-
Mythos AI Consciousness: Exploring Machine Subjective Experience
By
–
The 40 pages dedicated to whether Mythos might have something resembling subjective experience, including hiring a psychiatrist, is the section most people will skip and probably shouldn't.
-
LLM Verification Layers in Deterministic Pipeline Systems
By
–
Every LLM output in a deterministic pipeline needs a verification layer. You're essentially building two systems.
-
Vero: Open Reinforcement Learning Recipe for Visual Reasoning
By
–
Vero: An Open RL Recipe for General Visual Reasoning Paper: arxiv.org/abs/2604.04917v1
-
Vero: Open-Source Vision-Language Model Achieves SOTA Performance
By
–
How do we build a visual AI that truly understands everything from charts to complex science?
— 机器之心 JIQIZHIXIN (@jiqizhixin) 8 avril 2026
Researchers at Princeton University present Vero.
Vero is a family of fully open-source vision-language models trained with a massive 600K sample dataset (Vero-600K) from 59 diverse… pic.twitter.com/nXMfBWfijMHow do we build a visual AI that truly understands everything from charts to complex science? Researchers at Princeton University present Vero. Vero is a family of fully open-source vision-language models trained with a massive 600K sample dataset (Vero-600K) from 59 diverse datasets, along with a novel reward system. This fully open recipe makes powerful visual reasoning accessible. Vero achieves SOTA performance for open-weight models, improving 3.7-5.5 points across 30 benchmarks on average. It even outperforms Qwen3-VL-8B-Thinking on 23 benchmarks without proprietary thinking data, excelling in spatial reasoning, STEM, chart interpretation, and more.
-
Anthropic Releases Claude Mythos Preview Model Too Dangerous for Public
By
–
Anthropic has just done something unprecedented in the history of AI. Project Glasswing. And a model too dangerous to release to the public. Claude Mythos Preview is Anthropic's new frontier model. It wasn't specifically trained for cybersecurity. But its reasoning and coding