AI News Topics
robotics
7 concise briefings covering robotics.
IEEE Spectrum
18 Jul 2026
Sarah Downs, now a Ph.D. student at Texas A&M, created a force-based insertion algorithm that lets a robotic arm assemble satellite antennas in zero gravity without relying on cameras. Her work, done with NASA and the U.S. Air Force during her master’s, addresses peg‑in‑hole insertion and compensates for reaction torques in space.
TechCrunch AI
18 Jul 2026
Agility Robotics is opening a new training center for its bipedal Digit robots in Fremont, California. The facility positions the company geographically near Tesla and aims to scale operator training and field testing for its humanoid platform.
Google DeepMind Blog
13 Jul 2026
Google DeepMind and India’s Atal Innovation Mission introduced ATL Saathi, an AI assistant powered by Gemini to help teachers run robotics labs. The tool is designed to guide educators with curriculum-aligned support and hands-on project help in school innovation spaces.
IEEE Spectrum
13 Jul 2026
X Square Robot outlines an open embodied-AI stack combining curated interaction data, an event-oriented world model (WALL-WM), and a pretrained action model (Wall-OSS-0.5) with a semantic action tokenizer. The company emphasizes data validity through physical replay and claims cross-embodiment transfer and deployable pretraining before fine-tuning, while noting most results come from its own robots and benchmarks.
OpenAI News
11 Oct 2016
OpenAI News melaporkan kajian tentang pemindahan tingkah laku dari simulasi ke dunia sebenar menggunakan model dinamik songsang mendalam. Laporan itu menyatakan pendekatan ini belajar pemetaan antara tindakan dan hasil pergerakan untuk membantu mengurangkan jurang antara simulasi dan aplikasi praktikal.
OpenAI News
01 Apr 2017
OpenAI melaporkan mereka mencipta AI pengesan spam pertama di dunia yang dilatih sepenuhnya dalam simulasi. Model itu kemudian dilaksanakan pada robot fizikal.
OpenAI News
07 Nov 2018
OpenAI membangunkan model berasaskan tenaga yang cepat mempelajari konsep spatial seperti 'near', 'above', 'between', 'closest' dan 'furthest' daripada hanya lima demonstrasi dalam bentuk set titik 2D. Model itu juga menunjukkan pemindahan lintas domain apabila konsep yang dipelajari digunakan untuk menyelesaikan tugas pada robot berasaskan fizik 3D.